Quantum computing is rapidly advancing, driven by significant global investments, including the UK's £2.5 billion funding for quantum research.

China is a major player in quantum research, spending an estimated $15.3 billion, rivaling the United States.

The US is investing heavily in quantum computing, led by companies like IBM, Google, and Microsoft.

Countries like Canada, Germany, and Australia are also investing heavily in quantum computing, with Canada spending over $1 billion in the past decade.

The global quantum computing market is expected to reach $1 trillion by 2035, led by companies like Google and IBM.

Quantum computing can revolutionize industries like finance, healthcare, and logistics by solving complex problems.

IBM, Mercedes-Benz, and others are exploring quantum computing in their products and services.

Quantum computing has the potential to bring breakthroughs in fields like cryptography, drug discovery, and machine learning.

There are significant challenges, including the need for robust quantum error correction and noise reduction.

The quantum computing market is expected to grow 36.89% annually from 2022 to 2032, reaching USD 234.06 billion.

Major players in the quantum computing market include IBM, Google, Microsoft, Honeywell, Intel, and Rigetti Computing.

Google achieved quantum supremacy in 2019 with its Sycamore processor.

IBM achieved quantum supremacy in 2021 with its 127-qubit Eagle processor.

IBM plans to have a 1,121-qubit quantum processor called Condor ready by the end of 2023.

Google has achieved a breakthrough in quantum computing by increasing qubit array size while reducing error rates.

Developing low-error quantum computing systems is key to creating a universal quantum computer, with Google and IBM at the forefront.

The UK government has allocated £2.5 billion for quantum research.

The US and China dominate the quantum computing sector with significant research investments.

IBM and a Chinese university are developing record-breaking quantum computers, one surpassing Google's by 10 billion times.

Quantum computing has various applications, including mathematical models, simulation, electronic devices, and medical imaging.

The global quantum computing market is expected to grow from $472m in 2021 to $1.77bn by 2026 at a 30.2% compound annual growth rate.

Adoption of quantum computing by financial services companies is expected to drive market growth.

Big Tech companies like Microsoft, Amazon, IBM, and Google offer cloud services for quantum simulator experimentation.

IBM's quantum accelerator programme helps businesses find quantum computing use cases, amid financial services concerns over cryptography.

By 2025, 40% of large companies plan to launch quantum computing initiatives, says Gartner.

Quantum computing can greatly increase calculation and transaction speed and volume, representing a significant change for the financial services sector.

Quantum computing development requires collaboration between academia, industry, and government, with countries like China, the US, and the EU investing heavily.

The National Quantum Mission aims to develop intermediate-scale quantum computers with 50-1,000 physical qubits using technologies like superconducting and photonic systems.

Quantum computing combines quantum mechanics and computer science, using qubits instead of traditional bits.

Qubits can represent both 0 and 1 states simultaneously through superposition, enabling parallelism.

Quantum computers can tackle challenges limiting traditional computers.

Quantum computing has wide applications in fields like drug development, finance, security, and defense.

China, the US, and the EU have invested $9.7 billion, $1.9 billion, and $1.1 billion, respectively, in quantum computing.

Quantum algorithms can significantly reduce the time required to solve complex problems, making some currently unsolvable problems solvable.

Researchers in Japan have developed an algorithm to accelerate a specific quantum computing workload.

Quantum algorithms and software ecosystems are being researched for potential applications in finance, climate, and logistics.

Quantum programming languages facilitate quantum information processing, enabling advancements in cryptography, optimization, and simulation.

The Finnish government believes building a quantum computer will prepare them for its adoption in various industries, including healthcare, finance, and security.

Novo Nordisk is launching a 12-year initiative to develop a full-scale quantum computer for medicine and other applications.

Scientists have developed a quantum algorithm to identify promising compounds for carbon sequestration, aiding the fight against climate change.

Quantum error correction maintains quantum information for a longer period than uncorrected hardware components.

Yale scientists, led by Michel Devoret, used quantum error correction to more than double a quantum bit's lifetime to 1.8 milliseconds.

China has delivered a 24-qubit quantum computer system, becoming the third country to do so after Canada and the US.

Google, IBM, and China have achieved quantum supremacy, with Google being the first in 2019.

IBM researchers discovered an error correction approach that reduces required qubits by a factor of 10.

The new approach connects each qubit to six others, increasing the information that can be encoded.

Entropica Labs, a Singapore-based quantum software startup, has received $4.7 million in A-round funding.

Developing large-scale quantum computers is hindered by the need for robust error correction and noise reduction.

Quantum error correction is a key challenge in developing large-scale quantum computers, with companies like Entropica Labs working on software solutions.

The Cloud-based Quantum Computing Market is projected to reach USD 6,289.8 Million by 2030, growing at a 35.5% CAGR.

Major vendors in the Global Cloud-Based Quantum Computing Market include Accenture, AWS, Baidu, Cambridge Quantum, D-Wave, Google, IBM, and Microsoft.

The market is growing as organizations seek to harness quantum processors through cloud services.

Cloud-based quantum computing democratizes access, allowing businesses to explore without extensive on-premises infrastructure.

Investment in quantum technology reached a record $2.35 billion in 2022.

68% of total quantum technology investment since 2001 has occurred in the last two years.

Quantum technology could add $1.3 trillion in value by 2035, a McKinsey report says.

Four industries will likely be impacted first by quantum technology: automotive, chemicals, financial services, and life sciences.

The next stage in quantum computing requires developing 'fault-tolerant' processors to solve real-world problems more accurately and faster.

IBM is developing two types of quantum processors: one with over 1,000 qubits and another with fewer, but higher-quality qubits.

Difficult challenges remain in the five main approaches to quantum computers, including scaling control and cooling systems.

Quantum computing scale-up requires top talent, but a significant gap still exists.

The talent gap is narrowing, with nearly two-thirds of open jobs potentially fillable with new master's-level graduates.

In 2022, 717 job postings remained unfilled despite 450 applicable master's-level graduates.

The EU and UK were top destinations for quantum technology graduates in 2020, with 303 and 217 graduates per million inhabitants, respectively.

North America leads the Cloud-based Quantum Computing market, driven by the US and Canada.

The research and academia segment is expected to hold the largest market share due to its active involvement in advancing quantum technologies.

Cloud-based platforms enable researchers and students to experiment with quantum computing collaboratively.

The market is growing as organizations seek to harness quantum processors through cloud services.

Cloud-based quantum computing democratizes access, allowing businesses to explore without extensive on-premises infrastructure.

Quantum computers use qubits that can be 0, 1, or both, enabling exponential increases in computing power.

Google's Sycamore processor completed a calculation in 200 seconds that would take a classical computer 10,000 years.

Quantum error-correction protocols, like surface code and cat code, are being developed to detect and correct qubit errors.

High hardware costs hinder quantum computing adoption.

A shortage of skilled quantum computing experts hinders its adoption.

Technical difficulties hinder the development of large-scale quantum computers.

Limited access to quantum experts restrains the quantum computing market's growth.

Few practical quantum computing applications have been developed, hindering its adoption.

Regulatory challenges, especially data privacy and security, may hinder quantum computing adoption.

Research and development are expected to overcome the obstacles in the quantum computing market.

Investments by governments, institutions, and companies are driving innovation in quantum computing.

Partnerships between quantum computing companies, academic institutions, and research organizations are creating opportunities for new quantum hardware and software development.

Cloud-based quantum computing services are making the technology more accessible to companies and researchers.

Quantum computing is rapidly advancing, driven by significant global investments, including the UK's £2.5 billion funding for quantum research.

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  1. Hardware
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April 25, 2023

Investment in quantum technology hit a record $2.35bn last year

Billions of dollars have been invested in quantum technology since 2001 with the majority of that investment happening since 2020.

By Ryan Morrison

Quantum technology companies attracted more than $2.35bn in private investment last year, slightly breaking the record set in 2021. A new report by McKinsey suggests this investment could be well placed, as companies deploying quantum stand to gain $1.3trn in value by 2035. To unlock this potential companies have to focus on attracting top talent and scaling up the speed and accuracy of qubits. One expert says public and private sector organisations have a role to play in solving the talent problem.

The McKinsey report suggests four industries are likely to see the earliest impact – automotive, chemicals, financial services and life sciences. This is because these areas have high compute needs and complex problems where quantum advantage is likely to come earlier.

A significant amount of investment in quantum technology is going to start-ups that came into the industry in the past two years. According to McKinsey, 68% of the money put into quantum since 2001 has been invested in the last two years

As of last year, that investment is being spread over fewer new companies. In 2021, 41 quantum technology start-ups were founded, dropping to 19 in 2022 which, according to McKinsey suggests money is going to established start-ups rather than new companies, which could be tied to difficulties in attracting new talent.

The report suggests investors are looking for companies “ready to scale”, with four of the ten largest investment deals since 2001 closed in 2022. Some of these have been worth up to $500m and seven of the ten largest deals in 2022 were worth more than $100m.

Public sector investment is also growing rapidly with the US committing $1.8bn in 2022, the UK will spend £2.5bn over a decade and the EU has $1.2bn for quantum on the table. These are all dwarfed by the estimated $15.2bn public investment in quantum announced by the Chinese government.

Another reason for the redirection of investment towards more established companies could be tied to the slowdown in major scientific breakthroughs, the report authors speculated.

Many of the early-stage quantum technology companies are formed out of university projects and in 2022 the number of published papers on quantum technology declined by 61% between 2020 and 2021. There was another decline, of about 5% between 2022 and 2021. This, they wrote, could be due to challenges becoming harder to solve.

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Need for ‘fault -olerant’ quantum machines

The next stage in quantum computing requires both a ramp-up in qubit numbers and quality to create “fault-tolerant” processors capable of solving real-world problems more accurately and faster than classical computers. The problem is that while qubit numbers have been growing steadily, the quality hasn’t kept pace.

IBM has gone from a 20-qubit processor in 2019 to announcing a 1,000+ qubit machine due for release next year, but it also has a second track of processors with better quality qubits but far fewer actual qubits on each chip.

“In each of the five main approaches to quantum computers, difficult challenges remain,” the authors wrote. This is across all the main types of qubit being developed. For example, in photonics these devices still “leak” photons which results in computation failures and high error rates. In superconducting systems like those used by IBM and Google there are issues scaling up the control and cooling systems to handle potentially thousands of qubits.

These problems have to be solved to unlock the economic value the technology holds, the report authors declared. As economic value depends on speedup, which depends on algorithm complexity, execution time and problem size.

Achieving this scale-up will require top talent and while the talent gap is “significant”, McKinsey suggests it is narrowing in quantum technologies. “Our analysis shows that nearly two-thirds of open jobs in the industry could be filled with new masters’-level graduates in 2022.”

There are still shortages though, with OECD figures showing 717 active job postings last year and 450 master's-level graduates with degrees applicable to those vacancies. This was better than in 2021 when there were 851 job vacancies and just 290 graduates.

Talent isn't evenly spread. Based on density per million inhabitants the EU and UK are top destinations for graduates in quantum technology-relevant fields with 303 per million graduating in the EU in 2020 and 217 per million in the UK.

Ekaterina Almasque, general partner at VC fund OpenOcean, told Tech Monitor the quantum industry was “in its growth phase”, making it extremely challenging to find talent with the necessary skills across a range of technologies and services. “Most individuals working in the industry today were introduced to the concept of quantum computing at a relatively late stage," Almasque says. "While this will change naturally as the industry becomes more established, the private and public sector stakeholders of quantum computing must work together to improve this.”

She adds: “From a European perspective, many pioneering quantum computing businesses are pushing to become world leaders. For Europe to properly establish and maintain a lead in quantum computing, there must be a broad, strategic initiative for early education in quantum computing.”

  • Ryan Morrison writes a new weekly newsletter, Quantum Untangled, looking at the practical applications of quantum computing and interviewing leading figures from the industry. Sign up here.

Read more: How will the UK develop quantum computer regulation?

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What countries and blocs are leading in developing quantum computing?

China is a major player in quantum research, spending an estimated $15.3 billion, rivaling the United States.

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Content: Chandeliers, ‘qubits’ and Schrödinger’s cat: Inside the bizarre world of quantum computing

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Chandeliers, ‘qubits’ and Schrödinger’s cat: Inside the bizarre world of quantum computing

In the quantum realm, the laws of physics are different. Now its mind-bending tech could soon transform our lives. How does it work?

It was 2009, and a group of scientists had crowded around a tiny monitor in a Sydney physics laboratory. The team, led by electrical engineer Andrea Morello, held their collective breath and peered at a single flat line on the screen. Then, in the blink of an eye, the line changed: it was a series of blips, like a heartbeat. They’d hit paydirt. “When you see that symbol, you’re in the game,” recalls physicist Charles Tahan.

Welcome to the quantum world, a subatomic realm – yes, smaller than an atom – where the laws of physics are, well, different. The experiment made Morello and his team the first in the world to show that a quantum computer could be made using not diamonds, not the superconductor niobium, but everyday silicon. “To show you could do that, 100 different things had to go right,” says Tahan.

Quantum computing is one of the key technologies defining this century. Its proponents say it will do for computers what the car did to the horse and buggy. It will upend encryption and molecular biology. In theory, it could even possibly find cures for cancer. Australia is among the world leaders in a quantum computing gold rush, with Prime Minister Anthony Albanese saying his government is “serious about building a strong quantum ecosystem” and investing nearly a billion dollars.

Yet despite eye-watering outlays worldwide, quantum computing is still in its infancy, part of a mind-bending world that physicists are only beginning to fully grasp. What is it? And how will it make a difference to our lives?

How does a quantum computer work (and why did Alice in Wonderland have the jump on it?)

It’s often remarked that it looks like a beautiful chandelier, or a wedding cake. And IBM’s quantum computer, one of the world’s largest, is certainly an intriguing object, an intricate dome of golden wires and graceful tubes suspended from a ceiling.

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The part we can see, though, is really just the control and support system for a microchip (currently a version called Condor) buried deep inside. The glittering exoskeleton is there to keep its tiny heart as cold as possible – a hundred times colder than the coldest depths of space – and to feed information in and out, the process that makes it a “computer” and not just a science experiment.

The chip itself is smaller than a postage stamp, with several layers of circuitry and metal sandwiched in a tiny square, cooled to improve conductivity and to eliminate “noise”, the bugbear of many such devices. But even what we see here is not where the action happens. For that, we have to go deeper still, down into the chip and well beyond what’s visible through even the most powerful microscope, beyond the layers of individual atoms, into the atoms themselves.

‘The truth is the universe doesn’t run by the rules that we see every day – gravity, you bounce a ball and it falls. It runs on these other rules: quantum mechanics.’

In the subatomic realm of electrons, protons and photons, things happen very differently. Indeed, these tiny particles have no use for Newton’s laws of physics, nor even many of Einstein’s. “The truth,” says Tahan, “is the universe doesn’t run by the rules that we see every day – gravity, you bounce a ball and it falls. It runs on these other rules: quantum mechanics.”

Why these particles behave as they do in the quantum realm is a difficult concept to get your head around. Even Einstein resisted aspects of it, famously arguing that “God does not play dice with the Universe”. It was a misstep. “Because he didn’t believe in the completeness of quantum mechanics,” says Morello, “he lost a lot of productive years because he didn’t understand how it is possible that this thing is true.”

Many leading physicists investigated the concept from the early 1900s, including some familiar from popular culture today, notably Einstein and Neils Bohr (portrayed in Oppenheimer), Werner Heisenberg (whose name Walter White stole for his drug-chemist alter ego in Breaking Bad) and Viennese physicist Erwin Schrödinger, of the famous cat experiment (explained below).

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Lewis Carroll, meanwhile, may have had the jump on quantum physics with his ideas in the Alice books, as James Renner observed in The Wall Street Journal in 2015. “We speak of going down the wormhole into a mysterious world that defies Newtonian physics, where once Alice went down the rabbit hole into a mysterious world that had much the same effect. Now we speak of quantum particles being in two places at once or even Schrödinger’s cat being alive and dead at the same time, long after the Cheshire Cat’s grin was magically displaced from its body.”

The quantum realm has only truly begun to reveal itself to us relatively recently. In 1964, the Irish-born physicist John Bell published one of the most important theorems, which, according to Professor Andrew Whitaker in Physics World, “opened up the possibility of experimental philosophy, the study of what are normally thought of as philosophical issues in experiments. Not only do these experiments probe the deepest and most profound aspects of quantum theory, they also provide information on the fundamental nature of the universe.”

At the time, Bell’s theorem could not be tested in a lab. That would come in the late 1960s and early 1970s when experimentalists such as John Clauser began to show that the weirdness Bell had described on paper actually occurred in the real world. Which, at the time, was considered quite rude. One eminent physicist “was highly offended by my impertinent effort and told me that it was tantamount to professing a disbelief in quantum physics,” Clauser later recalled.

He and other apostates continued their work because he found some of the predictions “sufficiently bizarre that I could not accept them without seeing experimental proof”. Working with leftover lab equipment – “physics department scrap” – he went on to provide experimental evidence that refuted even Einstein’s theories. “I was very sad to see that my own experiment had proven Einstein wrong,” he said. Clauser would go on to win the 2022 Nobel Prize for Physics alongside Alain Aspect and Anton Zeilinger for their groundbreaking experiments with so-called “entangled” particles.

Quantum physicists still despair at the difficulties of explaining their weird world to outsiders. “Many writers fall back on boilerplate that makes physicists howl in agony,” wrote computer scientist Scott Aaronson in The New York Times in 2019. Unfortunately, says Gerard Milburn, a quantum physicist from the University of Queensland, “The quantum world lies beyond the reach of natural language.”

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But we’ll give it a go. Chiefly, particles in the quantum realm aren’t tied down to being in one place or state in the way bigger things are in the outside world, such as cats, which tend to be in one place at once. They obey different rules entirely. The first way to understand this oddness harks back to high-school science and how light can behave as both a particle and a wave. Photons – bursts of light – can act like ball bearings, with position and momentum. Yet light also behaves like a wave washing over a beach in a way that a ball bearing can’t. That’s a quantum physics party trick.

What is Schrödinger’s cat?

The most famous primer for quantum mechanics is the paradox of Schrödinger’s cat, a mind experiment devised by Schrödinger in 1935. A hypothetical cat goes into a box with a vial of poison gas, which has a 50-50 chance of killing it. You close the box and can’t see inside. So, without opening the box, you can’t know whether the poison has killed the cat or not. Therefore, posited Schrödinger, puss is neither dead nor alive but both – until you open the box.

In quantum mechanics, this state is called “superposition”. It’s impossible to describe properly without a background in higher-level mathematics, which we lack, but it generally means not knowing whether, say, an electron is over here, or over there, or – cat-like – in both places at the same time. Another way of looking at it is to visualise a coin spinning on its side. Until it stops and lands on one side or another, it’s not heads or tails but both.

At least, kind of.

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“Every explanation we give in lay terms is in some way wrong,” says Stephen Bartlett, a theoretical quantum physicist and director of the University of Sydney Nano Institute. “People often say a quantum superposition is in the value zero and the value one at the same time. That’s sort of right, and sort of not right.” Says Morello: “This is where language is failing us, right? If you’re trying to say that in plain English, it sounds really weird. But if you actually think about, you know, the mathematics of it, and the actual physical embodiment of that, it actually makes perfect sense.” Suffice to say, a real cat cannot find itself in “superposition”: this is a state that can exist only in the subatomic world.

How is this useful (and what’s a qubit)?

In a conventional computer, information is encoded as voltages that pass around the system thanks to millions of tiny transistors – essentially, gates or switches that turn on and off. A quantum computer is similar except that instead of using transistors as switches it uses subatomic particles, such as electrons or photons, that can have many more states than simply on or off, according to their position, momentum, spin direction and polarisation. Once harnessed – and there are many ways of doing that – these particles-as-switches are called “qubits”, a play on the word “bit”, the smallest unit of data that a computer can process and store.

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Information can be encoded on qubits in various ways: for his computers, Morello uses silicon and strong magnetic fields like those found in MRI machines. “The stuff that I build in my lab is actually a small silicon chip the size of a fingernail,” he says, “but the whole infrastructure around it is quite fancy. It’s a very powerful refrigerator that cools down the chip to [just] above absolute zero.

Critically, qubits can relate to other qubits in a state called “entanglement”. This enables quantum computers to perform multiple calculations simultaneously – which is their superpower. Schrödinger described entanglement as “the characteristic trait of quantum mechanics, the one that enforces its entire departure from classical lines of thought”. Sceptical Einstein called entanglement “spooky action at a distance”. Gerard Milburn says entanglement is great for building a computer “because if you want to have all these switches, having them strongly correlated is exactly what you want. And if you can control those correlations, you can do computation.”

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It’s these characteristics that have scientists and engineers excited. Not because quantum computers will necessarily take over from the conventional miracles we so rely on today but because they can do some particular things that transistor-based machines either struggle with or fail at completely. Today’s supercomputer might try to simulate molecular behaviour with “brute force”, says IBM’s quantum department. “But as it moves past the simplest, most straightforward molecules available, the supercomputer stalls. Quantum algorithms take a new approach to these sorts of complex problems, creating multidimensional computational spaces.”

‘Calculations that are completely impossible … would rapidly become possible on a quantum computer.’

This might include modelling how a drug might affect a virus, how new materials in aeroplanes might react to stress, or the exact process necessary to create a perfect chemical reaction.

“Calculations that are completely impossible – not just on present-day conventional computers but any conceivable future conventional computer – would rapidly become possible on a quantum computer,” says Andrew Doherty, professor of physics at Sydney University. “These are things where the application of that computer would be transformative to people’s lives without every home, you know, having a laptop quantum computer.”

Whether quantum computing will also revolutionise artificial intelligence is less certain. AI works by drawing from a huge amount of data, which is not something that naturally fits on a quantum computer, says Morello. “The problem with quantum computers in general and, in particular, with applications to AI is that loading data into them and reading data out of them is slow and cumbersome and prone to errors. It’s a bottleneck.”

Why is it so hard to build quantum machines?

Creating the qubits is hard, whatever material you start with. Interfacing with them via tiny wires like the golden lattice in IBM’s machines is hard. Getting accurate information from them is hard: “noise”, in the form of vibration or spurious electromagnetic signals, makes them behave badly and give poor results – “decoherence”, in physics speak.

Much of Andrew Doherty’s team’s work these days is in figuring out how to reduce this noise to acceptable levels and compensating for the errors that noise produces. “Compared to our conventional computers, quantum technology [computers] are very noisy devices,” he says. “They go wrong one time in 1000 as opposed to one time in an astronomically huge number of uses of [normal computers].”

Teams around the world are working on multiple approaches both to building the machines and compensating for their eccentricities, from labs in Australia to the tech giants Google, Microsoft and IBM – its Quantum Lab relies on superconducting qubits made from aluminium and niobiumand the Chinese government.

Some versions, such as IBM’s and Morello’s, chill the atoms to keep them as stable as possible. In contrast, the Australian company Quantum Brilliance is working with synthetic diamonds because they work at room temperature. “Unlike other materials,” says co-founder Marcus Doherty (no relation to Andrew), “diamond’s incredible hardness means that even at room temperature, there isn’t enough thermal energy in the environment to create vibrations that destroy the quantum properties of qubits.”

‘People are working really hard to try to find different mathematical problems that they think maybe quantum computers can’t crack.’

Another key moment in the quantum timeline came in 1994 when US mathematician Peter Shor showed that a quantum computer could crack encryption standards safeguarding everything from national intelligence systems to bank accounts. “He devised an algorithm, in theory, that he would need to run on a quantum computer,” says Bartlett. “And if you could build a quantum computer of sufficient size, then yeah, all information security falls apart.” Cybersecurity experts call that scenario Q-Day. “At the moment, people are working really hard to try to find different mathematical problems that they think maybe quantum computers can’t crack,” says Bartlett.

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In 2001, IBM made a seven-qubit device controlled through radio frequency pulses to demonstrate Shor’s Theorem. IBM’s prototype wasn’t given a huge task, managing to calculate that three times five was … wait for it ... 15. Yet this was considered a great success, even if it had shades of the famous supercomputer Deep Thought from Douglas Adams’ Hitchhiker’s Guide to the Galaxy, which ponders the question of “life, the universe and everything” for thousands of years before giving the answer: 42.(Adams also dreamed up the Infinite Improbability Drive for a spaceship called the Heart of Gold, which used quantum theory to allow it to cross through every point in the universe simultaneously, allowing interstellar travel without all that “tedious mucking about in hyperspace”.)

Then, in 2019, Google claimed its 54-qubit Sycamore processor had performed a calculation in 200 seconds that would have taken the world’s most powerful supercomputer 10,000 years – a breakthrough some breathlessly likened to the Wright brothers’ first flight in 1903. Others were more sceptical, saying it would be many more years before quantum computers would have enough qubits – and be stable enough – to do anything actually useful. IBM said it could simulate Google’s experiment in two-and-a-half days on a “normal” computer, albeit if it had access to the Oak Ridge Summit supercomputer, a beast occupying an area the size of two basketball courts. IBM’s shimmering Eagle, meanwhile, had just 127 qubits; its successors, Osprey and now Condor, have pushed the bar to over 1000 and it plans for 1386 qubits in its Kookaburra in 2025.

Yet most of these devices are still basically proofs of concept, says Morello, the first step to manufacturing and miniaturising, as we saw with today’s transistor-based computers, which started out as rooms full of valves and cables. In the post-World War II era, says Andrew Doherty, “computers took up office floors of buildings in Manhattan and people put paper cards into them to program them. Out came numbers that even my childhood pocket calculator could have calculated right.” Many hundreds of billions of dollars have gone into developing computer technology, in packaging it for convenience and getting the components to work reliably, he says. “That whole engineering thing has got to grow up around these quantum technologies.”

Already, Marcus Doherty’s Quantum Brilliance has installed a quantum computer at the Pawsey Supercomputing Centre in Perth and is about to export computers, at this stage for customers to experiment with quantum computing and work out how to make it useful. In the future, finding commercial applications for a quantum computer will require tailoring it, at least initially, says UNSW’s Maja Cassidy, a former quantum researcher for Microsoft. “People have to go in and understand a company’s problem, how they’re using classical computing and … work out what section might be enhanced by the quantum computer.”

Who is leading the quantum race?

China is the only other nation giving the United States a run for its money. Its leader, Xi Jinping, put accelerating quantum technology in his 2021 five-year plan. McKinsey & Company estimates China has spent at least $15.3 billion in public funds on quantum research. That partly came to fruition in April with the Chinese Academy of Science’s unveiling of a 504-qubit chip, still half the size of IBM’s biggest.

For its part, Australia got a head start with quantum research in the 1990s. Today, two major spinoffs from UNSW research are pursuing silicon-based quantum computing: Silicon Quantum Computing (SQC), led by Professor Michelle Simmons, and Diraq, led by Professor Andrew Dzurak. SQC’s approach involves embedding phosphorus atoms within a wafer of silicon. Dzurak’s approach involves trapping electrons on silicon transistors. Both have the advantage of silicon chips already being ubiquitous. “Today, in our phones and our laptops, the silicon chips that are in those have upwards of a billion transistors on them,” says Dzurak. “The benefit of the technology that we’ve developed is that we are also able to get millions, and ultimately billions, of quantum bits onto a single silicon chip.”

‘Computers as we know them today are an absolutely mind-blowing achievement. So any technology that has the ambition of being an alternative or being better than that has a phenomenally high bar to clear.’

Other leading players in Australia include Q-CTRL, which is working on controlling and enhancing quantum hardware; quantum security company QuintessenceLabs; and Doherty’s Quantum Brilliance, which used its synthetic diamonds in the world-first integration of a two-qubit quantum device into a supercomputer at room temperature in 2022.

Meanwhile, out of the University of Queensland came early gains in “photonic” quantum computing, which harnesses particles of light – photons – as qubits. In April, the federal and Queensland governments jointly set aside $940 million in share purchases, grants and loans for PsiQuantum, a Silicon Valley company whose founders include Australian professors Jeremy O’Brien and Terry Rudolph. Unlike ions or electrons, photons are not charged, Bartlett says, so are not sent haywire by electromagnetic forces – but they are hard to manipulate and measure.

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Another approach involves “trapped ion” quantum computing, pursued by US company IonQ: physicists take an atom, flick off an electron so it is positively charged, then suspend the resulting ion within an electromagnetic field and manipulate the ion with lasers. But Bartlett says this approach will be hard to scale, given the technology to suspend millions of ion qubits doesn’t yet exist.

In April, the federal government also announced $18 million for the University of Sydney to establish Quantum Australia, a research consortium between several universities headed by Bartlett. “It used to be a small research community,” he says. “You absolutely needed to speak the common language of everyone else, which were the rules of physics. Now we are really seeing quite a bit of specialisation.”

Even if quantum computers develop practical uses, they will likely live in vast, super-cooled server farms where land and power are cheap. We’ll communicate with them through our everyday devices, much as we download and upload data from cloud servers, Netflix, TikTok, DropBox, whatever, today. The real challenge for quantum computing, says Morello, is that the alternative is “really, really good”. “Computers as we know them today are an absolutely mind-blowing achievement. So any technology that has the ambition of being an alternative or being better than that has a phenomenally high bar to clear.”

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How much have countries and blocs invested in quantum computing?

What countries and blocs are leading in developing quantum computing?

The US is investing heavily in quantum computing, led by companies like IBM, Google, and Microsoft.

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  1. Analysis
September 23, 2022

Is the finance sector quantum ready?

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It is an important year for quantum computing, according to GlobalData’s Technology, Media and Telecoms Predictions 2022. In addition to the high levels of hype generated around this disruptive technology, significant technical advances have seen companies starting to invest in exploring its potential benefits.

The global quantum computing market size is set to reach $1.77bn by 2026, up from $472m in 2021, at a compound annual growth rate of 30.2%, according to Markets and Markets. Pioneering adoption of quantum computing by financial services companies is expected to drive this growth.

Is the financial services industry prepared for quantum?

What does a quantum advantage over classical computing mean for financial services? Increasing the speed and volume of calculations and transactions by multiples represents the biggest change for a post-quantum financial services sector – and the key to identifying the potential benefits of specific use cases is exploration. Early iterations of quantum computing-as-a-service are under way with Big Tech companies Microsoft, Amazon, IBM and Google offering clients a cloud service for experimenting with quantum simulators (essentially classical computers mimicking quantum computers in the cloud to see what they can do).

This collaborative approach between businesses and tech companies addresses two problems in tandem: first, it allows businesses to familiarise themselves with the emerging technology despite quantum supremacy being some years away; second, it tackles the biggest business challenge, which is identifying the most effective use cases for financial services.

US tech giant IBM’s quantum accelerator programme was set up with exactly that in mind: to allow businesses themselves to find effective quantum computing use cases. Many of IBM’s financial services clients in the accelerator programme have initial concerns about the effect quantum computing will have on cryptography, according to Prakash Pattni, managing director for financial services – digital transformation at IBM.

“It took a few years for banks to work out where blockchain fits in with cryptography, for example, and we are now at a stage where blockchain is really taking off,” he says.

Pattni likens quantum computing as being at that same early stage of experimentation as blockchain was. Financial services companies are perhaps even more acutely aware of the potential impact of quantum computing on data security because the nature of banking regulation means data has to be stored and kept safe for many years, adds Pattni.

While cybersecurity remains a clear concern for clients, specific use cases are still being worked out. Again, experimentation is key, according to Pattni, who says: “I think we’ are still at that very early stage in terms of experimentation where quantum is concerned.” According to Gartner, 40% of large companies are planning to create initiatives around quantum computing by 2025, but even with accelerator programmes and research and development budgets, very specific use cases are still proving hard to identify.

Financial services, particularly those which work across multiple markets, stand to benefit greatly from efficiencies enabled by quantum computing given that it enables the modelling of multiple permutations of different scenarios or values to solve the most efficient outcomes in a fraction of the time it would take classical computing.

Pattni believes this could be particularly useful in the cross-border fraud detection space, saying: “Real-time payments mean the window to look at fraud needs to be in real time too.” As AI is increasingly integrated into banking systems, the interface between AI and quantum computing is also a testing ground. Pattni says risk calculation is an area that investment banks are looking at.

“It requires incredibly high levels of compute power to run multiple risk scenarios that regulators don’t like, so that is another area where quantum computing could be applied, but it is still really early days of experimenting with applications,” he adds.

Finance’s first movers in quantum computing adoption

EY’s 2022 Quantum Readiness survey, produced in collaboration with the UK’s National Quantum Computing Centre, found that 81% of senior UK executives expect quantum computing to play a significant role in their industry by 2030. Despite this, most companies are taking a ‘watch and see’ approach. However, there are those in the finance sector taking a pioneering approach by testing the technology and ramping up investment in a calculated bet that quantum computing will, in fact, live up to its hype.

US investment bank Goldman Sachs is actively researching how quantum computing can be applied to the pricing of complex derivatives. Computing a price within a complicated contract or statistical model can be an expensive process. Derivatives are so common in finance that even a small improvement in pricing them, or in calculating related quantities, could be very valuable, according to William Zeng, head of quantum research for Goldman Sachs, who made the claim in September 2022 for Microsoft Azure’s quantum blog.

In March 2022, Spain’s CaixaBank’s life insurance and pensions company, VidaCaixa, announced that it is using Canadian quantum computing company D-Wave’s cloud service to build a quantum computing application for its investment portfolio selection and allocation activities, as well as its portfolio hedging.

According to CaixaBank, this is the first time a financial services company has applied quantum computing in investment hedging in the insurance sector. What normally took the bank several hours of computing time was reduced to just minutes, representing up to a 90% decrease. This time reduction facilitates increased modelling complexity, which is better adapted to real-time markets, optimises invested capital while maintaining constant risk levels and improves the hedging decision-making process. The Spanish banking group is evaluating whether to use the application in other areas of its operations over the coming months.

In March 2022, HSBC announced it will join the IBM Quantum Accelerator programme to progress potential quantum use cases in pricing and portfolio optimisation to advance its net-zero goals and to mitigate risks, including identifying and addressing fraudulent activity. The collaboration will also include knowledge transfer through internal training programmes, as well as actively recruiting quantum computing research scientists to build a dedicated capability within its innovation team.

Elsewhere, Standard Chartered has embarked upon research into quantum computers as part of an academic partnership with the Universities Space Research Association. The partnership is already actively developing what is known as the Quantum Computing System for Financial Services, and the bank will use it to address the security challenges posed by a super-powerful quantum computer.

Post-quantum security a pressing matter

Both IBM and Google have road maps to create quantum computers capable of defeating current encryption by 2030, according to GlobalData. Despite the cybersecurity industry developing quantum-resistant encryption before that time, future quantum computers could decrypt data harvested today. As a result, GlobalData expects companies to implement quantum security solutions in 2022, particularly as cybersecurity has become front of mind for business leaders.

Over the past 12 months, interest in quantum security has grown considerably in the financial services sector, according to Duncan Jones, head of cybersecurity at quantum computing company Quantinuum. “This is partly driven by the stream of announcements from the US government highlighting the urgent need to combat the quantum threat alongside the business opportunities,” he says.

In addition, as more quantum-enabled business use cases emerge, so too do the cybersecurity concerns. Jones and his team at Quantinuum are working on ways to remedy this. Quantinuum’s partnership with cybersecurity software company PureVPN uses Quantinuum’s cyber platform, Quantum Origin, to create and deploy encryption keys generated using a verifiable quantum process, which are more secure than keys from unverified, classical computing processes.

Every technology advance creates a commensurate cybersecurity challenge and quantum-proofing financial services companies will continue to be a concern alongside the business growth opportunities, according to Jones. “Financial services companies are realising there is a new quantum baseline for security and are factoring this into their cyber planning,” he adds.

In July 2022, it became public knowledge that US investment bank JPMorgan Chase had hired assistant professor Dr Charles Lim – a world-renowned expert in next-generation, quantum-resistant communication networks at the National University of Singapore – to lead the bank’s quantum communications and cryptography. The move not only demonstrates how quantum computing has become a business concern but also highlighted a global race for talent in the field, serving as a warning to other financial services companies that they may want to ramp up their search for quantum computing talent. Historically, financial services has attracted the brightest and the best with attractive compensation, but the sector is now competing with commensurate employee offerings by Big Tech. A battleground for quantum computing talent is set to continue.

Credit rating financial services company Moody's Analytics announced in September 2022 that it is establishing the Moody's Analytics Quantum Computing Team, which is perhaps a sign that quantum computing has become part of the financial services establishment. Early adoption of this technology may seem like a choice in 2022, but it may prove vital in future-proofing financial services companies against the changes that it will bring to the sector. As with any emerging technology there are first movers and those that follow the trend – it is still too soon to tell which approach will reap the most benefits.

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Content: Quantum Computing Market was valued at nearly USD 234.06 billion by 2032

Prudour Private Limited

Updated · Mar 06, 2023

Quantum Computing Market Overview

Published Via 11Press: Quantum computing is a rapidly developing market that is revolutionizing how we approach computing and data processing. By employing principles of quantum mechanics to perform computations, quantum computers are capable of solving problems that classical computers may find impossible or impracticable to resolve.

The global quantum computing market size is forecast to reach USD 234.06 billion by 2032 from USD 10.13 billion in 2022, rising at a compound annual growth rate (CAGR) of 36.89% during the forecast period.

At present, the quantum computing market is dominated by a few major players such as IBM, Google, Microsoft, and Honeywell. These firms are investing heavily in quantum computing research and development as well as creating quantum computing hardware and software systems.

The quantum computing market is expected to have a profound effect on industries such as healthcare, finance, logistics, and energy. Some key applications of quantum computing include drug discovery, supply chain optimization, financial modeling, and climate modeling.

Though the quantum computing market is promising, it still faces several obstacles such as high costs of hardware, a shortage of skilled experts in this area, and technical difficulties when building large-scale quantum computers. With ongoing research and development efforts, however, these problems should be overcome within the coming years, leading to even greater growth and innovation in this space.

Key Takeaways

  • The global quantum computing market size was valued at USD 234.06 billion in 2022 and is expected to grow at a CAGR of around 36.89% from 2022 to 2032.
  • Quantum computing is capable of solving problems that would be intractable or impossible for classical computers to solve.
  • The quantum computing market is dominated by a few major players, including IBM, Google, Microsoft and Honeywell.
  • The quantum computing market is expected to have a profound effect on numerous industries, such as healthcare, finance, logistics and energy.
  • Quantum computing has many important applications such as drug discovery, supply chain optimization, financial modeling and climate modeling.
  • The quantum computing market remains plagued by several obstacles, such as the high cost of quantum computing hardware, lack of qualified quantum computing experts and technical difficulties in building and running large-scale quantum computing systems.
  • Research and development are expected to overcome these obstacles within the next couple of years, propelling even greater growth and innovation in the quantum computing market.

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Regional Snapshot

  • North America: North America is currently the leading market for quantum computing, with the United States playing a major role. Major companies such as IBM, Google, and Microsoft are driving this growth through their presence and investment in research and development activities related to quantum computing. This region boasts numerous key players such as IBM, Google, and Microsoft which are driving demand within this region.
  • Europe: Europe is an increasingly important market for quantum computing, with countries such as the UK, Germany, and France investing heavily in research and development. Through partnerships between quantum computing companies and other technology firms as well as the growing adoption of quantum computing across various industries, this region’s market is experiencing rapid expansion.
  • Asia Pacific: The quantum computing market in Asia Pacific is expected to experience significant growth over the coming years due to increased investments in research and development by countries like China, Japan, and South Korea. Furthermore, there have been an increasing number of collaborations between companies using quantum computing with academic institutions as well as its increasing adoption across industries like healthcare and finance – all contributing factors for market expansion within this region.
  • The Rest of the World: Countries such as Brazil, South Africa, and the UAE are expected to experience significant growth in the quantum computing market over the coming years due to increased investments in research and development efforts as well as the growing adoption of quantum computing across various industries. These factors are fueling this region’s meteoric rise in this region.

Drivers

  • Quantum Computing Gaining Adoption in Various Industries: Quantum computing is seeing an uptick in popularity across a range of industries, such as healthcare, finance, logistics, and energy – as companies seek to use their power to solve complex problems and gain an edge in competition.
  • Investments in Quantum Computing Research and Development: Governments, academic institutions, and private companies have made substantial investments in quantum computing research and development, spurring innovation and progress within the field.
  • Growing Number of Partnerships and Collaborations: There has been an uptick in partnerships and collaborations between quantum computing companies and other technology firms, as well as academic institutions and research organizations. This trend is propelling the development of new quantum computing hardware and software systems, as well as its adoption across various industries.
  • Increasing Access to Cloud-Based Quantum Computing Services: The growing availability of cloud-based quantum computing services is making it simpler for companies and researchers to utilize this cutting-edge technology, spurring adoption and innovation within the field.

Restraints

  • Limited Access to Qualified Quantum Computing Experts: Unfortunately, there is currently a shortage of highly experienced quantum computing specialists, making it challenging for companies to construct and sustain quantum computing systems.
  • Technical Challenges in Building and Maintaining Large-Scale Quantum Computing Systems: The development of large-scale quantum computing systems is still in its early stages, so there are numerous technical obstacles that must be overcome, such as noise reduction, error correction, and scalability.
  • Limited Quantum Computing Applications: Although the list of potential applications for quantum computing is growing, the number of practical ones that have been developed and implemented remains limited. This can make it challenging for companies to justify investing in quantum computing technology.
  • Regulatory Challenges: Quantum computing technology may face regulatory restrictions, particularly around data privacy and security. This could create additional obstacles to the adoption and investment in the technology.

Opportunities

  • Growing Number of Partnerships and Collaborations: The growing number of partnerships and collaborations among quantum computing companies, other technology firms, academic institutions, and research organizations is creating opportunities for the development of new quantum computing hardware and software systems as well as its adoption across various industries.
  • Advancements in Quantum Computing Hardware and Software: With the rapid progress being made in the development of quantum computing hardware and software, new opportunities will present themselves for applying this technology across various industries and fields.
  • The growing availability of cloud-based quantum computing services: Cloud-based quantum computing services are making it simpler for companies and researchers to access and utilize quantum computing technology, spurring adoption and innovation within the field.
  • Growth of Quantum Computing as a Service: As more companies and researchers embrace the potential of quantum computing, cloud-based quantum computing services are creating exciting new business opportunities for those offering these solutions.
  • Potential for Breakthroughs in Areas such as Drug Discovery, Finance, and Energy: Quantum computing holds the potential to unravel complex issues in fields like drug discovery, finance, and energy – leading to major breakthroughs and advances. This presents companies with unique opportunities for those who can develop and implement quantum computing solutions in these sectors.

Challenges

  • Technical Challenges in Constructing and Running Large Quantum Computing Systems: As quantum computing systems continue to emerge, numerous technical obstacles must be overcome such as noise reduction, error correction, and scalability. These issues make it challenging for companies to construct and run these massive quantum computers efficiently.
  • Limited Access to Qualified Quantum Computing Experts: There is currently a shortage of highly experienced quantum computing professionals, making it difficult for companies to construct and maintain quantum computing systems. This shortage could potentially restrict the growth of this industry in the coming years.
  • Quantum computing Applications: While quantum computing has many potential uses, the number of practical applications that have been created and implemented remains limited. This could make investing in quantum computing technology and research on practical applications an attractive prospect.

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Recent Developments

  • Google Claims Quantum Supremacy: In 2019, Google claimed to have achieved quantum supremacy by performing a calculation on its quantum computer that even the most powerful supercomputers would take thousands of years to complete. This was seen as an important milestone in the advancement of quantum computing technology.
  • IBM Launches Quantum Computing Program for Students: In 2020, IBM unveiled a quantum computing program specifically tailored towards students that provides them with access to IBM’s resources and tools, as well as a platform for learning and collaboration.
  • Honeywell Achieves Quantum Computer Record Performance: On March 20, 2021, Honeywell revealed its creation of a quantum computer with an astonishing quantum volume of 512. This feat marked an amazing advancement in quantum computing technology and demonstrated how rapidly progress has been made since then.
  • Amazon Web Services Announces Quantum Computing Service: On June 2021, Amazon Web Services (AWS) announced the launch of its own quantum computing service called Amazon Bracket. This offering gives customers access to various vendors’ hardware as well as tools and resources for developing and testing quantum algorithms.

Key Market Segments

Type

  • Hardware
  • Software
  • Services

Application

  • Defense
  • Healthcare & pharmaceuticals
  • Chemicals
  • Banking & Finance
  • Energy & power

Key Market Players

  • D-Wave Systems
  • Google
  • IBM
  • Intel
  • Microsoft
  • 1QB Information Technologies
  • Anyon Systems
  • Cambridge Quantum Computing
  • ID Quantique
  • IonQ
  • QbitLogic
  • QC Ware
  • Quantum Circuits
  • Qubitekk
  • QxBranch
  • Rigetti Computing

Nature Insights

  • Progress is being made in the development of quantum computing hardware: Despite the challenges facing large-scale quantum computing systems, progress is being made on quantum computing hardware. This includes creating quantum processors with increasingly more qubits and creating new materials suitable for use in quantum computers.
  • Quantum computing software is still in its early stages: While progress is being made with quantum computing hardware, software development for quantum computation remains at a standstill. This presents an immense challenge to the industry as developing efficient quantum algorithms is essential to realizing its full potential.
  • Collaboration is essential to the advancement of quantum computing: Collaboration between companies, academic institutions, and research organizations is essential for progress in this industry. This includes joint efforts to develop new hardware and software systems as well as collaborations that promote quantum computing across various industries.

Report Scope

Report Attribute Details
The market size value in 2022 USD 10.13 Bn
Revenue forecast by 2032 USD 234.6 Bn
Growth Rate CAGR Of 36.89%
Regions Covered North America, Europe, Asia Pacific, Latin America, and Middle East & Africa, and the Rest of the World
Historical Years 2017-2022
Base Year 2022
Estimated Year 2023
Short-Term Projection Year 2028
Long-Term Projected Year 2032

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FAQ.

What is quantum computing?

Quantum computing is a type of processing data using quantum mechanics. It relies on principles such as superposition, entanglement, and interference which enable quantum computers to perform calculations that would be impossible with classical computers.

What are some potential applications of quantum computing?

Quantum computing holds great promise for revolutionizing industries such as drug discovery, finance, energy, and logistics. Potential uses include creating new drugs and materials, optimizing supply chains and logistics networks, and even improving weather forecasting models with greater precision.

What are some of the challenges facing the quantum computing market?

The quantum computing market faces numerous obstacles, such as technical difficulties in building and running large-scale quantum computers, high costs associated with quantum computing hardware, a scarcity of highly qualified quantum experts, and an absence of practical applications developed and deployed.

Who are some of the major players in the quantum computing market?

Major companies operating within this space include IBM, Google, Microsoft, Honeywell, Intel, and Rigetti Computing. These firms are actively developing and commercializing quantum computing hardware and software systems.

What is the outlook for the quantum computing market?

Overall, analysts anticipate a bright future for quantum computing, with continued investment and innovation anticipated in the coming years. Though still in its early stages of development, its potential advantages are immense - leading to rapid industry growth over the coming years.

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Content: Cloud-based Quantum Computing Market projected to reach USD 6,289.8 Million by 2030, growing at a CAGR of 35.5% during the forecast period of 2023-2030 - says MarketDigits in its latest study

The Global Cloud-based Quantum Computing Market was valued USD 750 Million in 2023 and projected to reach USD 6,289.8 Million by 2030, growing at a CAGR of 35.5% during the forecast period of 2023-2030

Richmond, Jan. 02, 2024 (GLOBE NEWSWIRE) -- According to a research report "Cloud-based Quantum Computing Market, by Offering (Service, Software), Technology (Trapped Ions, Quantum Annealing, Superconducting Qubits, Other Technologies, Others), Application (Encryption, Optimization, Sampling, Simulation), Industry Vertical (BFSI, Healthcare and Pharmaceuticals, Aerospace and Defense, Research and Academia, Manufacturing, Transportation and Logistics, Others), and Region - Global Forecast to 2030.

Global Cloud-based Quantum Computing Market Report Scope:

Report Details
Market size value in 2023 USD 750 Million
Market size value in 2030 USD 6,289.8 Million
CAGR (2023-2030) 35.5%
Forecast Period 2023–2030
Historic Data 2019
Forecast Units Value (USD Million/USD Billion)
Segments Covered Offering, Technology, Application, End User and Region
Geographies Covered North America, Europe, Asia Pacific, and RoW

  • Accenture

  • AWS (Amazon Web Services)
Sample of Companies Covered
  • Baidu

  • Cambridge Quantum Computing

  • D-Wave Quantum Inc.

Download the Sample - https://www.marketdigits.com/request/sample/1108

TOC Covers in Depth & Breath on Cloud-based Quantum Computing Market
170 - Market Data Tables
65 - List of Figures
225 – Pages

The report includes Vendor Assessment (Company Profiles, Market Positioning, Strategies, Recent Developments, Capabilities & Product Offerings / Mapping), Technology Assessment (Developments & Economic Impact), Partner & Customer Ecosystem (Product Services, Proposition & Key Features) Competitive Index & Regional FootPrint by MarketDigits.

Market Overview

Cloud-based quantum computing enables remote access to quantum processors and algorithms, revolutionizing computation for diverse applications via online platforms. The cloud-based quantum computing market is experiencing unprecedented growth as organizations seek to harness the immense computational power of quantum processors through convenient and scalable cloud services. This market evolution marks a paradigm shift in computing capabilities, with leading tech companies investing heavily in quantum research and development. Quantum computing leverages the principles of superposition and entanglement to perform complex calculations at speeds unattainable by classical computers. Cloud-based offerings democratize access to quantum resources, allowing businesses to explore and experiment without the need for extensive on-premises infrastructure. As a result, a diverse range of industries, including finance, healthcare, and logistics, are exploring quantum solutions for optimization, simulation, and machine learning applications. The market's trajectory is driven by a convergence of technological advancements, increased investments, and a growing ecosystem of quantum developers and users, positioning cloud-based quantum computing as a transformative force in the future of information processing.

Major Vendors In The Global Cloud-Based Quantum Computing Market:

  • Accenture
  • Amazon Web Services (AWS)
  • Baidu
  • Cambridge Quantum Computing
  • D-Wave Quantum Inc.
  • D-Wave Systems
  • Fujitsu
  • Google
  • Honeywell
  • Huawei Technologies Co.
  • IBM
  • 1QBIT
  • Microsoft
  • QC Ware
  • Riverlane
  • Rigetti Computing
  • T-Systems International GmbH
  • Zapata Computing

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Increasing demand for advanced computational capabilities

The escalating demand for advanced computational capabilities stands as a pivotal driver propelling the cloud-based quantum computing market into prominence. As traditional computing architectures face limitations in solving complex problems, organizations across various sectors are turning to quantum computing to address challenges that were once deemed insurmountable. Cloud-based quantum computing offers a scalable and accessible solution, allowing businesses to harness the extraordinary processing power of quantum processors without the need for significant on-premises infrastructure investments. This surge in demand is fueled by the recognition that quantum algorithms have the potential to outperform classical counterparts in areas such as optimization, cryptography, and machine learning. The advent of cloud-based services democratizes access to quantum resources, empowering a diverse range of industries to explore novel solutions and stay at the forefront of technological innovation in the pursuit of solving complex problems more efficiently and effectively.

Market Dynamics

Drivers:

  • Increasing demand for advanced computational capabilities
  • Growing demand for faster data operations, secure data transfer, and communications

Opportunities:

  • Recent advances in cloud-based quantum computing
  • Growing adoption of quantum computing solutions across several verticals

Recent advances in cloud-based quantum computing

Recent advances in cloud-based quantum computing present a significant opportunity for the quantum computing market, opening new frontiers in computation and problem-solving. The integration of cutting-edge technologies into cloud services has enhanced the accessibility and usability of quantum computing resources. Cloud providers are actively investing in infrastructure, algorithms, and developer tools, making quantum computing capabilities more user-friendly and scalable. This progress is fostering a conducive environment for experimentation and innovation, attracting a broader spectrum of users from diverse industries. As cloud-based quantum computing platforms evolve, they offer businesses the chance to explore and harness the potential of quantum algorithms without the need for substantial in-house expertise or infrastructure. This opportunity not only accelerates the adoption of quantum technologies but also democratizes access, empowering organizations to leverage the transformative power of quantum computing to solve complex problems and gain a competitive edge in the rapidly advancing digital landscape.

The market for Cloud-based Quantum Computing is dominated by North America.

North America stands as the dominant force in the Cloud-based Quantum Computing market, with the United States and Canada playing pivotal roles. The region's leadership is attributed to the robust presence of major quantum computing players, significant research and development initiatives, and a burgeoning tech ecosystem. In the United States, companies like IBM, Google, and Rigetti Computing have spearheaded quantum advancements, while Canada boasts prominent players like D-Wave. The strategic collaboration between academia, government, and industry in North America has positioned the region as a global hub for quantum computing innovation, solidifying its preeminence in driving the growth and development of cloud-based quantum computing solutions.

The research and academia Segment is Anticipated to Hold the Largest Market Share During the Forecast Period

Based on Industry Vertical the Cloud-based Quantum Computing Market is segmented into BFSI, Healthcare and Pharmaceuticals, Aerospace and Defense, Research and Academia, Manufacturing, Transportation and Logistics, Others. The research and academia segment is poised to maintain its dominance, holding the largest market size in the Cloud-based Quantum Computing sector throughout the forecast period. This prominence can be attributed to the active involvement of research institutions and academic entities in advancing quantum technologies. These stakeholders play a crucial role in driving innovation, developing quantum algorithms, and educating the workforce. Cloud-based platforms offer an accessible environment for researchers and students to experiment with quantum computing, fostering collaboration and knowledge exchange. As a result, the research and academia segment continues to lead, shaping the trajectory of Cloud-based Quantum Computing's market growth.

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7 Best Quantum Computing Stocks to Buy in 2022

Quantum computing offers the potential to harness big data, make intricate predictions and use artificial intelligence (AI) to revolutionize business operations. Many industries such as automotive, agriculture, finance, healthcare, energy, logistics and space will be affected from the growth in this technology. As a result, Wall Street has been paying significant attention to quantum computing stocks.

Once considered science fiction, quantum computing has made significant progress in recent years to solve complex problems at lightning speed. This advanced technology uses the power of quantum mechanics to represent complex problems. These computers can take seconds to calculate equations that normally take days for machines that use a binary framework.

International Data Corporation forecasts that the global market for quantum computing should grow from about $412 million in 2020 to more than $8.5 billion in 2027. This increase would mean a  compound annual growth rate (CAGR) of an eye-popping 50% between now and 2027. Given such metrics, it’s understandable why investors are thrilled about the future of quantum computing stocks.

While it is currently in its early days, Wall Street has already warmed up to long-term prospects of this technology. Besides several pure-play quantum computing stocks going public in 2021, well-known tech names are pouring significant research dollars to invest in this advanced segment.

With that information, here are the seven best quantum computing stocks to buy in 2022:

  • Analog Devices (NASDAQ:ADI)
  • Defiance Quantum ETF (NYSEARCA:QTUM)
  • International Business Machines (NYSE:IBM)
  • IonQ (NYSE:IONQ)
  • Microsoft (NASDAQ:MSFT)
  • Nvidia (NASDAQ:NVDA)
  • Supernova Partners Acquisition II (NYSE:SNII)

Quantum Computing Stocks: Analog Devices (ADI)

Source: Shutterstock

52-week range: $142.25 – $191.95

Dividend yield: 1.7%

Semiconductor group Analog Devices manufactures integrated circuits that process analog and digital signals. ADI’s chips are used in data converters, high-performance amplifiers and microwave-integrated circuits.

Analog Devices issued Q4 2021 metrics on Nov. 23. Revenue increased 53% year-over-year (YOY) to $2.34 billion. Adjusted earnings soared from $1.44 per share to $1.73 per share. The company generated a free cash flow of $810 million. Cash and equivalents ended the period at $1.98 billion.

Factory automation has fueled demand for sensors and machine connectivity, which increasingly rely on Analog’s chips. In addition, the automotive industry has also become a key growth driver due to the rising use of advanced electronics in electric vehicles (EVs).

In late August, the chipmaker completed the acquisition of Maxim Integrated. The billion transaction should increase ADI’s market share in automotive and 5G chipmaking.

ADI currently trades just under $160, up 7% over the past 12 months. Shares are trading at 21.5 times forward earnings and 8.9 times trailing sales. The 12-month median price forecast for Analog Devices stock stands at $210.

Defiance Quantum ETF (QTUM)

Source: Maxx-Studio/ShutterStock.com

52-Week Range: $42.96 – $57.15

Expense Ratio: 0.40% per year

QTUM is an exchange-traded fund (ETF) that focuses on the next generation of computing. It offers exposure to names leading the way in quantum computing, machine learning and cloud computing. The fund tracks the BlueStar Quantum Computing and Machine Learning Index.

QTUM, which started trading in September 2018, has 71 holdings. The top 10 holdings account for less than 20% of net assets of $161.5 million. Put another way, fund managers are not taking major bets on any company.

Among the leading holdings on the roster are the security and aerospace company Lockheed Martin (NYSE:LMT), French telecommunications operator Orange (NYSE:ORAN) and IBM.

For most retail investors, QTUM could potentially be a safe and diversified place to start investing in quantum computing. As portfolio companies come from a wide range of technology segments, wide swings in the price of one stock will not affect the ETF significantly.

The fund has gained 8.7% over the past year and saw an all-time high in November 2021. However, the recent selloff in tech stocks led to a 10.7% decline year-to-date (YTD). Interested readers could regard this decline as a good entry point into QTUM.

Quantum Computing Stocks: International Business Machines (IBM)

Source: shutterstock.com/LCV

52-week range: $113.17 – $146.12

Dividend Yield: 4.8%

Technology giant International Business Machines (IBM) needs little introduction. The legacy tech name offers integrated solutions and services, including infrastructure, software, information technology (IT) and hardware.

IBM announced Q4 2021 financials on Jan. 24. The company generated revenues of $16.7 billion, up 6.5% YOY. Net income stood at $2.33 billion, or $2.57 per diluted share, up from $1.36 billion, or $1.51 per diluted share, in the prior-year quarter. Cash and equivalents ended the period at $6.65 billion.

After the announcement, CEO Arvind Krishna said, “We increased revenue in the fourth quarter with hybrid cloud adoption driving growth in
software and consulting.”

The company launched its Quantum System One quantum computer in 2019. Around 150 research groups and partner companies currently use IBM’s quantum computing services. These names come from financial services businesses, automakers and energy suppliers.

In June 2021, IBM unveiled Europe’s most powerful quantum computer in Germany. Moreover, the tech giant recently announced a deal with Raytheon Technologies (NYSE:RTX) to provide quantum computing and AI services for the aerospace, defense and intelligence industries.

IBM currently changes hands around $137, up 20% over the past 12 months. Shares are trading at 13.5 times forward earnings and 2.2 times trailing sales. The 12-month median price forecast for IBM stock is $144.50. Interested readers could consider buying IBM shares around these levels.

IonQ (IONQ)

Source: Shutterstock

52-week range: $7.07 – $35.90

IonQ is one of the first publicly traded pure-play quantum computing stocks. It went public via a merger with the special purpose acquisition company (SPAC) dMY Technology Group III in late 2021.

The quantum name released Q3 2021 results on Nov. 15. Its net loss was $14.8 million, or 12 cents loss per diluted share, compared to a net loss of $3.6 million a year ago. Cash and equivalents ended the quarter at $587 million. Wall Street was pleased that at the time, YTD contract bookings came in at $15.1 million.

IonQ is currently developing a network of quantum computers accessible from various cloud services. The technology uses ionized atoms that allow IonQ’s machines to perform complex calculations with fewer errors than any other quantum computer available.

The start-up has the financial backing of prominent investors, including Bill Gates and the Japanese telecommunications company Softbank Group (OTCMKTS:SFTBF). In addition, IonQ has been developing strategic partnerships with Microsoft, Amazon’s (NASDAQ:AMZN) Amazon Web Services and Alphabet’s (NASDAQ:GOOG, NASDAQ:GOOGL) Google Cloud.

While IonQ is taking steps to become a commercialization-stage name, it is still a speculative investment. With its potential for explosive growth, it could be an attractive quantum computing stock for investors looking to take a risk.

IONQ stock hovers around $12. The recent selloff in tech stocks has led to a 26.7% decline YTD. Yet, the 12-month median price forecast for IONQ stock stands at $23.

Quantum Computing Stocks: Microsoft (MSFT)

Source: rafapress / Shutterstock.com

52-week range: $224.26 – $349.67

Dividend Yield: 0.8%

Microsoft is one the largest and most prominent technology firms worldwide. It offers software products and services, including Azure cloud service, the Office 365 productivity suite and the customer relationship management (CRM) platform Dynamics 365.

Meanwhile, the Microsoft Quantum is “the world’s first full-stack, open cloud quantum computing ecosystem” that allows developers to create quantum applications and run them on multiple platforms. The software giant provides quantum computing services via the cloud on Azure.

Management announced robust Q2 FY22 metrics on Jan. 25. Revenue increased 20% YOY to $51.7 billion. Net income surged 21% YOY to $18.8 billion, or $2.48 per diluted share, compared to $15.5 billion, or $2.03 per diluted share, in the prior-year quarter. Cash and equivalents ended the period at $20.6 billion.

On Jan. 18, Microsoft announced plans to acquire Activision Blizzard (NASDAQ:ATVI), a leading player in game and interactive entertainment development. It will be an all-cash transaction valued at $68.7 billion. Wall Street expects this deal to provide tailwinds for Microsoft’s gaming business and building blocks for the metaverse.

MSFT stock currently trades just under $310, up 27% over the past 12 months. Shares support a valuation of 32.6 times forward earnings and 12.3 times trailing sales. And the 12-month median price forecast for Microsoft stock stands at $370.

Nvidia (NVDA)

Source: Antonio Baccardi / Shutterstock.com

52-week range: $115.67 – $346.47

Dividend Yield: 0.06%

Santa Clara, California-based Nvidia has become an important name in advanced semiconductor design and software for next-generation computing development. InvestorPlace readers likely know the chipmaker is a market leader in the gaming and data center markets.

Nvidia announced impressive Q3 FY 2022 numbers on Nov. 17. Revenue soared 50% YOY to a record $7.1 billion, fueled by record sales in the gaming and data center businesses. Net income increased 62% YOY to $2.97 billion, or $1.17 per diluted share. Cash and equivalents ended the period at $1.29 billion.

The chipmaker provides the necessary processing power that drives the development of quantum computing. Additionally, Nvidia recently released cuQuantum, a software development kit designed for building quantum computing workflows. It has partnered with Google, IBM and other quantum computing players that rely on cuQuantum to accelerate their quantum computing work.

Given its growing addressable market in cloud computing, gaming, AI, and more recently the metaverse, NVDA stock deserves your attention. Share are changing hands around $245, up nearly 80% over the past year. However, despite an 18% decline YTD, shares are trading at 46.5 times forward earnings and 25 times trailing sales.

Finally, the 12-month median price forecast for Nvidia stock is $350. As the company gets ready to report earnings soon, investors should expect increased choppiness in price.

Quantum Computing Stocks: Supernova Partners Acquisition II (SNII)

Source: Dmitry Demidovich/ShutterStock.com

52-week range: $9.62 – $12.75

Our final stock is Supernova Partners Acquisition II, a SPAC. It is merging with Rigetti Computing, a start-up focused on quantum computer development. As a result of the merger, Rigetti Computing was valued at about $1.5 billion and received $458 million in gross cash proceeds.

Rigetti designs quantum chips and then integrates those chips with a controlling architecture. It also develops software used to build algorithms for these chips.

Rigetti recently announced business highlights for the nine months ended Oct. 31, 2021. Revenue came in at $6.9 million. Net operating loss declined 3% YOY to $26.2 million.

“We believe the time for quantum computing has arrived,” said founder and CEO Chad Rigetti. “Customer demand is increasing as Rigetti quantum computers begin to address high-impact computational problems.”

The start-up launched the world’s first scalable multi-chip quantum processor in June 2021. This processor boasts a proprietary modular architecture. Now Wall Street expects the company to move toward commercialization.

Rigetti collaborates with government entities and technology to advance its quantum processors. For instance, it boasts strategic partnerships with the National Aeronautics and Space Administration (NASA) and the U.S. Department of Energy. It also works with data analytics firm Palantir Technologies (NYSE:PLTR) and electronics manufacturer Keysight Technologies (NYSE:KEYS).

SNII stock is currently shy of $10, down about 4% YTD. As investors’ interest in quantum computing names grow, shares are likely to become hot.

On the date of publication, Tezcan Gecgil holds both long and short positions in NVDA stock. The opinions expressed in this article are those of the writer, subject to the InvestorPlace.com Publishing Guidelines.

Tezcan Gecgil has worked in investment management for over two decades in the U.S. and U.K. In addition to formal higher education in the field, she has also completed all 3 levels of the Chartered Market Technician (CMT) examination. Her passion is for options trading based on technical analysis of fundamentally strong companies. She especially enjoys setting up weekly covered calls for income generation.

Article printed from InvestorPlace Media, https://investorplace.com/2022/02/7-best-quantum-computing-stocks-to-buy-in-2022/.

©2022 InvestorPlace Media, LLC

How much have countries and blocs invested in quantum computing?

What countries and blocs are leading in developing quantum computing?

How much have countries and blocs invested in quantum computing?

What countries and blocs are leading in developing quantum computing?

How much have countries and blocs invested in quantum computing?

What countries and blocs are leading in developing quantum computing?

How much have countries and blocs invested in quantum computing?

What countries and blocs are leading in developing quantum computing?

How much have countries and blocs invested in quantum computing?

What countries and blocs are leading in developing quantum computing?

Countries like Canada, Germany, and Australia are also investing heavily in quantum computing, with Canada spending over $1 billion in the past decade.

Title:

Content: There were 1,711 press releases posted in the last 24 hours and 342,181 in the last 365 days.

Supporting Canada's leadership in quantum computing to grow the economy and create jobs

TORONTO, Jan. 23, 2023 /CNW/ - Quantum technologies are at the leading edge of science and innovation. As Canadian researchers, workers and businesses continue to demonstrate leadership on the world stage in innovating and developing quantum technologies, we have the potential to transform how we work and live in Canada and around the world – in areas from fighting climate change to making advancements in health care. The Government of Canada will continue to support Canadian companies to help them keep growing and staying competitive, while driving economic growth and creating highly skilled and well-paying jobs for Canadians.

The Prime Minister, Justin Trudeau, today announced a new federal investment of $40 million to enable the Toronto-based Canadian quantum computing company Xanadu Quantum Technologies Inc. to build and commercialize the world's first photonic-based, fault-tolerant quantum computer. Once developed, this computer will have the potential to provide world leading capabilities to help solve complex data problems and could be used in a variety of sectors such as finance, transportation, environmental modelling, and health.

Supported through the government's Strategic Innovation Fund, this $177.8 million project is expected to create 530 new highly skilled positions in the high-tech and quantum computing fields.

Home to some of the world's largest quantum tech hubs, Canada is well positioned to become a global leader in the developing quantum sector, which will create new opportunities for Canadians and Canadian businesses. The Government of Canada will continue to invest in innovative companies to grow the economy and create highly skilled and well-paying jobs for Canadians.

Quotes

"Quantum technology is changing the world as we know it. With the potential to solve difficult problems in key areas such as health care, finance, and climate sciences, this sector expands the realm of possibility. Today's announcement is great news for Canadian workers and businesses. This investment will bring good jobs, spur economic growth, boost innovation, and solidify Canada as a world leader in quantum technology."

— The Rt. Hon. Justin Trudeau, Prime Minister of Canada

"Quantum technologies will set the course of the future and thanks to companies like Xanadu, Canada is at the forefront ready to lead. With today's announcement, our government is strengthening Canada's position in quantum technology and helping to create more economic growth and good jobs for Canadians. We'll continue to build this sector through our National Quantum Strategy and support made-in-Canada technology so Canada remains a world leader for decades to come."

— The Hon. François-Philippe Champagne, Minister of Innovation, Science and Industry

"The government's continued investment in quantum technologies has been invaluable to our success. We are proud to be a Canadian company and, with this investment, are excited to enter the next phase in our mission to build quantum computers that are useful and available to people everywhere."

— Christian Weedbrook, Founder and CEO, Xanadu

Quick Facts

  • Since the birth of quantum science more than 100 years ago, quantum technologies have been the source of many game-changing innovations such as semiconductors and the laser.
  • Quantum science is the study, manipulation, and control of systems at the atomic and subatomic level.
  • It is estimated that by 2045, the Canadian quantum industry will be a $139 billion industry, including all economic effects, and account for over 200,000 jobs, according to a study commissioned by the National Research Council in 2020.
  • Earlier this month, the Government of Canada launched its National Quantum Strategy, which invests an additional $360 million to help solidify Canada as a global leader in quantum technologies.
  • Over the past 10 years, the Government of Canada has invested more than $1 billion in quantum research and science.
  • Additionally, the government has invested in bringing new quantum technologies to the Canadian and global markets, including investments through Canada's regional development agencies, the Strategic Innovation Fund, and the National Research Council of Canada's Industrial Research Assistance Program.
  • Xanadu is a notable contributor to Canada's innovation ecosystem and has committed to continuing to support innovation, growth, and Canada's research and development sector.
  • Founded in 2016, Xanadu is a Toronto-based Canadian quantum computing company with the mission to build quantum computers that are useful and available to people everywhere. Xanadu has become one of the world's leading quantum hardware and software companies and leads the development of PennyLane, an open-source software library for quantum computing and application development.

Associated Links

This document is also available at https://pm.gc.ca

SOURCE Prime Minister's Office

View original content: http://www.newswire.ca/en/releases/archive/January2023/23/c3179.html

What countries and blocs are leading in developing quantum computing?

The global quantum computing market is expected to reach $1 trillion by 2035, led by companies like Google and IBM.

The global quantum computing market is expected to reach $1 trillion by 2035, led by companies like Google and IBM.

The global quantum computing market is expected to reach $1 trillion by 2035, led by companies like Google and IBM.

Quantum computing can revolutionize industries like finance, healthcare, and logistics by solving complex problems.

Title:

Content: The present and future of quantum computing
New Research 2022 / 12 / 13 19: 16: 07 Edited by: Yuansheng
The limitations of contemporary supercomputers, as well as their implications for academia and institutions around the world, are drawing the attention of the scientific community.
For example, researchers can use current techniques to perform more complex simulations, such as those that focus on chemistry and the reactive properties of each element.
However, as the complexity of these interactions increases, they become more challenging for current supercomputers.
Due to the limited processing power of these devices, it is nearly impossible to complete these types of calculations, forcing scientists to choose between speed and precision when conducting these studies.
To provide some context for the breadth of these experiments, let ’ s start with the example of hydrogen atom modeling.
With only one proton and one electron in hydrogen, researchers can easily perform chemical reactions manually or rely on computers to complete calculations.
However, depending on the number of atoms and whether the electrons are entangled, the process becomes more difficult.
To write out every conceivable result of an element like thulium, which contains a staggering 69 electrons, all twisted together, would take more than 20 trillion years.
Obviously, this time is too long for us, and we need a new way out.
Quantum computers open the door to a whole new world of possibilities.
The equations needed to simulate chemistry have been known to the scientific community since the 1930s, but it has only recently begun to build computers with the ability and reliability to perform these calculations.
Today ’ s quantum computers provide the speed researchers need to mimic all aspects of chemistry, making them significantly predictive and reducing the need for laboratory testing.
Colleges and universities may be able to use quantum computers to augment existing knowledge of chemistry.
Consider the potential time and cost savings that could be achieved if quantum computers were able to eliminate the need for laboratory testing during research.
Moreover, since the computational power to master chemical properties did not exist previously, this step could lead to a major step forward in chemistry previously unknown to the world
01. Quantum computing in practice
Many companies are already using quantum computing.
For example, IBM is working with Mercedes-Benz, ExxonMobil, CERN, and Mitsubishi Chemical to implement quantum computing into their products and services:
Mercedes-Benz
Mercedes-Benz is exploring quantum computing to create better batteries for its electric vehicles.
The company hopes to shape the future of modern electric vehicles by implementing quantum computing in its products and making an impact on the environment by implementing quantum computing in its products in an effort to be carbon neutral by 2039.
Simulating what ’ s going on inside a battery is incredibly difficult, even with today ’ s most advanced computers.
However, using quantum computing technology, Mercedes-Benz can more accurately simulate chemical reactions in car batteries.
Exxon Mobil
ExxonMobil is using quantum algorithms to more easily discover the most efficient routes for transporting clean combustion fuels around the world.
Without quantum computing, it would be almost impossible to compute all routing combinations and find the most efficient routing combinations.
European Centre for Nuclear Research
The European Centre for Nuclear Research (CERN) is trying to discover the secrets of the universe.
Using quantum computing, CERN can find algorithms to pinpoint complex events in the universe in a more efficient way.
For example, quantum computing could help CERN figure out patterns in the Large Hadron Collider (LHC) data.
Mitsubishi Chemical
A team from Mitsubishi Chemical and Keio University is working on a key chemical step for lithium-oxygen batteries: lithium superoxide rearrangement.
They are using quantum computers to "perform accurate simulations of what happens inside a chemical reaction at the molecular level".
Advantages and disadvantages of quantum computing
Quantum computing has the potential to revolutionize industries such as finance, pharmaceuticals, artificial intelligence, and automotive in the coming years, fundamentally changing the world around us.
The value of quantum computers comes from the probabilistic way in which they operate.
By using the probabilistic computing style directly instead of simulating it, computer scientists have shown potential applications for fast search engines, more accurate weather forecasts, and precise medical applications.
In addition, quantum computers represent the original motivation for the development of quantum computing and are very useful in directly simulating quantum mechanics.
Perhaps the main appeal of quantum computing is that it can solve problems faster, making it ideal for applications that need to handle large amounts of data (for example, aerospace logistics, drug manufacturing, molecular research, or other fields that use canonical processes at the atomic level).
However, creating a powerful quantum computer is not an easy task and involves many drawbacks.
The sensitivity of quantum computing systems to extreme temperatures is one of the main drawbacks.
In order for the system to function properly, it must be near absolute zero temperature, which poses a major engineering challenge.
Moreover, quantum bit quality is not where it needs to be.
After a given number of instructions, qubits can produce inaccurate results, and quantum computers lack error correction to solve this problem.
Because of the number of wires or lasers required to make each qubit, keeping control is difficult, especially if the goal is to create a chip with a million qubits.
And quantum computing is very expensive: the cost of a single qubit can be as high as $10,000 or so.
Finally, if standard information systems and encryption methods are used for malicious purposes, they will be overwhelmed by the processing power of quantum computers.
These computers ’ reliance on the principles of quantum physics allows them to decrypt the most secure data (e.g., bank records, government secrets, and internet / email passwords).
Cryptography experts around the world will need to develop encryption techniques that can withstand possible attacks from quantum computers.
Impact of Quantum Computing on Higher Education
The education community is always looking for new opportunities for growth and prosperity.
Many higher education institutions have begun extensive research into quantum computing, using the unique properties of quantum physics to usher in a new era of technology, including computers capable of performing currently impossible computations, ultra-secure quantum networks, and exotic new quantum materials.
Oxford University
Researchers at the University of Oxford are interested in quantum research because of its huge potential in areas such as healthcare, finance and security.
The university is recognized worldwide as a pioneer in the field of quantum science.
Oxford and York universities demonstrate first working pure state NMR quantum computer
Harvard University
Researchers at Harvard University have established a community group, the Harvard Quantum Initiative for Science and Engineering, with the goal of making significant progress in science and engineering related to quantum computers and their applications.
According to research conducted by the group, the “second quantum revolution ” will build on the first quantum revolution, which is responsible for the development of global communications, technologies such as GPS flight, and medical breakthroughs such as magnetic resonance imaging.
University of Maryland
Researchers from the University of Maryland's Department of Physics, the National Institute of Standards and Technology, and the Physical Sciences Laboratory are part of the Joint Quantum Institute "dedicated to the goal of controlling and utilizing quantum systems."
Institute of Technology
MIT researchers have built a quantum computer and are working on areas such as quantum algorithms and complexity, quantum information theory, measurement and control, and applications and connectivity.
University of California, Berkeley
Researchers at the Center for Quantum Computing and Information at the University of California, Berkeley are working on basic quantum algorithms, cryptography, information theory, quantum control, and experiments with quantum computers and quantum devices.
University of Chicago Quantum Exchange
Researchers at the University of Chicago Quantum Exchange are focusing on developing new ways to understand and utilize the laws of quantum mechanics. CQE encourages collaboration, joint projects and information exchange between research groups and collaborating institutions.
China University of Science and Technology
Researchers at the University of Science and Technology of China are exploring quantum optics and quantum information.
Areas of major interest include quantum foundations, free space and fiber-based quantum communication, superconducting quantum computing, supercooled atomic quantum simulations, and quantum metrology theory and theory-related concepts.
One broad impact on higher education is that quantum computing will open up new careers for tomorrow ’ s students.
In addition, this technology will allow for accurate forecasting of the overall growth of the job market and the demand for skilled and knowledgeable workers in all fields.
In the near future, the power of quantum computing will be unleashed on machine learning.
In the field of education, quantum-driven algorithms will make informed decisions about student learning and deficiencies, just as quantum computing promises to revolutionize medical classification and diagnosis.
In addition, quantum computing will power a new era of individual learning, knowledge and achievement.
This will be achieved by processing large amounts of student data in a timely manner, and quantum computers may eventually have the ability to control programs designed to accommodate students ’ unique achievements and abilities, as well as backfilling specific areas where students may need help.
These aspects of quantum computing are critical to achieving the goal of truly personalized learning.
Through the cloud, you can access any of the relatively small number of physical quantum subcomputers in the world.
These computers include the 20 + IBM Quantum System One, which is currently installed more in the United States, Germany and Japan, and more are planned in the United States, South Korea and Canada.
Anyone with an internet connection can log on to a quantum computer and be educated on the basics of quantum programming.
For example, IBM offers a variety of quantum-centric education programs, including access to quantum computers, teaching support, summer schools, and hackathons.
The IBM Quantum Educator and Investigator Program and Qubit ’ s “Introduction to Quantum Computing ” are just two examples of quantum computing resources that are accessible to educators and students alike.
Such initiatives are absolutely necessary.
Colleges and universities around the world need to collaborate to bridge the current knowledge gap in quantum education and prepare the next generation of scientists and engineers.
04 、 Conclusion
The quantum computing revolution is happening.
We have just entered a new era of computing.
Next generation computing is not the next generation of hardware, but the next generation of algorithms and computing
Quantum computers use quantum mechanics principles to solve problems.
Compared to classical computers, the state of a quantum system is inherently probabilistic.
This means that quantum computers can handle many times more computations than conventional computers.
05, extended reading
The main players in quantum computing can be divided into four categories: the first category is international technology giants, such as IBM, Google, Honeywell, etc.; the second category is quantum computing startups, such as Rigetti, IonQ, etc.; the third category is national scientific research institutes, such as Fermilab, Argonne National Laboratory, and the Institute of Quantum Information and Quantum Technology Innovation. University of Cambridge, University of Science and Technology of China, Harvard University, etc.
Today's quantum computers can only deal with one or a few aspects of the problem, and they have not yet reached the level of generality.
Quantum technology companies not only need to invest heavily in developing quantum computers, but also need to have many researchers designing and manufacturing quantum hardware and software to support these machines.
In the future, general quantum computers need to work on the underlying quantum physics equipment, quantum computer architecture, quantum resource scheduling, upper quantum programming language, quantum algorithms and quantum application software.
The following are typical representatives of the quantum computing industry regarding the latest technological and commercial advances in quantum computing.
The information provided herein is for general guidance and informational purposes only, and the contents of this article should not be considered investment, business, legal or tax advice under any circumstances.
This article is from the WeChat public account: new research (ID: chuxinyanjiu), author: Yousef Fazea, compiled by: Tang Shi
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What advantages do quantum computers have over conventional computers?

extremely fast calculations
extremely complex calculations

What fields can quantum computers advance?

IBM, Mercedes-Benz, and others are exploring quantum computing in their products and services.

What are important areas in quantum research?

What companies are leading in developing quantum computing?

Quantum computing has the potential to bring breakthroughs in fields like cryptography, drug discovery, and machine learning.

Title:

Content: The quantum leap: Quantum computing breakthroughs to watch

The classical computer has been the bedrock of computing for over 50 years. That’s going to change soon. quantum computing, which was once a concept limited to fringe scientific papers, is now becoming a mainstream topic.

We’re seeing significant breakthroughs in the headlines which are stoking the flames of conjecture. The truth is, that this technology will bring with it much more than hype and opportunities to breathe life into sci-fi creations. In this article, we’re going to dive into some of the milestones of quantum computing, future goals and, of course, the challenges that we still have to overcome.

The Quantum Paradigm

Classical computers began as room-sized machines. Computer scientists from the 1950s would be completely flummoxed to see the powerful gaming or AI training rigs of today. That said, computers process information using bits -- either a 0 or a 1. quantum computers break the mold by using quantum bits, or qubits. They’re built upon the principles of quantum mechanics, which allow us to conceptualize that a qubit can exist in a state of 0, 1, or both at the same time (this is known as superposition in quantum theory).

As a result of this state, quantum computers are able to measure vast quantities of possibilities at the same time and exponentially increase their computing power compared to classical machines.

Significant Milestones in Quantum Computing

As with everything groundbreaking, quantum computing has been the subject of much fanfare, which has caused tangible advancements to slip through the cracks. This includes:

The Rise of Quantum Supremacy

The idea of "quantum supremacy" once seemed rather farfetched. That was until Google demonstrated with its Sycamore processor exactly what quantum machines could do. Sycamore was given a calculation that would have taken a classical computer 10,000 years to complete. It completed it in 200 seconds. quantum supremacy is now a modern reality and not just a hypothesis.

Innovations in Quantum Error-Correction

The inherently fragile nature of qubits means they're prone to errors from even the smallest environmental interference. Over the years, researchers have been laser-focused on tackling this problem, giving rise to various quantum error-correction protocols. Among the most prominent are the "surface code" and "cat code" methods, which deploy specialized qubit arrangements and extra layers of computational checks to detect and correct errors in real time.

Development of Quantum Algorithms

Unsurprisingly, with the growth of quantum processors has come an increase in quantum algorithms being developed. Algorithms like Shor's (for integer factorization) and Grover's (for database searching) have proven quantum computing's superiority over classical methods.

quantum algorithms have more granular applications as well, especially for devs and larger organizations. They could drastically reduce the time it takes to render documents in a React PDF viewer, particularly those that are large or contain complex elements like high-resolution images or intricate designs. Imagine one day sending petabytes of multimedia files without delay.

In a fraction of a second, teams could edit, compare, and merge files, all on their native platform, without having to wait until all the documentation is ready for analysis or sending.

This is just a microcosm of how massive quality-of-life (QoL) improvements from quantum computing will actually be. Aside from document readers, artists will also be able to render entire films in a matter of seconds, as there will be no resolution too high to be processed instantly. The same goes for 4K video calls without lags, VR gaming, and so much more.

Quantum Potential

What makes quantum computers so powerful is their ability to solve the problems that have simply been out of reach for classical machines, This includes:

  • Cryptography: Certain mathematical problems (like factorizing large prime numbers) are difficult for modern classical computers. quantum computers, however, are able to solve these problems much faster due to their parallel processing capabilities. Modern digital security rests on the assumption that these problems prevent computers from solving them quickly, and so quantum computing will be incredibly disruptive to modern cryptography. "Revolutionary" won’t even begin to define it.
  • Drug Discovery and Material Science: Another difficult task for classical computers is simulating and understanding complex molecular structures. With quantum computing, molecular simulations will be turbo-charged and lead to important breakthroughs in medicine and material science at a blistering pace.
  • Optimization Challenges: Be it traffic management, financial modeling, or supply chain optimization, problems involving multiple variables and constraints could benefit immensely from quantum computing's prowess, resulting in more efficient and optimal solutions.
  • Machine Learning and Big Data: Data is the new oil. And companies everywhere are drilling. quantum computers can process and analyze vast datasets swiftly and can send machine learning models to the stratosphere. This will lead to more accurate predictions and insights.

Navigating Quantum Challenges

The dream of a large-scale, fault-tolerant quantum computer is still just a dream for now, due to certain technical hurdles.

The first is maintaining the quantum state of qubits over extended durations. The term for this is ‘quantum coherence’, and it is not an easy task. External disturbances such as cosmic rays or nearby electronic devices can disrupt its state and prevent long computations.

Of course, one must also ponder about scalability. Scaling from a few qubits to thousands or even millions which are needed for more complex tasks will need further innovations in quantum error correction (and system architecture for that matter).

For now, computer scientists have gotten around this by using extremely low temperatures to maintain qubit stability, but this is not something companies or organizations without vast resources can accomplish.

Another aspect to consider is the software ecosystem. quantum computers will need their own kind of software, along with unique programming languages and tools. This will take years and possibly decades of collaboration between physicists, computer scientists, and industry stakeholders before a barebones system is achieved. QApplications in Diverse Domains

quantum computing is going to massively change many sectors. That said, some stand to benefit sooner than the rest:

  • Financial Modeling: The financial sector is an obvious winner when it comes to having more computing power -- the sector is already using AI to its advantage. quantum algorithms will allow traders and analysts to evaluate vast numbers of scenarios extremely quickly, giving those companies with quantum machines an extraordinary advantage.
  • Climate Modeling: Predicting the Earth’s climate involves accounting for a ton of variables and how they interact with each other. quantum computers will allow more accurate climate models and better insights into climate change which will hopefully help us develop better strategies for mitigating it.
  • Logistics and Supply Chain: Efficient solutions to the traveling salesman problem -- a challenge that involves finding the shortest possible route through multiple cities -- could revolutionize logistics, saving time and reducing costs for businesses worldwide.

The Interplay Between Quantum and Classical Systems

While you may think that quantum computers will eventually replace classical computers, the truth is the future more likely has them together in a symbiotic relationship. This is because quantum machines will be used for tasks they’re better at, namely more advanced computational needs, while classical computers will be kept for more routine tasks and for user interfaces. An example of this already exists in cloud-based quantum computing platforms -- where users can send a certain task to a quantum machine and receive the result through their own classical machine.

Looking Towards the Quantum Future

The next decade promises a slew of breakthroughs. Today’s quantum computers are being compared to the classical computers of the 1950s, which is probably accurate considering they’re still in their nascent stage of development and haven’t even begun realizing their full potential.

quantum computing promises an increase in computation power for sure, but it offers much more than that. It promises a massive shift across many industries -- from healthcare to finance, energy and transportation. We live in exciting times as we stand on the precipice of a new era in technology, one that previously only belonged to the pages of science fiction.

Image credit: plotplot/Shutterstock

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What advantages do quantum computers have over conventional computers?

What fields can quantum computers advance?

There are significant challenges, including the need for robust quantum error correction and noise reduction.

Title:

Content: Singapore-based quantum software startup Entropica Labs has recently secured a $4.7 million Series A funding round.
It is understood that the financing was jointly led by Italian deep technology investment institution Liftt and its existing investor Wavemaker Partners, with participation from SEEDS Capital (the investment arm of Singapore Enterprise Development Authority), CerraCap Ventures, SUTD Venture Holdings, Elev8 and others.
According to the statement, the funds will be used to expand Entropica Labs ’ team building in the areas of quantum error correction, software engineering and computational architecture.
Entropica Labs was founded in 2018 to provide developers and users with software development tools that enable quantum computers to recognize and correct errors during computation, helping them improve accuracy and efficiency in quantum computing.
Entropica Labs says that as hardware companies continue to roll out larger and more advanced quantum computing systems, some of which have crossed computational thresholds, the demand for complex error correction schemes in the field has become more intense, so Entropica Labs hopes to enhance the space for quantum computers with scalable software tools.
According to the official website, Entropica Labs has now launched two products, OpenQAOA and JEPOS, the former is a multi-end and open source Python software development kit for quantum computer optimization, and the latter can be used for benchmarking quantum performance.
It is worth mentioning that earlier this year, another Singapore-based quantum computing startup called Horizon Quantum Computing also received a Series A funding round.
It is understood that the size of the financing is 18.1 million US dollars, and the investors include Tencent.

What are the challenges in quantum computing research?

sensitivity to environment
high error rates

The quantum computing market is expected to grow 36.89% annually from 2022 to 2032, reaching USD 234.06 billion.

Major players in the quantum computing market include IBM, Google, Microsoft, Honeywell, Intel, and Rigetti Computing.

Title:

Content: Finland has big plans for quantum computing applications

The QuTI project will develop new components, manufacturing and testing solutions, and algorithms for the needs of quantum computing applications.
25 January 2022

Quantum computing applications are expected to be adopted by more industries this year as organizations around the world begin testing the use cases for the technology. While organizations are the ones most looking forward to making the most of the technology, a few governments are also hoping quantum computing applications can improve their services.

In Finland, their first-ever quantum computer was commissioned at a research center near the capital. Scientists are expected to use it to study next-generation computing power. The 5 quantum-bit computers were developed to learn how to build a quantum computer, how to program one, and how to operate one in the future.

The state-owned VTT Technical Research Center (VTT) plays a crucial role in ensuring researchers learn in a range of scientific domains and making quantum computing applications ready for the industry. According to a report by Computer Weekly, the Finnish government believes that the best way to be ready for the quantum computing industry is to build a working quantum computer.

Computer Weekly also highlights five areas for quantum computing applications. They are in drug and materials discovery, supply chain and logistics, financial services, artificial intelligence, and cloud security.

For drug and materials discovery, Computer Weekly reports that a separate team in VTT which is the quantum algorithm team is developing algorithms to be used on the quantum computer. They are looking at two broad types of quantum computing applications. The first is to solve complex optimization problems that exist in many industries. This includes energy distribution, process control, and fleet management. The second is to predict the structures and properties of molecular formations more accurately and effectively. This will help accelerate drug discovery and the development of new materials.

While other countries are also developing quantum computer ecosystems, with the majority focusing on topics and platforms. Tech vendors like IBM and Google, who are also developing quantum use cases are not government-linked or owned and are mostly testing industry use cases.

Compared to the rest of the world, Finnish researchers focus almost exclusively on the superconducting qubit approach, which they have been using for years and know very well. In fact, a new research project has just been launched to accelerate the progress of Finnish quantum technology.

The QuTI project, coordinated by VTT, will develop new components, manufacturing and testing solutions, and algorithms for the needs of quantum technology. The QuTI consortium, partly financed by Business Finland, consists of 12 partners and has a total budget of around EUR 10 million.

For Professor Mika Prunnila, QuTI project’s coordinator, from VT, “Quantum technology is a multidisciplinary and rapidly advancing field. The QuTI consortium provides an ideal starting point for strengthening the international competitiveness of Finnish technology and industry in this fast-growing field.”

The quantum computing, communication and sensing devices to be developed in the QuTI project are largely based on expertise in microsystems, photonics, electronics, and cryogenics. The project develops customized software and algorithms hand in hand with the hardware, strengthening the Finnish quantum computing infrastructure. In addition, new tools will be created for quantum technology product development that will serve the needs of the QuTI project as well as the entire field of quantum technology.

As China and the US continue to battle each other for quantum computing supremacy, Finland is definitely building their presence in the industry as well. With the government supporting quantum computing initiatives, Finland might just have a quantum computing ecosystem on the horizon.

What countries and blocs are leading in developing quantum computing?

What countries and blocs are leading in developing quantum computing?

Google achieved quantum supremacy in 2019 with its Sycamore processor.

Title:

Content: Google, IBM and China have already achieved quantum supremacy. Now they face another challenge: the correction of errors

Quantum supremacy is no longer at the center of the debate. It was at the end of 2019 because it came to light that the Google team led by John Martinis had managed to achieve it using its Sycamore quantum processor, and no one had done it until that moment. The noise that this news caused when it broke was justified.

But a year later, in December 2020, the group of Chinese researchers led by Jian-Wei Pan published an article in Science showing that I had also reached using its Zuchongzhi superconducting processor. And a year later, in November 2021, IBM followed suit and announced that it had reached this milestone using its 127-qubit Eagle quantum processor.

At this point no one doubts that quantum computers have come a long way. And, furthermore, they have done it in a real record time if we bear in mind that the first solid theoretical proposals arrived in the mid-1990s. And they are already capable of solving a few problems (very few still). in much less time than the most advanced supercomputers we currently have.

In fact, this is what quantum supremacy consists of: in solving in a short period of time, a few minutes or a few hours, a problem in which a classical supercomputer would spend many years. Even several centuries. Or millennia. Right now it is not too important whether these problems have practical applications or not. Whether or not they are relevant. We are still establishing the foundations of quantum computing, and the important thing is to face the challenges that are around the corner.

In search of higher quality qubits

One of the biggest challenges facing researchers involved in the development of quantum computing is delaying the onset of quantum decoherence. This phenomenon occurs when the necessary conditions for a system that is in an entangled quantum state to be maintained disappear.

Perhaps a slightly simpler way of describing it is to see it as a system that stops behaving as dictated by the rules of quantum mechanics when certain conditions are met, beginning to behave from that moment on as dictated by the rules of classical physics. . When does quantum decoherence appear? quantum effects disappear. And, therefore, also the advantages that they bring in the context of quantum computing.

The time it takes for quantum decoherence to appear is closely linked to the quality of the qubits

This phenomenon is very important because it helps us understand why many macroscopic physical systems do not exhibit quantum effects. Or, what is the same, why in our daily environment we cannot observe the counterintuitive effects of quantum mechanics. In any case, what is really relevant is that as the the quality of the qubits of a quantum processor, the longer it takes for quantum decoherence to appear. And, for this reason, we have more time available to carry out operations with it.

The two qubit fabrication technologies that are currently giving us the best results are superconducting qubits, which benefit greatly from recent advances in silicon lithography, and ion traps. However, some research groups also have other very promising technologies on the table that are worth pursuing, such as neutral atoms or the ions implanted in macromolecules.

IBM already has a 127-qubit superconducting quantum processor, and by the end of 2023 it plans to have Condor ready, a promising quantum chip with no less than 1,121 qubits.

We already brush the correction of errors with the tips of our fingers

The other big challenge facing quantum computing right now is error correction. Quantum computers make errors when carrying out some operations, and when this happens, the results they return to us are not correct, of course. The problem is that implementing a quantum error correction protocol it’s not trivial. And furthermore, if they abound, it is essentially impossible to correct them and simultaneously prevent the quantum processor’s efficiency from sinking.

Fortunately, we have good news. As we told you a few days ago, three independent research groups have managed to perfect superconducting qubits that have an accuracy greater than 99%. This simply means that they make mistakes very infrequently, and the good news is that when they are so infrequent it is easier to correct them. Much easier.

When the incidence of errors is less than 1%, it is much easier for quantum fault-correction protocols to carry out their task

In fact, these research groups ensure that when the incidence of errors is less than 1% quantum fault-correction protocols find it much easier to do their job. At the moment they are working with only one or two qubits, and these quantum processors are too simple to solve significant problems, but if they manage to scale this technology to many more qubits, quantum computers could leave behind one of the biggest challenges they currently face. .

As we have just seen, quantum computing is advancing at a breakneck pace. The entry of private companies in this sector you are greatly accelerating your progress, but before we get carried away with enthusiasm, it is important that we keep in mind that there are other challenges that are also crucial to solve.

Two of the most substantial are the need to control qubits more precisely, and also the importance of implementing new quantum algorithms that they are able to help us tackle the problems that we cannot solve with the most powerful classical supercomputers that we have today. Still, the future for quantum computing is hopeful. And, above all, very promising.

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What are important areas in quantum research?

What companies are leading in developing quantum computing?

What countries and blocs are leading in developing quantum computing?

What have been the landmark achievements in quantum computing?

Google's Sycamore quantum supremacy experiment

IBM achieved quantum supremacy in 2021 with its 127-qubit Eagle processor.

What are important areas in quantum research?

What companies are leading in developing quantum computing?

What countries and blocs are leading in developing quantum computing?

What seminal quantum computers/ processors have been developed?

IBM plans to have a 1,121-qubit quantum processor called Condor ready by the end of 2023.

Title:

Content: Google, IBM and China have already achieved quantum supremacy. Now they face another challenge: the correction of errors

Quantum supremacy is no longer at the center of the debate. It was at the end of 2019 because it came to light that the Google team led by John Martinis had managed to achieve it using its Sycamore quantum processor, and no one had done it until that moment. The noise that this news caused when it broke was justified.

But a year later, in December 2020, the group of Chinese researchers led by Jian-Wei Pan published an article in Science showing that I had also reached using its Zuchongzhi superconducting processor. And a year later, in November 2021, IBM followed suit and announced that it had reached this milestone using its 127-qubit Eagle quantum processor.

At this point no one doubts that quantum computers have come a long way. And, furthermore, they have done it in a real record time if we bear in mind that the first solid theoretical proposals arrived in the mid-1990s. And they are already capable of solving a few problems (very few still). in much less time than the most advanced supercomputers we currently have.

In fact, this is what quantum supremacy consists of: in solving in a short period of time, a few minutes or a few hours, a problem in which a classical supercomputer would spend many years. Even several centuries. Or millennia. Right now it is not too important whether these problems have practical applications or not. Whether or not they are relevant. We are still establishing the foundations of quantum computing, and the important thing is to face the challenges that are around the corner.

In search of higher quality qubits

One of the biggest challenges facing researchers involved in the development of quantum computing is delaying the onset of quantum decoherence. This phenomenon occurs when the necessary conditions for a system that is in an entangled quantum state to be maintained disappear.

Perhaps a slightly simpler way of describing it is to see it as a system that stops behaving as dictated by the rules of quantum mechanics when certain conditions are met, beginning to behave from that moment on as dictated by the rules of classical physics. . When does quantum decoherence appear? quantum effects disappear. And, therefore, also the advantages that they bring in the context of quantum computing.

The time it takes for quantum decoherence to appear is closely linked to the quality of the qubits

This phenomenon is very important because it helps us understand why many macroscopic physical systems do not exhibit quantum effects. Or, what is the same, why in our daily environment we cannot observe the counterintuitive effects of quantum mechanics. In any case, what is really relevant is that as the the quality of the qubits of a quantum processor, the longer it takes for quantum decoherence to appear. And, for this reason, we have more time available to carry out operations with it.

The two qubit fabrication technologies that are currently giving us the best results are superconducting qubits, which benefit greatly from recent advances in silicon lithography, and ion traps. However, some research groups also have other very promising technologies on the table that are worth pursuing, such as neutral atoms or the ions implanted in macromolecules.

IBM already has a 127-qubit superconducting quantum processor, and by the end of 2023 it plans to have Condor ready, a promising quantum chip with no less than 1,121 qubits.

We already brush the correction of errors with the tips of our fingers

The other big challenge facing quantum computing right now is error correction. Quantum computers make errors when carrying out some operations, and when this happens, the results they return to us are not correct, of course. The problem is that implementing a quantum error correction protocol it’s not trivial. And furthermore, if they abound, it is essentially impossible to correct them and simultaneously prevent the quantum processor’s efficiency from sinking.

Fortunately, we have good news. As we told you a few days ago, three independent research groups have managed to perfect superconducting qubits that have an accuracy greater than 99%. This simply means that they make mistakes very infrequently, and the good news is that when they are so infrequent it is easier to correct them. Much easier.

When the incidence of errors is less than 1%, it is much easier for quantum fault-correction protocols to carry out their task

In fact, these research groups ensure that when the incidence of errors is less than 1% quantum fault-correction protocols find it much easier to do their job. At the moment they are working with only one or two qubits, and these quantum processors are too simple to solve significant problems, but if they manage to scale this technology to many more qubits, quantum computers could leave behind one of the biggest challenges they currently face. .

As we have just seen, quantum computing is advancing at a breakneck pace. The entry of private companies in this sector you are greatly accelerating your progress, but before we get carried away with enthusiasm, it is important that we keep in mind that there are other challenges that are also crucial to solve.

Two of the most substantial are the need to control qubits more precisely, and also the importance of implementing new quantum algorithms that they are able to help us tackle the problems that we cannot solve with the most powerful classical supercomputers that we have today. Still, the future for quantum computing is hopeful. And, above all, very promising.

Pictures | IBM

Source link

About Admin

Check Also

Android | Why does my cell phone get hot | Solution | problem | Smartphones | Battery | nnda | nnni | SPORT-PLAY

Currently, cell phones have a series of components, such as a battery that lasts two …

What are important areas in quantum research?

What companies are leading in developing quantum computing?

What seminal quantum computers/ processors have been developed?

Google has achieved a breakthrough in quantum computing by increasing qubit array size while reducing error rates.

Title:

Content: Google confirms quantum computing breakthrough – more computing power with fewer errors
On the pages of our site you can find a lot of information about quantum computers, so regular readers know that quantum bits, qubits, are very sensitive to external interference.
Light, heat and electromagnetic waves cause errors during calculations, which makes the results of these calculations less reliable.
And, the more qubits are included in the quantum computing system, the higher, naturally, the error rate becomes.
However, representatives of the group of developers of quantum systems Google announced that they managed to “see the light at the end of the tunnel ”.
In their latest work, they used new algorithms for quantum error correction, which allowed them to increase the dimension of the qubit array, while even lowering the error rate.
Previously, Google specialists combined qubits into logical groups of 17 qubits, but the new design of a logical qubit with 49 qubits allowed to implement a more effective mechanism for correcting errors.
According to the available data, this case is the first in the history of quantum informatics, when the size of an array of qubits was increased while reducing the error rate.
And this is a very big and important step towards the creation of a real universal quantum computer.
However, the creation of a large logical qubit with a small error rate in itself entails the need to modify the hardware and software of a quantum computing system.
At present, Google specialists are already working towards the creation of a new system of cryogenics and electronic control.
When all this is ready, it will be embodied in the form of a new processor for the next generation quantum computer Sycamore 2, which will replace the previous computer and will be used as a cloud service for the development of new drugs, battery technologies, new materials, etc.
Key words:
Google, Quantum, Computer, Processor, Cubit, Error, Odds, Sycamore
Primary source
Other news on the topic:
Google begins to introduce the first technologies of error correction in the field of quantum computing
Google predicts the emergence of full-fledged quantum computers capable of self-learning within the next ten years
Intel begins development of silicon qubits, which will become the basis of scalable quantum computers with millions of qubits
A new type of quantum logic element will allow you to create quantum computers that do not allow errors
Matrix of five superconducting qubits - a prototype of the future quantum processor
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What are important areas in quantum research?

What are the challenges in quantum computing research?

What companies are leading in developing quantum computing?

Developing low-error quantum computing systems is key to creating a universal quantum computer, with Google and IBM at the forefront.

Title:

Content: State of the Art Quantum Chemistry in 2022

Quantum chemistry is very hard. The best quantum computing chemistry seems to be at the level of 12 qubits / 12 atoms. Supercomputer simulations can handle 20 qubits and 20 atoms simulation. There are early papers that suggest classical supercomputers can get to 100 atoms and 1000 qubit for some types of simulation. Quantum computers are pushing up to 35 high fidelity trapped ion and there is work to achieve superior error mitigation and error suppression and eventual error correction with quantum computers. Breakthroughs in algorithms for supercomputers and for quantum systems are continuing and there are many competitors with different quantum technologies looking to make breakthroughs to scale to thousands and millions of qubits and to develop superior and more efficient error management.

There was a paper in 2022 where quantum simulations on the Sunway supercomputer was performed. At the current stage, classical simulation of quantum computation is crucial for the study of quantum algorithms and quantum computing architectures, especially for heuristic quantum algorithms as VQE. The largest VQE experiment performed on a quantum computer up to date has used 12 qubits. An industrially relevant quantum computational advantage in quantum chemistry is expected to appear at around 38 ≤ N ≤ 68 qubits (under the assumption of error-corrected qubits), which is related to an electronic structure problem including
19 ≤ N ≤ 34 electrons.

Compared to RQC (Random Quantum Circuits), VQE (variational quantum eigensolver) is much more demanding for both quantum and classical computers, for example, the number of CNOT gates involved in a typical quantum computational chemistry simulation quickly goes beyond 1 million with commonly used physically motivated ansatz such as unitary coupled-cluster (UCC). Moreover, the parametric quantum circuit has to be executed many times as is typical for variational algorithms. These effects limit most of the current investigations of VQE using classical computers to very small problems (less than 20 qubits). Unleashing the Julia programming language on Sunway architectures and running it efficiently over 20 million cores is also an extremely challenging task. The 2022 work has set the standard for large-scale classical simulation of quantum computational chemistry, and paves the way for benchmarking VQE applications on near-term noisy quantum computers.

Q2 Chemistry is suitable for large-scale simulation of quantum computational chemistry, based on a combination of the Density Matrix Embedding Theory and the Matrix Product States to reduce the exponentially memory scaling against the system size; a customized three-level parallelization scheme has been implemented according to the nature of the physical problem and the many-core architecture; Julia is used as the primary language which both makes programming easier and enables cutting edge performance close to native C or Fortran; Real chemical systems have been studied to demonstrate the power of Q2Chemistry in computational quantification of proteinligand interactions. To the best of their knowledge, this is the first reported quantum computational chemistry simulation
calculation for real chemical system with as many as 100 atoms and 1000 qubits using DMET-MPS-VQE (and 200 qubits using MPS-VQE), and scales to around 20 million cores. This paves the way for benchmarking with near term
VQE experiments on quantum computers with around 100 qubits.

A new study shows that for problems of real-world interest, such as calculating the energy states of a cluster of atoms, quantum simulations are not yet more accurate than those of classical computers.

The study results show how close quantum computers are to becoming useful atomic and molecular simulation tools for chemists and materials scientists.

Garnet Chan of the California Institute of Technology and his co-workers performed simulations of a molecule and a material using a 53-qubit Google processor called Weber, based on Sycamore.

The team selected two problems of current interest, without any consideration of how well suited they might be to a quantum circuit. The first involves calculating the energy states of an 8-atom cluster of iron (Fe) and sulfur (S) found in the catalytic core of the enzyme nitrogenase. This enzyme breaks strong bonds in nitrogen molecules as the first step in an important biological process called nitrogen fixation. Understanding the chemistry of this process could be valuable for developing artificial nitrogen-fixing catalysts for the chemical industry.

One of the key obstacles to accurate quantum simulations is noise—random errors in both the switching of the “gates” that perform quantum logic operations and in the reading of their output states. These errors accumulate and restrict the number of gate operations a computation can enact before the noise dominates. The researchers found that simulations with more than 300 gates were overwhelmed by noise. But the more complex the system, the more gates are needed. The Fe-S cluster, for example, has long-range interactions between spins; to be represented accurately, such interactions require many gates.

The simulations provided predictions for the energy spectra of the Fe-S cluster and the heat capacity of 𝛼-RuCl3 reasonably well—but only if the simulated systems were not too big. For 𝛼-RuCl3 the team could only obtain meaningful results for a very small 6-atom chunk of the crystal lattice; if they increased the size to just 10 atoms, the noise overwhelmed the output. And the constraints on gate operations meant that only about one-fifth of Weber’s quantum resources could be used for the calculation.

State of the Art Quantum Chemistry on IonQ Trapped Ion

Quantum computation has attracted significant attention for its potential to solve certain computational problems more efficiently than with classical computers, especially since IBM launched the first cloud accessible quantum computer and Google demonstrated quantum advantage. One of its most promising applications is to solve electronic structure problems efficiently: to illustrate, consider that for a problem containing N spin orbitals, the number of classical bits required to represent the wave function scales combinatorially with N, while on a quantum
computer only N qubits are needed. The exponential advantage offered by quantum computers has motivated a great deal of research in developing quantum algorithms to solve the electronic structure problem.

The variational quantum eigensolver (VQE) algorithm is designed specifically for current near-term intermediate scale quantum (NISQ) computers. VQE estimates the ground state of a system by implementing a shallow parameterized circuit, which is classically optimized to variationally minimize the energy expectation value. The VQE algorithm allows the user to select the form of the parameterized circuit.

There is a research paper from $2 billion Trapped Ion quantum computer company IonQ. They got a new record with 12 qubits and 72 parameters. If I am not mistaken the Google work with 10 atoms and qubits was surpassed by this IonQ work.

IonQ is currently testing a 35 trapped ion qubit system. Trapped ion should theoretically be able to achieve physically perfect qubits. However, there are other sources of error in the whole system.

The Sunway supercomputer work on classical machines simulating atoms and the IonQ and other quantum systems will continue to push ahead and race to simulating larger and larger physical atomic and molecular systems.

Orbital-optimized pair-correlated electron simulations on trapped-ion quantum computers

Variational quantum eigensolvers (VQE) are among the most promising approaches for solving electronic structure problems on near-term quantum computers. A critical challenge for VQE in practice is that one needs to strike a balance between the expressivity of the VQE ansatz versus the number of quantum gates required to implement the ansatz, given the reality of noisy quantum operations on near-term quantum computers. In this work, we consider an orbital-optimized pair-correlated approximation to the unitary coupled cluster with singles and doubles (uCCSD) ansatz and report a highly efficient quantum circuit implementation for trapped-ion architectures. We show that orbital optimization can recover significant additional electron correlation energy without sacrificing efficiency through measurements of low-order reduced density matrices (RDMs). In the dissociation of small molecules, the method gives qualitatively accurate predictions in the strongly-correlated regime when running on noise-free quantum simulators. On IonQ’s Harmony and Aria trapped-ion quantum computers, we run end-to-end VQE algorithms with up to 12 qubits and 72 variational parameters – the largest full VQE simulation with a correlated wave function on quantum hardware. We find that even without error mitigation techniques, the predicted relative energies across different molecular geometries are in excellentagreement with noise-free simulators.

Is there evidence of exponential quantum Advantage in Quantum chemistry.

Abstract
The idea to use quantum mechanical devices to simulate other quantum systems is commonly ascribed to Feynman. Since the original suggestion, concrete proposals have appeared for simulating molecular and materials chemistry through quantum computation, as a potential “killer application”. Indications of potential exponential quantum advantage in artificial tasks have increased interest in this application, thus, it is critical to understand the basis for potential exponential quantum advantage in quantum chemistry. Here we gather the evidence for this case in the most common task in quantum chemistry, namely, ground-state energy estimation. We conclude that evidence for such an exponential advantage across chemical space has yet to be found. While quantum computers may still prove useful for quantum chemistry, it may be prudent to assume exponential speedups are not generically available for this problem.

Researchers from Berkeley and elsewhere examined the case for the exponential quantum advantage (EQA) hypothesis for the central task of ground-state determination in quantum chemistry. The specific version of EQA that they examined required quantum state preparation to be exponentially easy compared to classical heuristics, and for classical heuristics to be exponentially hard. Their numerical simulations highlight that heuristics are necessary to achieve efficient quantum ground-state preparation. At the same time, they do not find evidence for the exponential scaling of classical heuristics in a set of relevant problems. The latter suggests that quantum state preparation can be made efficient for the same problems. However, as EQA is based on the ratio of costs, this does not lead to EQA.

Numerical calculations are not mathematical proof of asymptotics with respect to size and error, nor can they exclude EQA in specific problems. However, their results suggest that without new and fundamental insights, there may be a lack of generic EQA in this task. Identifying a relevant quantum chemical system with strong evidence of EQA remains an open question. They did not consider tasks other than ground-state determination, nor do they rule out polynomial speedups. Depending on the precise form, polynomial quantum speedups could be associated with useful quantum advantage, as even a polynomial classical algorithm does not mean that solutions can be obtained in a practical time. Both aspects may prove important in the further development of quantum algorithms in quantum chemistry.

Title:

Content: New Codes Could Accelerate the Advent of Practical Quantum Computing

One of the biggest stumbling blocks for quantum computers is their tendency to be error-prone and the massive computational overhead required to clean up their mistakes. IBM has now made a breakthrough by dramatically reducing the number of qubits required to do so.

All computers are prone to errors, and even the computer chip in your laptop runs code designed to fix things when a bit flips accidentally. But fragile quantum states are far more vulnerable to things like environmental noise, which means correcting errors in quantum processors will require considerable resources.

Most estimates predict that creating just a single fault-tolerant qubit, or logical qubit, that can carry out useful operations will require thousands of physical qubits dedicated to error correction. Given that today’s biggest processors have just hundreds of qubits, this suggests we’re still a long way from building practical quantum computers that can solve real problems.

But now researchers at IBM say they’ve discovered a new approach that slashes the number of qubits required for error correction by a factor of 10. While the approach currently only works on quantum memory rather than computation, the technique could open the door to efficient new approaches to creating fault-tolerant devices.

Practical error correction is far from a solved problem,” the researchers write in a blog post. “However, these new codes and other advances across the field are increasing our confidence that fault tolerant quantum computing isn’t just possible, but is possible without having to build an unreasonably large quantum computer.”

The leading approach to error correction today is known as the surface code, which involves arranging qubits in a specially configured 2D lattice and using some to encode data and others to make measurements to see if an error has occurred. The approach is effective, but it requires a large number of physical qubits to pull off—as many as 20 million for some key problems of interest, according to IBM.

The new technique, outlined in a preprint on arXiv, comes from the same family of error-correction approaches as the surface code. But while each qubit in the surface code is connected to four others, the new technique connects them to six others, which makes it possible to encode more information into the same number of physical qubits.

As a result, the researchers say they can reduce the number of qubits required by an order of magnitude. Creating 12 logical qubits using their approach would require only 288 physical qubits, compared to more than 4,000 when using the surface code.

There are some significant caveats, though. For a start, it’s currently impossible to achieve the kind of six-way connectivity the team envisages. While the surface code operates on a single plane and can therefore be easily implemented on the kind of flat chip already found in quantum processors, the new approach requires connections to distant qubits that aren’t located on the same surface.

The researchers say this isn’t an insurmountable barrier, and IBM is already developing the kind of long-range couplers required to make these kinds of corrections. The technologies needed are certainly plausible, Jérémie Guillaud at French quantum computing startup Alice & Bob told New Scientist, and could be here in just a matter of years.

A bigger open question, though, is the fact that so far the approach only works with a small number of logical operations. This means that while it works for reading and writing to a quantum memory in a fault-tolerant way, it wouldn’t support most quantum computations.

But the IBM researchers say the techniques they’ve unveiled are just a stepping stone that points toward a rich new vein of even better error-correction approaches. If they’re right and scientists are able to find more efficient alternatives to the surface code, it could significantly accelerate the advent of practical quantum computing.

Image Credit: IBM

Edd Genthttp://www.eddgent.com/
I am a freelance science and technology writer based in Bangalore, India. My main areas of interest are engineering, computing and biology, with a particular focus on the intersections between the three.
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Title:

Content: Quantum Computing Comes To The Rescue?

Sep. 22, 2022 1:41 AM ETNVO1 Comment
Derek Lowe
3.69K Followers

Summary

  • Let's look at another aspect of the general computational enthusiasm that we're seeing in drug discovery these days.
  • Building the hardware for a working quantum computer is extremely difficult, as is keeping it working once you've built it.
  • So there are, in the end, a number of important choices to be made when you start talking about quantum computing for the life sciences.

Let's look at another aspect of the general computational enthusiasm that we're seeing in drug discovery these days. As you read my opinions, though, keep in mind that I've seen several cycles of this over a > 30-year career, so I can't help but be informed (or perhaps misinformed?) by that experience. But not many of us have had thirty years of thinking about the subject of this press release from Novo Nordisk (NVO), which announces their foray into quantum computing.

This part of the blog post is where the background on that concept should go, but I'm manifestly unqualified to deliver it. Broadly put, it's easy enough to define - this is the application to computational methods of the phenomena that can only occur meaningfully down at the quantum level, things like entanglement, superposition, and interference. There's no one thing that encompasses all the possible techniques of quantum computing (as far as I know!) but all of the proposals plan to use these effects to do things that simply can't be accomplished out here in the bulky world. You hear an awful lot of hand-waving talk about that step, stuff about "doing all the computations at once" and so on, and from what I do know about the subject you'd be better off ignoring that. But it does seem certain that quantum-based algorithms exist (or can exist) that would provide remarkable advantages over what can be accomplished classically. You're not breaking out of the Church-Turing thesis, though: anything that a non-quantum computer can accomplish, theoretically, can be accomplished by a quantum one (of whatever sort), and vice versa. But there are opportunities for huge accelerations in how quickly those results can be obtained.

Actually realizing those advantages, though - that's been hard. There was a claim of "quantum supremacy" from Google (GOOG, GOOGL) not too long ago (a result that was obtained far more efficiently than any classical system could have), but not everyone in the field believed that, to put it lightly, and recent results bear out that skepticism. Building the hardware for a working quantum computer is extremely difficult, as is keeping it working once you've built it. And no matter how well you build it, you're going to have to deal with quantum decoherence: the idealized particle-in-a-box of quantum chemistry courses can sit there platonically and not interact with its environment, but that's not what's going out here in the real world, particularly the real world where you'd like to read out the states of all these qubits at the end of the process. You will gradually (or maybe not so gradually) lose the specialness of the quantum states that you have gone to such trouble to obtain, so a big part of any working quantum computer is going to be some really robust error correction techniques.

Another big part of any such system is going to be software that takes maximum advantage of the quantum technology you're using. That's not so simple, either. There are some algorithms that have proven to mesh extremely well with quantum phenomenon (I discussed some of those in this post, which I think is the last time I dove into this topic), but it's safe to say that a lot of effort has been going into identifying more such techniques in the expectation that we're going to have hardware to run them on at some point. And that brings us, at last, to Novo Nordisk!

The press release announces an effort "to establish the first full-scale quantum computer for the development of new medicines", but as you will see if you read on, that's not all. Very quickly we find out that this machine is also expected to provide breakthroughs in the study of climate change and the "green transition". In fact, the whole thing turns into a dump-truck delivery of buzzy phrases. Personalized medicine? Yep! Human microbiome studies? Of course! Large-scale genomics data? Naturally! New sustainable materials, decarbonization, cybersecurity, energy solutions - it's all in there. And to be fair, sure, one could imagine that wildly more capable computational resources could indeed come in handy in all those fields. To the credit of Novo Nordisk and the Danish government, this is a twelve-year initiative, the first seven of which are expected to be spent in just figuring out what sort of quantum computer to build, which seems at least fairly realistic.

But in each case, you're going to run into the same fundamental problem: faster computers are only going to be wonderfully helpful for processes whose rate-limiting stops involve the speed of computation. That might sound obvious or tautological at first, but think about it. This all gets back to the same things that I keep saying about (for example) AlphaFold - that as great an accomplishment as it is, it is not going to lead to an immediate revolution in drug discovery because our biggest problems do not depend on knowledge of protein structure and thus can't really be accelerated by it much. Similarly, having something that can sort through massive mounds of (say) genomics data would be useful - but what would be even more useful is understanding what those results mean and what to do with them. That's a slower process, for sure. Look at that AlphaFold-driven work that I was writing about the other week: if you suddenly gave that team access to a working quantum computer, what would they be able to accomplish with it under present conditions? Generate fairly unreliable docking-and-scoring results much more quickly? What does that buy you? (Please note - I'm not putting down that paper or the people who wrote it at all! If you read it, you can sense their own frustrations with the state of the computational tools that we have now, and I'm sure that just speeding those up would not be the first thing they'd wish for).

So there are, in the end, a number of important choices to be made when you start talking about quantum computing for the life sciences. First off, you have to decide what sort of quantum computational technique you're going to be using. Then you have to decide how to realize that in actual hardware. After that, you have to find algorithms that will take maximum advantage of your new machine. Then you have to very carefully pick the problems for which those algorithms will fit the best, and finally, you will want to narrow down on the problems that have been waiting for just the sorts of results you will now be able to deliver. What we'll be left with after these selection steps will only become obvious with time. And effort. And lots and lots of money.

Disclosure: None

Original Post

Editor's Note: The summary bullets for this article were chosen by Seeking Alpha editors.

This article was written by

3.69K Followers
Derek Lowe, an Arkansan by birth, got his BA from Hendrix College and his PhD in organic chemistry from Duke before spending time in Germany on a Humboldt Fellowship on his post-doc. He's worked for several major pharmaceutical companies since 1989 on drug discovery projects against schizophrenia, Alzheimer's, diabetes, osteoporosis and other diseases. To contact Derek, email him directly: derekb.lowe@gmail.com (mailto:derekb.lowe@gmail.com)

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Content: How big does your quantum computer need to be?

Quantum computers are expected to be disruptive and potentially impact many industry sectors. So researchers in the United Kingdom and the Netherlands decided to explore two very different quantum problems: breaking the encryption of Bitcoin (a digital currency) and simulating the molecule responsible for biological nitrogen fixation.

In AVS Quantum Science, from AIP Publishing, the researchers describe a tool they created to determine how big a quantum computer needs to be to solve problems like these and how long it will take.

“The majority of existing work within this realm focuses on a particular hardware platform, superconducting devices, like those IBM and Google are working toward,” said Mark Webber, of the University of Sussex. “Different hardware platforms will vary greatly on key hardware specifications, such as the rate of operations and the quality of control on the qubits (quantum bits).”

Many of the most promising quantum advantage use cases will require an error-corrected quantum computer. Error correction enables running longer algorithms by compensating for inherent errors inside the quantum computer, but it comes at the cost of more physical qubits.

Pulling nitrogen out of the air to make ammonia for fertilizers is extremely energy-intensive, and improvements to the process could impact both world food scarcity and the climate crisis. Simulation of relevant molecules is currently beyond the abilities of even the world’s fastest supercomputers but should be within the reach of next-gen quantum computers.

“Our tool automates the calculation of the error-correction overhead as a function of key hardware specifications,” Webber said. “To make the quantum algorithm run faster, we can perform more operations in parallel by adding more physical qubits. We introduce extra qubits as needed to reach the desired runtime, which is critically dependent on the rate of operations at the physical hardware level.”

Most quantum computing hardware platforms are limited, because only qubits right next to each other can interact directly. In other platforms, such as some trapped ion designs, the qubits are not in fixed positions and can instead be physically moved around — meaning each qubit can interact directly with a wide set of other qubits.

“We explored how to best take advantage of this ability to connect distant qubits, with the aim of solving problems in less time with fewer qubits,” said Webber. “We must continue to tailor the error-correction strategies to exploit the strengths of the underlying hardware, which may allow us to solve highly impactful problems with a smaller-size quantum computer than had previously been assumed.”

Quantum computers are exponentially more powerful at breaking many encryption techniques than classical computers. The world uses RSA encryption for most of its secure communication. RSA encryption and the one Bitcoin uses (elliptic curve digital signature algorithm) will one day be vulnerable to a quantum computing attack, but today, even the largest supercomputer could never pose a serious threat.

The researchers estimated the size a quantum computer needs to be to break the encryption of the Bitcoin network within the small window of time it would actually pose a threat to do so — in between its announcement and integration into the blockchain. The greater the fee paid on the transaction, the shorter this window will be, but it likely ranges from minutes to hours.

“State-of-the-art quantum computers today only have 50-100 qubits,” said Webber. “Our estimated requirement of 30 [million] to 300 million physical qubits suggests Bitcoin should be considered safe from a quantum attack for now, but devices of this size are generally considered achievable, and future advancements may bring the requirements down further.

“The Bitcoin network could perform a ‘hard-fork’ onto a quantum-secure encryption technique, but this may result in network scaling issues due to an increased memory requirement.”

The researchers emphasize the rate of improvement of both quantum algorithms and error- correction protocols.

“Four years ago, we estimated a trapped ion device would need a billion physical qubits to break RSA encryption, requiring a device with an area of 100-by-100 square meters,” said Webber. “Now, with improvements across the board, this could see a dramatic reduction to an area of just 2.5-by-2.5 square meters.”

A large-scale error-corrected quantum computer should be able to solve important problems classical computers cannot.

“Simulating molecules has applications for energy efficiency, batteries, improved catalysts, new materials, and the development of new medicines,” said Webber. “Further applications exist across the board — including for finance, big data analysis, fluid flow for airplane designs, and logistical optimizations.” The article “The impact of hardware specifications on reaching quantum advantage in the fault tolerant regime” is authored by Mark Webber, Vincent Elfving, Sebastian Weidt, and Winifried K. Hensinger. It will appear in AVS Quantum Science on Jan. 25, 2022 (DOI: 10.1116/5.0073075). After that date, it can be accessed at https://aip.scitation.org/doi/10.1116/5.0073075.

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Title:

Content: Google, IBM and China have already achieved quantum supremacy. Now they face another challenge: the correction of errors

Quantum supremacy is no longer at the center of the debate. It was at the end of 2019 because it came to light that the Google team led by John Martinis had managed to achieve it using its Sycamore quantum processor, and no one had done it until that moment. The noise that this news caused when it broke was justified.

But a year later, in December 2020, the group of Chinese researchers led by Jian-Wei Pan published an article in Science showing that I had also reached using its Zuchongzhi superconducting processor. And a year later, in November 2021, IBM followed suit and announced that it had reached this milestone using its 127-qubit Eagle quantum processor.

At this point no one doubts that quantum computers have come a long way. And, furthermore, they have done it in a real record time if we bear in mind that the first solid theoretical proposals arrived in the mid-1990s. And they are already capable of solving a few problems (very few still). in much less time than the most advanced supercomputers we currently have.

In fact, this is what quantum supremacy consists of: in solving in a short period of time, a few minutes or a few hours, a problem in which a classical supercomputer would spend many years. Even several centuries. Or millennia. Right now it is not too important whether these problems have practical applications or not. Whether or not they are relevant. We are still establishing the foundations of quantum computing, and the important thing is to face the challenges that are around the corner.

In search of higher quality qubits

One of the biggest challenges facing researchers involved in the development of quantum computing is delaying the onset of quantum decoherence. This phenomenon occurs when the necessary conditions for a system that is in an entangled quantum state to be maintained disappear.

Perhaps a slightly simpler way of describing it is to see it as a system that stops behaving as dictated by the rules of quantum mechanics when certain conditions are met, beginning to behave from that moment on as dictated by the rules of classical physics. . When does quantum decoherence appear? quantum effects disappear. And, therefore, also the advantages that they bring in the context of quantum computing.

The time it takes for quantum decoherence to appear is closely linked to the quality of the qubits

This phenomenon is very important because it helps us understand why many macroscopic physical systems do not exhibit quantum effects. Or, what is the same, why in our daily environment we cannot observe the counterintuitive effects of quantum mechanics. In any case, what is really relevant is that as the the quality of the qubits of a quantum processor, the longer it takes for quantum decoherence to appear. And, for this reason, we have more time available to carry out operations with it.

The two qubit fabrication technologies that are currently giving us the best results are superconducting qubits, which benefit greatly from recent advances in silicon lithography, and ion traps. However, some research groups also have other very promising technologies on the table that are worth pursuing, such as neutral atoms or the ions implanted in macromolecules.

IBM already has a 127-qubit superconducting quantum processor, and by the end of 2023 it plans to have Condor ready, a promising quantum chip with no less than 1,121 qubits.

We already brush the correction of errors with the tips of our fingers

The other big challenge facing quantum computing right now is error correction. Quantum computers make errors when carrying out some operations, and when this happens, the results they return to us are not correct, of course. The problem is that implementing a quantum error correction protocol it’s not trivial. And furthermore, if they abound, it is essentially impossible to correct them and simultaneously prevent the quantum processor’s efficiency from sinking.

Fortunately, we have good news. As we told you a few days ago, three independent research groups have managed to perfect superconducting qubits that have an accuracy greater than 99%. This simply means that they make mistakes very infrequently, and the good news is that when they are so infrequent it is easier to correct them. Much easier.

When the incidence of errors is less than 1%, it is much easier for quantum fault-correction protocols to carry out their task

In fact, these research groups ensure that when the incidence of errors is less than 1% quantum fault-correction protocols find it much easier to do their job. At the moment they are working with only one or two qubits, and these quantum processors are too simple to solve significant problems, but if they manage to scale this technology to many more qubits, quantum computers could leave behind one of the biggest challenges they currently face. .

As we have just seen, quantum computing is advancing at a breakneck pace. The entry of private companies in this sector you are greatly accelerating your progress, but before we get carried away with enthusiasm, it is important that we keep in mind that there are other challenges that are also crucial to solve.

Two of the most substantial are the need to control qubits more precisely, and also the importance of implementing new quantum algorithms that they are able to help us tackle the problems that we cannot solve with the most powerful classical supercomputers that we have today. Still, the future for quantum computing is hopeful. And, above all, very promising.

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What are important areas in quantum research?

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What are important areas in quantum research?

What are the challenges in quantum computing research?

What countries and blocs are leading in developing quantum computing?

What are important areas in quantum research?

What are the challenges in quantum computing research?

What countries and blocs are leading in developing quantum computing?

What are important areas in quantum research?

What are the challenges in quantum computing research?

What countries and blocs are leading in developing quantum computing?

What are important areas in quantum research?

What are the challenges in quantum computing research?

What countries and blocs are leading in developing quantum computing?

What are important areas in quantum research?

What are the challenges in quantum computing research?

What countries and blocs are leading in developing quantum computing?

What are important areas in quantum research?

What are the challenges in quantum computing research?

What countries and blocs are leading in developing quantum computing?

The UK government has allocated £2.5 billion for quantum research.

Title:

Content: TIMES ENTERPRISE NETWORK: RISING STARS

Start-up leads charge in widening access to quantum computing

Oxford Quantum Circuits sells access to its supercomputer via Amazon Web Services
new

Dr Ilana Wisby is the chief executive of Europe’s first “quantum computing-as-a-service” company and one of very few women leading start-ups in the field.

Quantum computing is developing rapidly, and global investment in the sector has topped $35.5 billion (£27 million) as industry and governments look to seize on the opportunity it presents. In his most recent budget, Jeremy Hunt unveiled a £2.5 billion funding pot for quantum research, even as he slashed funding for other tech areas.

Quantum computers can operate much faster than conventional computers and perform multiple calculations simultaneously. The technology is still maturing, but in the near future it could solve previously intractable problems, enhance artificial intelligence and transform processes such as drug discovery.

Wisby, 32, who holds a PhD in

What countries and blocs are leading in developing quantum computing?

The US and China dominate the quantum computing sector with significant research investments.

Title:

Content: Monday, 25 March 2024 02: 58 GMT
UAE invests in ‘ quantum computing ’ to look to the future
(MENAFN- Al-Bayan)
The UAE is investing in the sector of quantum computing, which is expected to reach a global market value of $1 trillion in 2035, as one of the fastest expanding fields of technology in the world and because of its innovative applications capable of solving challenges in many sectors, because of its strength and speed in calculating physical phenomena, compared to traditional computers.
The UAE aims to invest in quantum computing to enable innovation and a knowledge and sustainable economy through the Quantum Research Center and UAE institutes and universities to explore the future of this vital sector. The Institute of Technology Innovation ’ s (TII) Quantitative Research Center is working to build the first quantum computer in the UAE, according to the Interregional Center for Strategic Analytics in Abu Dhabi.
The UAE has quickly realized the benefits of the quantum computing sector in all sectors and fields, especially in the economy and scientific research, as part of the country ’ s long-term strategies to keep pace with the global technological development represented by the fourth industrial revolution and artificial intelligence, which will change the face of the world in the coming years.
IDC expects global investments in quantum computing to reach $16.4 billion by the end of 2027, with a compound annual growth rate of 11.5%, which includes investments by the public and private sectors and R & D spending from technology, services and finance companies.
There is growing interest in quantum computing by global government agencies, with 14 of them (13 countries plus the European Union) announcing multi-year initiatives that will generate billions of dollars for quantum computing research.
The center said that the UAE is among the 50 projects working to create an attractive investment environment for investments in new and future sectors, including quantum computing technology.
According to Accenture Middle East, quantum computing technology is advancing rapidly, making it a promising technology sector.
The US and China dominate the quantum computing sector to take advantage of the features of the new technological revolution that has enabled scientists to study the basic particles of matter, whose applications have multiplied across different fields despite their relative novelty, promising radical transformations for any industry dependent on speed and processing power, including aerospace, automotive, medicine and others.
Quantum computing technologies have a huge market value, with quantum computing alone expected to reach a global market value of $1 trillion by 2035.
Quantum technology has played a role in many areas, including complex mathematical models, simulations, electronic devices, CT scanners and many others, as it has the potential to revolutionize the way humans communicate and process information at record speeds.
The most prominent areas of use of quantum computing can be found in many fields of military, communications and medicine, and can address economic crises and challenges quickly, and there is no doubt that quantum computing technology can change the map of national industries.
Major technology companies are leading efforts to develop quantum computing, with Google Research Lab and IBM, which built one of the largest quantum computers in the field, and the Chinese University of Science and Technology has developed a quantum computer that is 10 billion times faster than the computer developed by Google.
Follow the economic statement via Google News
MENAFN24032024000110011019ID1108015991
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This disclaims our responsibility for the privacy practices or content of the sites included in our network, including images and videos.
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IBM and a Chinese university are developing record-breaking quantum computers, one surpassing Google's by 10 billion times.

Title:

Content: Monday, 25 March 2024 02: 58 GMT
UAE invests in ‘ quantum computing ’ to look to the future
(MENAFN- Al-Bayan)
The UAE is investing in the sector of quantum computing, which is expected to reach a global market value of $1 trillion in 2035, as one of the fastest expanding fields of technology in the world and because of its innovative applications capable of solving challenges in many sectors, because of its strength and speed in calculating physical phenomena, compared to traditional computers.
The UAE aims to invest in quantum computing to enable innovation and a knowledge and sustainable economy through the Quantum Research Center and UAE institutes and universities to explore the future of this vital sector. The Institute of Technology Innovation ’ s (TII) Quantitative Research Center is working to build the first quantum computer in the UAE, according to the Interregional Center for Strategic Analytics in Abu Dhabi.
The UAE has quickly realized the benefits of the quantum computing sector in all sectors and fields, especially in the economy and scientific research, as part of the country ’ s long-term strategies to keep pace with the global technological development represented by the fourth industrial revolution and artificial intelligence, which will change the face of the world in the coming years.
IDC expects global investments in quantum computing to reach $16.4 billion by the end of 2027, with a compound annual growth rate of 11.5%, which includes investments by the public and private sectors and R & D spending from technology, services and finance companies.
There is growing interest in quantum computing by global government agencies, with 14 of them (13 countries plus the European Union) announcing multi-year initiatives that will generate billions of dollars for quantum computing research.
The center said that the UAE is among the 50 projects working to create an attractive investment environment for investments in new and future sectors, including quantum computing technology.
According to Accenture Middle East, quantum computing technology is advancing rapidly, making it a promising technology sector.
The US and China dominate the quantum computing sector to take advantage of the features of the new technological revolution that has enabled scientists to study the basic particles of matter, whose applications have multiplied across different fields despite their relative novelty, promising radical transformations for any industry dependent on speed and processing power, including aerospace, automotive, medicine and others.
Quantum computing technologies have a huge market value, with quantum computing alone expected to reach a global market value of $1 trillion by 2035.
Quantum technology has played a role in many areas, including complex mathematical models, simulations, electronic devices, CT scanners and many others, as it has the potential to revolutionize the way humans communicate and process information at record speeds.
The most prominent areas of use of quantum computing can be found in many fields of military, communications and medicine, and can address economic crises and challenges quickly, and there is no doubt that quantum computing technology can change the map of national industries.
Major technology companies are leading efforts to develop quantum computing, with Google Research Lab and IBM, which built one of the largest quantum computers in the field, and the Chinese University of Science and Technology has developed a quantum computer that is 10 billion times faster than the computer developed by Google.
Follow the economic statement via Google News
MENAFN24032024000110011019ID1108015991
Legal Disclaimer:
MENA Financial Services Network provides information "as is" without any representations or warranties...
This disclaims our responsibility for the privacy practices or content of the sites included in our network, including images and videos.
For any queries regarding the use and reuse of this source of information, please contact the provider of the above article.

What are important areas in quantum research?

What companies are leading in developing quantum computing?

What countries and blocs are leading in developing quantum computing?

Quantum computing has various applications, including mathematical models, simulation, electronic devices, and medical imaging.

Title:

Content: Monday, 25 March 2024 02: 58 GMT
UAE invests in ‘ quantum computing ’ to look to the future
(MENAFN- Al-Bayan)
The UAE is investing in the sector of quantum computing, which is expected to reach a global market value of $1 trillion in 2035, as one of the fastest expanding fields of technology in the world and because of its innovative applications capable of solving challenges in many sectors, because of its strength and speed in calculating physical phenomena, compared to traditional computers.
The UAE aims to invest in quantum computing to enable innovation and a knowledge and sustainable economy through the Quantum Research Center and UAE institutes and universities to explore the future of this vital sector. The Institute of Technology Innovation ’ s (TII) Quantitative Research Center is working to build the first quantum computer in the UAE, according to the Interregional Center for Strategic Analytics in Abu Dhabi.
The UAE has quickly realized the benefits of the quantum computing sector in all sectors and fields, especially in the economy and scientific research, as part of the country ’ s long-term strategies to keep pace with the global technological development represented by the fourth industrial revolution and artificial intelligence, which will change the face of the world in the coming years.
IDC expects global investments in quantum computing to reach $16.4 billion by the end of 2027, with a compound annual growth rate of 11.5%, which includes investments by the public and private sectors and R & D spending from technology, services and finance companies.
There is growing interest in quantum computing by global government agencies, with 14 of them (13 countries plus the European Union) announcing multi-year initiatives that will generate billions of dollars for quantum computing research.
The center said that the UAE is among the 50 projects working to create an attractive investment environment for investments in new and future sectors, including quantum computing technology.
According to Accenture Middle East, quantum computing technology is advancing rapidly, making it a promising technology sector.
The US and China dominate the quantum computing sector to take advantage of the features of the new technological revolution that has enabled scientists to study the basic particles of matter, whose applications have multiplied across different fields despite their relative novelty, promising radical transformations for any industry dependent on speed and processing power, including aerospace, automotive, medicine and others.
Quantum computing technologies have a huge market value, with quantum computing alone expected to reach a global market value of $1 trillion by 2035.
Quantum technology has played a role in many areas, including complex mathematical models, simulations, electronic devices, CT scanners and many others, as it has the potential to revolutionize the way humans communicate and process information at record speeds.
The most prominent areas of use of quantum computing can be found in many fields of military, communications and medicine, and can address economic crises and challenges quickly, and there is no doubt that quantum computing technology can change the map of national industries.
Major technology companies are leading efforts to develop quantum computing, with Google Research Lab and IBM, which built one of the largest quantum computers in the field, and the Chinese University of Science and Technology has developed a quantum computer that is 10 billion times faster than the computer developed by Google.
Follow the economic statement via Google News
MENAFN24032024000110011019ID1108015991
Legal Disclaimer:
MENA Financial Services Network provides information "as is" without any representations or warranties...
This disclaims our responsibility for the privacy practices or content of the sites included in our network, including images and videos.
For any queries regarding the use and reuse of this source of information, please contact the provider of the above article.

What advantages do quantum computers have over conventional computers?

The global quantum computing market is expected to grow from $472m in 2021 to $1.77bn by 2026 at a 30.2% compound annual growth rate.

Adoption of quantum computing by financial services companies is expected to drive market growth.

What fields can quantum computers advance?

Big Tech companies like Microsoft, Amazon, IBM, and Google offer cloud services for quantum simulator experimentation.

What companies are leading in developing quantum computing?

IBM's quantum accelerator programme helps businesses find quantum computing use cases, amid financial services concerns over cryptography.

What companies are leading in developing quantum computing?

What fields can quantum computers advance?

By 2025, 40% of large companies plan to launch quantum computing initiatives, says Gartner.

Quantum computing can greatly increase calculation and transaction speed and volume, representing a significant change for the financial services sector.

What advantages do quantum computers have over conventional computers?

extremely fast calculations
extremely complex calculations

What fields can quantum computers advance?

Quantum computing development requires collaboration between academia, industry, and government, with countries like China, the US, and the EU investing heavily.

Title:

Content: Terra Quantum announces hybrid quantum computing collaboration with NVIDIA

Terra Quantum collaborates with NVIDIA to develop quantum-accelerated applications. The partnership aims to bridge the gap between classical and quantum computing, leveraging hybrid algorithms.

Terra Quantum, a quantum services company with headquarters in Germany and Switzerland, has today announced a collaboration with NVIDIA aimed at fostering the development of quantum-accelerated applications.

The chicken and egg conundrum

As the manufacturers of quantum computers and error correction mechanisms continue to compete in a qubit arms race, in order to do the algorithm research needed to develop applications that can leverage this technology, scientists need a solution to bridge the divide between classical and quantum computing. A chicken and egg conundrum that Terra Quantum has been working on since 2019 with its hybrid algorithm approach.

Focusing on harnessing the power of quantum computing, both hybrid now and native in the future, and applying it specifically in the fields optimisation, simulation, and machine learning, the Swiss/German outfit has assembled, in the words of its founder and CEO Markus Pflitsch, “one of the largest libraries in the world” of algorithms designed to not only deliver unprecedented accelerated computing solutions using today’s hybrid computational power but ones that will scale exponentially when native quantum hardware is realised.

The quantum inflection point

There is no arguing that NVIDIA has been instrumental, if not the linchpin in driving the explosion of AI technologies that proliferate today’s headlines.

The company is so crucial to the development of next-gen technologies that world governments have butted heads on who has dibs on the company’s next purchase orders.

And now, according to Pflitsch, we’re about to see the same revolution in quantum computing.

Driven by NVIDIA’s open-source CUDA Quantum initiative, a project that allows for the integration and programming of quantum processing units (QPU), graphics processing units (GPU), and central processing units (CPU) all in one system, the chicken and egg conundrum has seemingly met its match.

C-suite proof

While we’ve seen governments pour tremendous amounts of money into quantum, China $9.7 billion, the United States $1.9 billion, and the European Union $1.1 billion, government support can and will only take the market so far.

To fully realise and advance the potential of a technology, c-suite executives have to see the bottom line in dollars and cents. Helping to move this needle Terra Quantum has partnerships with a number of blue chip organisations including HSBC, Thales, and Schaeffler Group.

Now in collaboration with NVIDIA providing its CUDA Quantum participants with access to Terra Quantum’s library of algorithms, that needle is set to jump.

Pflitsch shared:

“We are using our hybrid quantum algorithms delivered on NVIDIA GPUs to deliver significant business impact today. This collaboration will not only accelerate this impact but also help unlock  a whole new range of opportunities in the areas of machine learning and simulation — while also setting a pathway for quantum computing.”

Furthermore, NVIDIA’s director of HPC and Quantum Tim Costa explained:

“Our collaboration with Terra Quantum will put CUDA Quantum into the hands of a new set of  researchers working to build the world’s first quantum accelerated applications, contributing to breakthroughs on the path to valuable quantum computing.”

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The National Quantum Mission aims to develop intermediate-scale quantum computers with 50-1,000 physical qubits using technologies like superconducting and photonic systems.

Title:

Content: Satyam Priyadarshy

Rajesh Mehta

Governments, venture capitalists, and private companies have invested billions of dollars in quantum computing in the last 10 years. Recently, at the Puzzle X conference held in Barcelona, it was evident that Europe is preparing to take on the leadership role to push the boundaries of quantum computing ecosystem. So, what is quantum computing?

Bits to Qubits

In simple words, quantum computing combines the fields of quantum mechanics and computer science. It moves us beyond Bits to Qubits. In traditional computer science, the information is stored and manipulated using bits that have two discrete states, 0 and 1, while in the quantum computing world, Qubits can represent both states at the same time, thus allowing for a high degree of parallelism, enabling by phenomena of “interference, superposition, and entanglement.”

Such parallelism allows quantum computers to tackle computational challenges that become a limiting factor for traditional computers.

Wide applications

Many companies in the quantum computing field are engaged in solving complex problems that could significantly impact the fields of drug development, material design, energy transition, finance, security, and defense.

All nations must address various aspects of the quantum computing ecosystem sooner than later due to China’s quantum computing activities.

The National Quantum Mission (NQM) was approved by Prime Minister Narendra Modi, on April 19, 2023.

With a budget of ₹6,003 crore over eight years, it aims to create, develop, and nurture the quantum technology ecosystem in the country.

The goal of the mission is to develop intermediate-scale quantum computers with 50-1,000 physical qubits in various platforms like superconducting and photonic technology. Satellite-based secure quantum communications between ground stations over a range of 2,000 km within India, long-distance secure quantum communications with other countries, inter-city quantum key distribution over 2,000 km, as well as multi-node quantum networks with quantum memories, are among the other deliverables. The technology is expected to break ground in communications, cryptography, intelligence, fossil fuel exploration, space research, and drug design.

As we step into 2024, an increased set of activities to solve complex challenges will be addressed by combining the tools of Artificial Intelligence and Quantum computing.

Priyadarshy is a pioneer in the fields of Quantum Mechanics, Data Science, Big Data and Emerging Technologies; Mehta is an International Consultant in the field of Market Entry, Innovation and Public Policy

COMMENT NOW

What are important areas in quantum research?

new types of qubits
implementations of quantum processors

Quantum computing combines quantum mechanics and computer science, using qubits instead of traditional bits.

Title:

Content: Satyam Priyadarshy

Rajesh Mehta

Governments, venture capitalists, and private companies have invested billions of dollars in quantum computing in the last 10 years. Recently, at the Puzzle X conference held in Barcelona, it was evident that Europe is preparing to take on the leadership role to push the boundaries of quantum computing ecosystem. So, what is quantum computing?

Bits to Qubits

In simple words, quantum computing combines the fields of quantum mechanics and computer science. It moves us beyond Bits to Qubits. In traditional computer science, the information is stored and manipulated using bits that have two discrete states, 0 and 1, while in the quantum computing world, Qubits can represent both states at the same time, thus allowing for a high degree of parallelism, enabling by phenomena of “interference, superposition, and entanglement.”

Such parallelism allows quantum computers to tackle computational challenges that become a limiting factor for traditional computers.

Wide applications

Many companies in the quantum computing field are engaged in solving complex problems that could significantly impact the fields of drug development, material design, energy transition, finance, security, and defense.

All nations must address various aspects of the quantum computing ecosystem sooner than later due to China’s quantum computing activities.

The National Quantum Mission (NQM) was approved by Prime Minister Narendra Modi, on April 19, 2023.

With a budget of ₹6,003 crore over eight years, it aims to create, develop, and nurture the quantum technology ecosystem in the country.

The goal of the mission is to develop intermediate-scale quantum computers with 50-1,000 physical qubits in various platforms like superconducting and photonic technology. Satellite-based secure quantum communications between ground stations over a range of 2,000 km within India, long-distance secure quantum communications with other countries, inter-city quantum key distribution over 2,000 km, as well as multi-node quantum networks with quantum memories, are among the other deliverables. The technology is expected to break ground in communications, cryptography, intelligence, fossil fuel exploration, space research, and drug design.

As we step into 2024, an increased set of activities to solve complex challenges will be addressed by combining the tools of Artificial Intelligence and Quantum computing.

Priyadarshy is a pioneer in the fields of Quantum Mechanics, Data Science, Big Data and Emerging Technologies; Mehta is an International Consultant in the field of Market Entry, Innovation and Public Policy

COMMENT NOW

Qubits can represent both 0 and 1 states simultaneously through superposition, enabling parallelism.

Title:

Content: Satyam Priyadarshy

Rajesh Mehta

Governments, venture capitalists, and private companies have invested billions of dollars in quantum computing in the last 10 years. Recently, at the Puzzle X conference held in Barcelona, it was evident that Europe is preparing to take on the leadership role to push the boundaries of quantum computing ecosystem. So, what is quantum computing?

Bits to Qubits

In simple words, quantum computing combines the fields of quantum mechanics and computer science. It moves us beyond Bits to Qubits. In traditional computer science, the information is stored and manipulated using bits that have two discrete states, 0 and 1, while in the quantum computing world, Qubits can represent both states at the same time, thus allowing for a high degree of parallelism, enabling by phenomena of “interference, superposition, and entanglement.”

Such parallelism allows quantum computers to tackle computational challenges that become a limiting factor for traditional computers.

Wide applications

Many companies in the quantum computing field are engaged in solving complex problems that could significantly impact the fields of drug development, material design, energy transition, finance, security, and defense.

All nations must address various aspects of the quantum computing ecosystem sooner than later due to China’s quantum computing activities.

The National Quantum Mission (NQM) was approved by Prime Minister Narendra Modi, on April 19, 2023.

With a budget of ₹6,003 crore over eight years, it aims to create, develop, and nurture the quantum technology ecosystem in the country.

The goal of the mission is to develop intermediate-scale quantum computers with 50-1,000 physical qubits in various platforms like superconducting and photonic technology. Satellite-based secure quantum communications between ground stations over a range of 2,000 km within India, long-distance secure quantum communications with other countries, inter-city quantum key distribution over 2,000 km, as well as multi-node quantum networks with quantum memories, are among the other deliverables. The technology is expected to break ground in communications, cryptography, intelligence, fossil fuel exploration, space research, and drug design.

As we step into 2024, an increased set of activities to solve complex challenges will be addressed by combining the tools of Artificial Intelligence and Quantum computing.

Priyadarshy is a pioneer in the fields of Quantum Mechanics, Data Science, Big Data and Emerging Technologies; Mehta is an International Consultant in the field of Market Entry, Innovation and Public Policy

COMMENT NOW

Quantum computers can tackle challenges limiting traditional computers.

Title:

Content: Satyam Priyadarshy

Rajesh Mehta

Governments, venture capitalists, and private companies have invested billions of dollars in quantum computing in the last 10 years. Recently, at the Puzzle X conference held in Barcelona, it was evident that Europe is preparing to take on the leadership role to push the boundaries of quantum computing ecosystem. So, what is quantum computing?

Bits to Qubits

In simple words, quantum computing combines the fields of quantum mechanics and computer science. It moves us beyond Bits to Qubits. In traditional computer science, the information is stored and manipulated using bits that have two discrete states, 0 and 1, while in the quantum computing world, Qubits can represent both states at the same time, thus allowing for a high degree of parallelism, enabling by phenomena of “interference, superposition, and entanglement.”

Such parallelism allows quantum computers to tackle computational challenges that become a limiting factor for traditional computers.

Wide applications

Many companies in the quantum computing field are engaged in solving complex problems that could significantly impact the fields of drug development, material design, energy transition, finance, security, and defense.

All nations must address various aspects of the quantum computing ecosystem sooner than later due to China’s quantum computing activities.

The National Quantum Mission (NQM) was approved by Prime Minister Narendra Modi, on April 19, 2023.

With a budget of ₹6,003 crore over eight years, it aims to create, develop, and nurture the quantum technology ecosystem in the country.

The goal of the mission is to develop intermediate-scale quantum computers with 50-1,000 physical qubits in various platforms like superconducting and photonic technology. Satellite-based secure quantum communications between ground stations over a range of 2,000 km within India, long-distance secure quantum communications with other countries, inter-city quantum key distribution over 2,000 km, as well as multi-node quantum networks with quantum memories, are among the other deliverables. The technology is expected to break ground in communications, cryptography, intelligence, fossil fuel exploration, space research, and drug design.

As we step into 2024, an increased set of activities to solve complex challenges will be addressed by combining the tools of Artificial Intelligence and Quantum computing.

Priyadarshy is a pioneer in the fields of Quantum Mechanics, Data Science, Big Data and Emerging Technologies; Mehta is an International Consultant in the field of Market Entry, Innovation and Public Policy

COMMENT NOW

What advantages do quantum computers have over conventional computers?

extremely fast calculations
extremely complex calculations

What are important areas in quantum research?

What fields can quantum computers advance?

Quantum computing has wide applications in fields like drug development, finance, security, and defense.

Title:

Content: Satyam Priyadarshy

Rajesh Mehta

Governments, venture capitalists, and private companies have invested billions of dollars in quantum computing in the last 10 years. Recently, at the Puzzle X conference held in Barcelona, it was evident that Europe is preparing to take on the leadership role to push the boundaries of quantum computing ecosystem. So, what is quantum computing?

Bits to Qubits

In simple words, quantum computing combines the fields of quantum mechanics and computer science. It moves us beyond Bits to Qubits. In traditional computer science, the information is stored and manipulated using bits that have two discrete states, 0 and 1, while in the quantum computing world, Qubits can represent both states at the same time, thus allowing for a high degree of parallelism, enabling by phenomena of “interference, superposition, and entanglement.”

Such parallelism allows quantum computers to tackle computational challenges that become a limiting factor for traditional computers.

Wide applications

Many companies in the quantum computing field are engaged in solving complex problems that could significantly impact the fields of drug development, material design, energy transition, finance, security, and defense.

All nations must address various aspects of the quantum computing ecosystem sooner than later due to China’s quantum computing activities.

The National Quantum Mission (NQM) was approved by Prime Minister Narendra Modi, on April 19, 2023.

With a budget of ₹6,003 crore over eight years, it aims to create, develop, and nurture the quantum technology ecosystem in the country.

The goal of the mission is to develop intermediate-scale quantum computers with 50-1,000 physical qubits in various platforms like superconducting and photonic technology. Satellite-based secure quantum communications between ground stations over a range of 2,000 km within India, long-distance secure quantum communications with other countries, inter-city quantum key distribution over 2,000 km, as well as multi-node quantum networks with quantum memories, are among the other deliverables. The technology is expected to break ground in communications, cryptography, intelligence, fossil fuel exploration, space research, and drug design.

As we step into 2024, an increased set of activities to solve complex challenges will be addressed by combining the tools of Artificial Intelligence and Quantum computing.

Priyadarshy is a pioneer in the fields of Quantum Mechanics, Data Science, Big Data and Emerging Technologies; Mehta is an International Consultant in the field of Market Entry, Innovation and Public Policy

COMMENT NOW

What advantages do quantum computers have over conventional computers?

What fields can quantum computers advance?

China, the US, and the EU have invested $9.7 billion, $1.9 billion, and $1.1 billion, respectively, in quantum computing.

Title:

Content: Terra Quantum announces hybrid quantum computing collaboration with NVIDIA

Terra Quantum collaborates with NVIDIA to develop quantum-accelerated applications. The partnership aims to bridge the gap between classical and quantum computing, leveraging hybrid algorithms.

Terra Quantum, a quantum services company with headquarters in Germany and Switzerland, has today announced a collaboration with NVIDIA aimed at fostering the development of quantum-accelerated applications.

The chicken and egg conundrum

As the manufacturers of quantum computers and error correction mechanisms continue to compete in a qubit arms race, in order to do the algorithm research needed to develop applications that can leverage this technology, scientists need a solution to bridge the divide between classical and quantum computing. A chicken and egg conundrum that Terra Quantum has been working on since 2019 with its hybrid algorithm approach.

Focusing on harnessing the power of quantum computing, both hybrid now and native in the future, and applying it specifically in the fields optimisation, simulation, and machine learning, the Swiss/German outfit has assembled, in the words of its founder and CEO Markus Pflitsch, “one of the largest libraries in the world” of algorithms designed to not only deliver unprecedented accelerated computing solutions using today’s hybrid computational power but ones that will scale exponentially when native quantum hardware is realised.

The quantum inflection point

There is no arguing that NVIDIA has been instrumental, if not the linchpin in driving the explosion of AI technologies that proliferate today’s headlines.

The company is so crucial to the development of next-gen technologies that world governments have butted heads on who has dibs on the company’s next purchase orders.

And now, according to Pflitsch, we’re about to see the same revolution in quantum computing.

Driven by NVIDIA’s open-source CUDA Quantum initiative, a project that allows for the integration and programming of quantum processing units (QPU), graphics processing units (GPU), and central processing units (CPU) all in one system, the chicken and egg conundrum has seemingly met its match.

C-suite proof

While we’ve seen governments pour tremendous amounts of money into quantum, China $9.7 billion, the United States $1.9 billion, and the European Union $1.1 billion, government support can and will only take the market so far.

To fully realise and advance the potential of a technology, c-suite executives have to see the bottom line in dollars and cents. Helping to move this needle Terra Quantum has partnerships with a number of blue chip organisations including HSBC, Thales, and Schaeffler Group.

Now in collaboration with NVIDIA providing its CUDA Quantum participants with access to Terra Quantum’s library of algorithms, that needle is set to jump.

Pflitsch shared:

“We are using our hybrid quantum algorithms delivered on NVIDIA GPUs to deliver significant business impact today. This collaboration will not only accelerate this impact but also help unlock  a whole new range of opportunities in the areas of machine learning and simulation — while also setting a pathway for quantum computing.”

Furthermore, NVIDIA’s director of HPC and Quantum Tim Costa explained:

“Our collaboration with Terra Quantum will put CUDA Quantum into the hands of a new set of  researchers working to build the world’s first quantum accelerated applications, contributing to breakthroughs on the path to valuable quantum computing.”

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What countries and blocs are leading in developing quantum computing?

Quantum algorithms can significantly reduce the time required to solve complex problems, making some currently unsolvable problems solvable.

Title:

Content: Quantum computing expert Ilana Wisby explains how next-generation processing power can help operators revolutionize network management by significantly reducing the time required for complex computing.
The CEO and founder of Oxford Quantum Circuits (pictured) said in a keynote speech that the core rules of quantum entanglement can be used to form the basics of algorithms covering optimization, machine learning and simulation, helping to shorten the time needed to solve various problems.
Algorithms can provide solutions that are “impossible in today ’ s concept ”“ in an instant ” rather than thousands of years.
Using the puzzle of calculating how many cities a traveling salesperson can go to in the shortest amount of time, Wisby explains that while this is “somewhat solvable, ” at some point it will take“ longer than the total time known to the universe. ”
In the quantum state, the algorithm can "effectively encode this to an optimized problem", is a solvable problem, and can "significantly shorten the computation time".
Of course, Wisby believes that quantum computing can bring a wide range of benefits to society, but he also stresses that the challenges surrounding security and ethics remain prominent.

What advantages do quantum computers have over conventional computers?

extremely fast calculations
extremely complex calculations

Researchers in Japan have developed an algorithm to accelerate a specific quantum computing workload.

Title:

Content: New Technology ｜ Major Breakthroughs in Quantum Computing, Performance Improves, Cost Reduces, and Approaches to Practical Application
Author: Zhongguancun Online
Published: Updated:
Of all the common rebuttals in the computer (computer) world, the phrase “if only software could catch up with the hardware ” might rank high.
However, software does catch up with hardware sometimes.
In fact, this time, the software seems to be able to achieve the point of unlocking quantum computing for classical computers.
This is what researchers at the Center for Quantum Computing at the Institute of Physics and Chemistry in Japan say, and they have published an algorithm that greatly accelerates a specific quantum computing workload.
What ’ s more, the workload itself — called the time evolution operator — has applications in condensed matter physics and quantum chemistry, two fields that can unlock new worlds in our own.
Typically, an improved algorithm won ’ t completely break away from the norm; after all, updates are everywhere.
Every application update, software update, or firmware upgrade basically brings revised code that either solves the problem or improves performance (hopefully).
The improved algorithm is good, and anyone with an AMD or NVIDIA graphics card can attest to that.
But let ’ s face it: we ’ re used to being disappointed with performance upgrades.
+ 12
However, in this case, the performance improvement is extraordinary.
Really, the results could hardly have been more impressive.
With improved algorithms (which are themselves a hybrid of quantum and classical methods), future quantum computers can be simpler than we thought: they will be able to handle bigger problems faster than we expected, and at a lower cost.
However, the increase in performance is not limited to this.
They can make it possible for conventional machines to deal with problems of a level of complexity that only quantum computers are said to be able to solve.
Kaoru Mizuta of the Center for Quantum Computing at the Institute of Physics and Chemistry explains: “The time-evolution operator is a huge mesh that describes the complex behavior of quantum materials.
They are very important because they give quantum computers a very practical application -- a better understanding of quantum chemistry and solid physics. "
Extended reading: Science and technology, scientists achieve a breakthrough, robots can change the shape of liquefaction and then restore the original shape.
+ 38
【 This article is reproduced with permission from Zhongguancun Online. 】

What advantages do quantum computers have over conventional computers?

What are important areas in quantum research?

development of high-level software
implementations of quantum processors

Quantum algorithms and software ecosystems are being researched for potential applications in finance, climate, and logistics.

What are important areas in quantum research?

What fields can quantum computers advance?

logistics
climate change solutions
finance

Quantum programming languages facilitate quantum information processing, enabling advancements in cryptography, optimization, and simulation.

Title:

Content: Grow with AppMaster.
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Quantum programming
Quantum programming is an emerging field in the field of computer programming that focuses on the development of algorithms and software for quantum computers.
To harness the unparalleled computational power of quantum computing systems, quantum programming combines the principles of quantum mechanics, linear algebra, and computer science to solve complex problems that are beyond the reach of classical computing architectures.
Quantum programming languages and frameworks are designed to handle qubits and facilitate the processing of quantum information, enabling revolutionary advances in areas such as cryptography, optimization, and simulation.
Unlike classical bits, which can be either 0 or 1, quantum bits can exist in multiple states simultaneously due to a phenomenon known as superposition.
This property, along with entanglement, which allows correlation between qubits in discrete quantum states, enables quantum computers to simultaneously process vast amounts of data and perform a large number of calculations in parallel.
As a result, quantum programming has the potential to radically transform many industries, from pharmaceuticals and finance to artificial intelligence and cybersecurity.
In the context of programming models, quantum programming represents a distinct shift from classical deterministic and probability methods.
While traditional programming languages are designed for classical computers with binary logic gates, quantum programming languages use quantum logic gates and quantum circuits to manipulate qubit states and perform quantum operations.
These specialized languages are designed to exploit the unique characteristics of quantum computing, thus enabling developers to encrypt quantum algorithms more naturally and effectively.
Some notable examples of quantum programming languages and frameworks include Q # (a specific domain language from Microsoft), Qiskit (IBM ’ s Open Source Quantum Software Development Group), and Cirq (Google ’ s Open Source Python Framework).
These tools have been developed to facilitate the creation of quantum software that can run on both simulators and actual quantum devices, allowing programmers and researchers to explore and refine quantum algorithms without needing a deep understanding of fundamental physics.
The advent of quantum programming has also led to the emergence of classical quantum hybrid approaches, where classical and quantum computing resources are combined to solve specific problems.
A notable example is the Quantitative Approximate Optimization (QAOA) algorithm, which involves running iterative optimizations on a quantum processor followed by evaluation and modification on a classical processor.
This technology can efficiently address harmonic optimization issues, which are commonly encountered in real-world applications such as scheduling and resource allocation.
At AppMaster ’ s no-code platform, we recognize the growing importance of quantum programming in shaping the future of software development, and strive to keep ourselves abreast of relevant developments and innovations.
Although the platform currently focuses on creating traditional classic software applications, our expertise in various programming models enables us to be at the forefront of cutting-edge technologies, ensuring that our customers always have access to industry-leading solutions and services.
To help users better understand the complex field of quantum programming, extensive resources, manuals and documentation are available from academic and industry sources.
Research organizations, such as the Institute of Electrical and Electronics Engineers (IEEE) and the Association for Computing Machinery (ACM), regularly publish research papers and host conferences related to quantum programming.
Moreover, many online courses and tutorials cater to beginners and experienced developers alike, equipping them with the knowledge and skills to harness the power of quantum computing.
In short, quantum programming is a rapidly evolving field that seeks to unlock the extraordinary potential of quantum computing through the development of algorithms, languages, and software designed for quantum computers.
As a relatively nascent field, quantum programming still faces technical challenges and even ethical concerns.
However, its promise to revolutionize industries and deliver unprecedented computational capabilities ensures that it will remain an increasingly integral part of the programming landscape.
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What are important areas in quantum research?

What fields can quantum computers advance?

The Finnish government believes building a quantum computer will prepare them for its adoption in various industries, including healthcare, finance, and security.

Title:

Content: Finland has big plans for quantum computing applications

The QuTI project will develop new components, manufacturing and testing solutions, and algorithms for the needs of quantum computing applications.
25 January 2022

Quantum computing applications are expected to be adopted by more industries this year as organizations around the world begin testing the use cases for the technology. While organizations are the ones most looking forward to making the most of the technology, a few governments are also hoping quantum computing applications can improve their services.

In Finland, their first-ever quantum computer was commissioned at a research center near the capital. Scientists are expected to use it to study next-generation computing power. The 5 quantum-bit computers were developed to learn how to build a quantum computer, how to program one, and how to operate one in the future.

The state-owned VTT Technical Research Center (VTT) plays a crucial role in ensuring researchers learn in a range of scientific domains and making quantum computing applications ready for the industry. According to a report by Computer Weekly, the Finnish government believes that the best way to be ready for the quantum computing industry is to build a working quantum computer.

Computer Weekly also highlights five areas for quantum computing applications. They are in drug and materials discovery, supply chain and logistics, financial services, artificial intelligence, and cloud security.

For drug and materials discovery, Computer Weekly reports that a separate team in VTT which is the quantum algorithm team is developing algorithms to be used on the quantum computer. They are looking at two broad types of quantum computing applications. The first is to solve complex optimization problems that exist in many industries. This includes energy distribution, process control, and fleet management. The second is to predict the structures and properties of molecular formations more accurately and effectively. This will help accelerate drug discovery and the development of new materials.

While other countries are also developing quantum computer ecosystems, with the majority focusing on topics and platforms. Tech vendors like IBM and Google, who are also developing quantum use cases are not government-linked or owned and are mostly testing industry use cases.

Compared to the rest of the world, Finnish researchers focus almost exclusively on the superconducting qubit approach, which they have been using for years and know very well. In fact, a new research project has just been launched to accelerate the progress of Finnish quantum technology.

The QuTI project, coordinated by VTT, will develop new components, manufacturing and testing solutions, and algorithms for the needs of quantum technology. The QuTI consortium, partly financed by Business Finland, consists of 12 partners and has a total budget of around EUR 10 million.

For Professor Mika Prunnila, QuTI project’s coordinator, from VT, “Quantum technology is a multidisciplinary and rapidly advancing field. The QuTI consortium provides an ideal starting point for strengthening the international competitiveness of Finnish technology and industry in this fast-growing field.”

The quantum computing, communication and sensing devices to be developed in the QuTI project are largely based on expertise in microsystems, photonics, electronics, and cryogenics. The project develops customized software and algorithms hand in hand with the hardware, strengthening the Finnish quantum computing infrastructure. In addition, new tools will be created for quantum technology product development that will serve the needs of the QuTI project as well as the entire field of quantum technology.

As China and the US continue to battle each other for quantum computing supremacy, Finland is definitely building their presence in the industry as well. With the government supporting quantum computing initiatives, Finland might just have a quantum computing ecosystem on the horizon.

What countries and blocs are leading in developing quantum computing?

What fields can quantum computers advance?

Novo Nordisk is launching a 12-year initiative to develop a full-scale quantum computer for medicine and other applications.

What are important areas in quantum research?

What fields can quantum computers advance?

Scientists have developed a quantum algorithm to identify promising compounds for carbon sequestration, aiding the fight against climate change.

Title:

Content: HomeTech NewsQuantum computing algorithm to capture carbon and save the planet

Quantum computing algorithm to capture carbon and save the planet

Published on

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The fight against climate change is at a critical stage, but many studies are being carried out to turn the tables.

One of the most promising solutions is atmospheric carbon capture. In fact, a team of scientists recently developed a quantum computing algorithm that could revolutionize this process. In this article, we will explore how this algorithm could change the way we approach the problem of climate change.

Carbon sequestration and its importance

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Atmospheric carbon capture is a promising tool to combat climate change. The technology is in an early stage of development, and much work is still needed to make it capable of capturing the large amounts of CO2 required. One of the most promising versions uses compounds called amines that chemically bond with carbon dioxide.

It is necessary to identify the best amines for carbon sequestration, since the efficiency of the technology depends on small variations in the structure of the amines.

Quantum computing and innovative algorithm

A team of scientists has developed an algorithm that uses quantum computing to analyze amine reactions and find the most promising compounds for carbon sequestration.

Quantum computing makes it possible to simulate interactions between atoms, and this algorithm can quickly identify the most efficient amines for carbon capture.

Impact on the fight against climate change

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The quantum computing algorithm could have a significant impact in the fight against climate change. By quickly identifying the most efficient amines for carbon sequestration, billions of additional tons of CO2 could be captured. This would help reduce the concentration of greenhouse gases in the atmosphere, reducing global warming.

Challenges and future of technology

Despite their potential, both quantum computing and carbon capture face challenges. Quantum computing is still in an early stage of development, and researchers must work within the limitations of current systems.

However, scientists are optimistic about the future of quantum computing and its application in carbon capture. As technology advances, it is expected that the algorithm will become more accurate and efficient, which will allow more and more effective compounds to be identified for carbon sequestration.

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Now work is being done on three fronts:

  • Advances in quantum computing technology
  • Increased accuracy and efficiency in compound identification
  • Development of more effective solutions for carbon capture

Undoubtedly, the algorithm has great potential in the fight against climate change. While it faces challenges, such as the current limitations of quantum computing, its impact could be significant in identifying the most efficient compounds for carbon capture. In the future, this technology could contribute to reducing the concentration of greenhouse gases in the atmosphere and combat global warming, and that is worth all the effort that can be put in around the world.

More information at www.eurekalert.org.

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What fields can quantum computers advance?

Quantum error correction maintains quantum information for a longer period than uncorrected hardware components.

Title:

Content: Doubling a qubit’s life, Yale scientists prove a key theory of quantum physics

Researchers at Yale have for the first time, using a process known as quantum error correction, substantially extended the lifetime of a quantum bit — a long-sought-after goal and one of the trickiest challenges in the field of quantum physics.

Led by Yale’s Michel Devoret, the experiment proves — decades after its theoretical foundations were proposed — that quantum error correction works in practice.

Quantum error correction is a process designed to keep quantum information intact for a period of time longer than if the same information were stored in hardware components without any correction.

The results were published March 21 in Nature.

Information in classical computing comes in the form of bits corresponding to ones or zeros. In quantum computing, information is stored in special devices with quantum properties that are known as quantum bits, or “qubits.”

In the lab of Devoret, the Frederick W. Beinecke Professor of Applied Physics, these qubits are constructed with superconducting circuits cooled to temperatures 100 times lower than those in outer space.

The qubits can each represent a one or a zero, or — confoundingly — both one and zero at the same time.

This “quantum parallelism” is one of the properties that enables quantum computers to make calculations that will potentially be orders of magnitude faster than what is possible on classical supercomputers and transform multiple industries.

Quantum systems, though, are fragile. They are bedeviled by a fundamental phenomenon of decoherence, a process in which the information stored in qubits quickly loses its quantum properties as a result of their interactions with the surrounding environment.

Quantum error correction, which was theoretically discovered in 1995, offers a means to combat this decoherence. Employing redundancy, it protects the quantum bit of information by encoding it in a system larger than what, in principle, is needed to represent a single qubit.

This larger system, however, makes the effect of the surrounding environment even more invasive and the encoded qubit even more fragile. Because of this effect, and complications from the additional components required to perform error correction, this process had never been able to definitively extend the lifetime of a quantum bit in practice.

In fact, just breaking even with an uncorrected qubit is a rare event, researchers say. Contrary to theoretical promises, in most experiments, error correction accelerates the decoherence of quantum information.

“For the first time, we have shown that making the system more redundant and actively detecting and correcting quantum errors provided a gain in the resilience of quantum information,” Devoret said. “Our experiment shows that quantum error correction is a real practical tool. It’s more than just a proof-of-principle demonstration.”

Devoret’s group has managed to more than double the lifetime of quantum information. Their error-corrected qubit lived for 1.8 milliseconds — things happen fast in the quantum realm.

They achieved their results using an error-correction code that was invented in 2001. “It gives you a sense of the delay between the theoretical proposals and practical realization of them in our field,” Devoret said.

Volodymyr Sivak, the lead author of the paper, said that this performance was achieved in part by employing a machine-learning agent that tweaked the error correction process to improve the outcome.

“There is no single breakthrough that enabled this result,” said Sivak, a former Ph.D.  student in Devoret’s lab and now a research scientist at Google. “It’s actually a combination of a whole bunch of different technologies that were developed in the past few years, which we combined in this experiment.”

The practical success of quantum computing will hinge on being able to create quantum bits of extremely high quality using quantum error correction. “Our experiment validates a cornerstone assumption of quantum computing, and this makes me very excited about the future of this field,” said Sivak.

Other authors of the paper (all affiliated or formerly affiliated with Yale) are Alec Eickbusch, Baptiste Royer, Shraddha Singh, Ioannis Tsioutsios, Suhas Ganjam, Alessandro Miano, Benjamin Brock, Andy Ding, Luigi Frunzio, Steven Girvin, and Robert Schoelkopf.

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Yale scientists, led by Michel Devoret, used quantum error correction to more than double a quantum bit's lifetime to 1.8 milliseconds.

Title:

Content: Doubling a qubit’s life, Yale scientists prove a key theory of quantum physics

Researchers at Yale have for the first time, using a process known as quantum error correction, substantially extended the lifetime of a quantum bit — a long-sought-after goal and one of the trickiest challenges in the field of quantum physics.

Led by Yale’s Michel Devoret, the experiment proves — decades after its theoretical foundations were proposed — that quantum error correction works in practice.

Quantum error correction is a process designed to keep quantum information intact for a period of time longer than if the same information were stored in hardware components without any correction.

The results were published March 21 in Nature.

Information in classical computing comes in the form of bits corresponding to ones or zeros. In quantum computing, information is stored in special devices with quantum properties that are known as quantum bits, or “qubits.”

In the lab of Devoret, the Frederick W. Beinecke Professor of Applied Physics, these qubits are constructed with superconducting circuits cooled to temperatures 100 times lower than those in outer space.

The qubits can each represent a one or a zero, or — confoundingly — both one and zero at the same time.

This “quantum parallelism” is one of the properties that enables quantum computers to make calculations that will potentially be orders of magnitude faster than what is possible on classical supercomputers and transform multiple industries.

Quantum systems, though, are fragile. They are bedeviled by a fundamental phenomenon of decoherence, a process in which the information stored in qubits quickly loses its quantum properties as a result of their interactions with the surrounding environment.

Quantum error correction, which was theoretically discovered in 1995, offers a means to combat this decoherence. Employing redundancy, it protects the quantum bit of information by encoding it in a system larger than what, in principle, is needed to represent a single qubit.

This larger system, however, makes the effect of the surrounding environment even more invasive and the encoded qubit even more fragile. Because of this effect, and complications from the additional components required to perform error correction, this process had never been able to definitively extend the lifetime of a quantum bit in practice.

In fact, just breaking even with an uncorrected qubit is a rare event, researchers say. Contrary to theoretical promises, in most experiments, error correction accelerates the decoherence of quantum information.

“For the first time, we have shown that making the system more redundant and actively detecting and correcting quantum errors provided a gain in the resilience of quantum information,” Devoret said. “Our experiment shows that quantum error correction is a real practical tool. It’s more than just a proof-of-principle demonstration.”

Devoret’s group has managed to more than double the lifetime of quantum information. Their error-corrected qubit lived for 1.8 milliseconds — things happen fast in the quantum realm.

They achieved their results using an error-correction code that was invented in 2001. “It gives you a sense of the delay between the theoretical proposals and practical realization of them in our field,” Devoret said.

Volodymyr Sivak, the lead author of the paper, said that this performance was achieved in part by employing a machine-learning agent that tweaked the error correction process to improve the outcome.

“There is no single breakthrough that enabled this result,” said Sivak, a former Ph.D.  student in Devoret’s lab and now a research scientist at Google. “It’s actually a combination of a whole bunch of different technologies that were developed in the past few years, which we combined in this experiment.”

The practical success of quantum computing will hinge on being able to create quantum bits of extremely high quality using quantum error correction. “Our experiment validates a cornerstone assumption of quantum computing, and this makes me very excited about the future of this field,” said Sivak.

Other authors of the paper (all affiliated or formerly affiliated with Yale) are Alec Eickbusch, Baptiste Royer, Shraddha Singh, Ioannis Tsioutsios, Suhas Ganjam, Alessandro Miano, Benjamin Brock, Andy Ding, Luigi Frunzio, Steven Girvin, and Robert Schoelkopf.

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What countries and blocs are leading in developing quantum computing?

China has delivered a 24-qubit quantum computer system, becoming the third country to do so after Canada and the US.

Title:

Content: Computing

INTERNATIONAL NEWS

China Delivers Its First Practical Quantum Computer System to a Customer

China’s Science Ministry on Monday announced that the country’s first practical quantum computer was delivered to a user, which the agency didn’t identify, a year ago.

The 24-qubit Wuyan system based on superconducting technology was built by Origin Quantum Computing Technology, a company founded in 2017 by two of the country’s leading quantum physicists, Guo Guoping and Guo Guangcan. A qubit in the quantum world performs functions akin to bits in the digital world.

With the on-premises installation of the Wuyan system, China became the third country, after Canada and the United States, to deliver a complete quantum computer system to a customer.

Some skeptics questioned the timing of the announcement.

“Quantum technology has a high priority for national security in China. If this were something very important, I doubt it would be disclosed like this in a transparent way by Chinese authorities,” explained Weifeng Zhong, a senior research fellow at the Mercatus Center of George Mason University in Fairfax, Va.

“The fact that it was delayed for a year suggests that they realize now that it’s not important to national security, so they’re trying to use it to build China’s image as a technology leader at a time when they’re trying to open up their economy to the rest of the world,” Zhong told TechNewsWorld.

Important Step

However, Hodan Omaar, a senior AI policy analyst at the Center for Data Innovation, a think tank studying the intersection of data, technology, and public policy, in Washington, D.C., maintained the announcement shows that China has made an important step in its quantum development.

“Overcoming technical challenges on the path toward large-scale quantum computers will depend on the ability to scale the number of qubits in quantum systems, much like modern classical computers have depended on the growth in the number of transistors in superconducting chips,” Omaar told TechNewsWorld.

“Investing in near-term quantum computing applications helps bolster the development of longer-term use cases of the technology, thereby helping to improve competitiveness,” she added.

Skip Sanzeri, co-founder and COO of QuSecure, a maker of quantum-safe security solutions in San Mateo, Calif., called the announcement “formidable” because China is stating that they have a fully functional quantum computer, albeit the qubit count is low.

“Nonetheless, error correction and noise reduction are two significant factors in ensuring that a quantum computer can process data and provide applications that we can rely on,” Sanzeri told TechNewsWorld. “By announcing that they have been able to get to this level shows that China is making progress towards larger quantum computers.”

Bucking a Trend

The Wuyan system appears to be on par with other systems in the market, noted Heather West, a senior research analyst at IDC’, an international market research company.

“The fact that they sold a 24 qubit system to someone isn’t that different from what we’re seeing elsewhere around the world,” West told TechNewsWorld.

Delivering a standalone system like the Wuyan is actually bucking the current trend in the market.

“Most quantum computers that people are accessing today are accessed through the cloud,” explained Doug Finke, an analyst with Global Quantum Intelligence, an international market intelligence firm.

“This Wuyan computer is being delivered to a customer in an on-premise situation,” Finke told TechNewsWorld. “On-premise has a lot of disadvantages. You have to worry about maintenance. You have to worry about spare parts. You have to worry about calibration.”

“In addition,” he continued, “quantum computing innovation is so fast that they become obsolete in about two years. So few people want an on-premise quantum computer. They’re much more comfortable with the cloud.”

Superconducting Challenges

The Wuyan system is built using superconducting chip technology, one of the earliest technologies for quantum computers. Since its introduction, other technologies have been explored. They include photonics, trapped ions, and neutral atoms.

“At the moment, no one knows which technology will be the winner or if there’ll be a combination of technologies that will combine for efficacious quantum applications,” Sanzeri said.

“Superconducting is very difficult,” he explained. “It requires near zero Kelvin refrigeration.”

“The electrons used in superconducting quantum computers are very hard to manage due to very short coherence times,” he continued. “That’s why they must be cooled to such a low temperature.”

Other methods are managing longer coherence times and a faster path to the desired goal of 1,000 error-corrected qubits, he added.

“The million-dollar question is what technology will win the race to the fault-tolerant quantum computer,” West said. “There might not be one winner. There might not be one system that comes out on top. It might be that certain kinds of systems are better than others at solving certain kinds of problems.”

Long View

Omaar countered that superconducting chips have a number of advantages over competing technologies.

“First, superconducting qubits are solid-state electrical circuits that are easier to control because they are manipulated using microwaves,” she said. “Scientists can therefore use easily accessible commercial microwave devices and equipment in superconducting quantum computing applications.”

“Second,” she continued, “because preparing superconducting circuits is based on the existing method for fabricating semiconductor chips, the development of high-quality devices can leverage advanced chip-making technologies, which is good for manufacturing and scalability.”

Despite developments like China’s Wuyan system, the arrival of a quantum computer that can tackle problems beyond the capacity of silicon computers appears to be years away.

“What quantum computers are going to be best for is solving complex, intractable problems beyond the scope of classical compute technology,” West said. “Those problems are years away from a quantum computer solving.”

“To get to that, we need at least a million qubits,” she continued. “That’s going to take a lot of work in scaling and stabilizing the qubits. Qubits are very sensitive to outside noise. As a result, the error rates are high in the technology we have.”

Despite the exuberance exhibited by many, we’re still in the early days of quantum computing, added Richard Stiennon, founder and chief research analyst at IT-Harvest, a cybersecurity industry analyst firm in Birmingham, Mich.

“There are many physical constraints on quantum computing that require precision in length of pathways — we are talking microns — and resistance to forces — footsteps can interfere with it. Supercooled chips just add to the complexity,” Stiennon told TechNewsWorld.

“I put it in the same realm as developing usable nuclear fusion as an energy source,” he said. “Hundreds of billions of dollars and decades to show a glimmer of progress.”

John P. Mello Jr. has been an ECT News Network reporter since 2003. His areas of focus include cybersecurity, IT issues, privacy, e-commerce, social media, artificial intelligence, big data and consumer electronics. He has written and edited for numerous publications, including the Boston Business Journal, the Boston Phoenix, Megapixel.Net and Government Security News. Email John.

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What are important areas in quantum research?

What countries and blocs are leading in developing quantum computing?

Google, IBM, and China have achieved quantum supremacy, with Google being the first in 2019.

Title:

Content: Google, IBM and China have already achieved quantum supremacy. Now they face another challenge: the correction of errors

Quantum supremacy is no longer at the center of the debate. It was at the end of 2019 because it came to light that the Google team led by John Martinis had managed to achieve it using its Sycamore quantum processor, and no one had done it until that moment. The noise that this news caused when it broke was justified.

But a year later, in December 2020, the group of Chinese researchers led by Jian-Wei Pan published an article in Science showing that I had also reached using its Zuchongzhi superconducting processor. And a year later, in November 2021, IBM followed suit and announced that it had reached this milestone using its 127-qubit Eagle quantum processor.

At this point no one doubts that quantum computers have come a long way. And, furthermore, they have done it in a real record time if we bear in mind that the first solid theoretical proposals arrived in the mid-1990s. And they are already capable of solving a few problems (very few still). in much less time than the most advanced supercomputers we currently have.

In fact, this is what quantum supremacy consists of: in solving in a short period of time, a few minutes or a few hours, a problem in which a classical supercomputer would spend many years. Even several centuries. Or millennia. Right now it is not too important whether these problems have practical applications or not. Whether or not they are relevant. We are still establishing the foundations of quantum computing, and the important thing is to face the challenges that are around the corner.

In search of higher quality qubits

One of the biggest challenges facing researchers involved in the development of quantum computing is delaying the onset of quantum decoherence. This phenomenon occurs when the necessary conditions for a system that is in an entangled quantum state to be maintained disappear.

Perhaps a slightly simpler way of describing it is to see it as a system that stops behaving as dictated by the rules of quantum mechanics when certain conditions are met, beginning to behave from that moment on as dictated by the rules of classical physics. . When does quantum decoherence appear? quantum effects disappear. And, therefore, also the advantages that they bring in the context of quantum computing.

The time it takes for quantum decoherence to appear is closely linked to the quality of the qubits

This phenomenon is very important because it helps us understand why many macroscopic physical systems do not exhibit quantum effects. Or, what is the same, why in our daily environment we cannot observe the counterintuitive effects of quantum mechanics. In any case, what is really relevant is that as the the quality of the qubits of a quantum processor, the longer it takes for quantum decoherence to appear. And, for this reason, we have more time available to carry out operations with it.

The two qubit fabrication technologies that are currently giving us the best results are superconducting qubits, which benefit greatly from recent advances in silicon lithography, and ion traps. However, some research groups also have other very promising technologies on the table that are worth pursuing, such as neutral atoms or the ions implanted in macromolecules.

IBM already has a 127-qubit superconducting quantum processor, and by the end of 2023 it plans to have Condor ready, a promising quantum chip with no less than 1,121 qubits.

We already brush the correction of errors with the tips of our fingers

The other big challenge facing quantum computing right now is error correction. Quantum computers make errors when carrying out some operations, and when this happens, the results they return to us are not correct, of course. The problem is that implementing a quantum error correction protocol it’s not trivial. And furthermore, if they abound, it is essentially impossible to correct them and simultaneously prevent the quantum processor’s efficiency from sinking.

Fortunately, we have good news. As we told you a few days ago, three independent research groups have managed to perfect superconducting qubits that have an accuracy greater than 99%. This simply means that they make mistakes very infrequently, and the good news is that when they are so infrequent it is easier to correct them. Much easier.

When the incidence of errors is less than 1%, it is much easier for quantum fault-correction protocols to carry out their task

In fact, these research groups ensure that when the incidence of errors is less than 1% quantum fault-correction protocols find it much easier to do their job. At the moment they are working with only one or two qubits, and these quantum processors are too simple to solve significant problems, but if they manage to scale this technology to many more qubits, quantum computers could leave behind one of the biggest challenges they currently face. .

As we have just seen, quantum computing is advancing at a breakneck pace. The entry of private companies in this sector you are greatly accelerating your progress, but before we get carried away with enthusiasm, it is important that we keep in mind that there are other challenges that are also crucial to solve.

Two of the most substantial are the need to control qubits more precisely, and also the importance of implementing new quantum algorithms that they are able to help us tackle the problems that we cannot solve with the most powerful classical supercomputers that we have today. Still, the future for quantum computing is hopeful. And, above all, very promising.

Pictures | IBM

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What companies are leading in developing quantum computing?

What have been the landmark achievements in quantum computing?

Google's Sycamore quantum supremacy experiment

IBM researchers discovered an error correction approach that reduces required qubits by a factor of 10.

Title:

Content: New Codes Could Accelerate the Advent of Practical Quantum Computing

One of the biggest stumbling blocks for quantum computers is their tendency to be error-prone and the massive computational overhead required to clean up their mistakes. IBM has now made a breakthrough by dramatically reducing the number of qubits required to do so.

All computers are prone to errors, and even the computer chip in your laptop runs code designed to fix things when a bit flips accidentally. But fragile quantum states are far more vulnerable to things like environmental noise, which means correcting errors in quantum processors will require considerable resources.

Most estimates predict that creating just a single fault-tolerant qubit, or logical qubit, that can carry out useful operations will require thousands of physical qubits dedicated to error correction. Given that today’s biggest processors have just hundreds of qubits, this suggests we’re still a long way from building practical quantum computers that can solve real problems.

But now researchers at IBM say they’ve discovered a new approach that slashes the number of qubits required for error correction by a factor of 10. While the approach currently only works on quantum memory rather than computation, the technique could open the door to efficient new approaches to creating fault-tolerant devices.

Practical error correction is far from a solved problem,” the researchers write in a blog post. “However, these new codes and other advances across the field are increasing our confidence that fault tolerant quantum computing isn’t just possible, but is possible without having to build an unreasonably large quantum computer.”

The leading approach to error correction today is known as the surface code, which involves arranging qubits in a specially configured 2D lattice and using some to encode data and others to make measurements to see if an error has occurred. The approach is effective, but it requires a large number of physical qubits to pull off—as many as 20 million for some key problems of interest, according to IBM.

The new technique, outlined in a preprint on arXiv, comes from the same family of error-correction approaches as the surface code. But while each qubit in the surface code is connected to four others, the new technique connects them to six others, which makes it possible to encode more information into the same number of physical qubits.

As a result, the researchers say they can reduce the number of qubits required by an order of magnitude. Creating 12 logical qubits using their approach would require only 288 physical qubits, compared to more than 4,000 when using the surface code.

There are some significant caveats, though. For a start, it’s currently impossible to achieve the kind of six-way connectivity the team envisages. While the surface code operates on a single plane and can therefore be easily implemented on the kind of flat chip already found in quantum processors, the new approach requires connections to distant qubits that aren’t located on the same surface.

The researchers say this isn’t an insurmountable barrier, and IBM is already developing the kind of long-range couplers required to make these kinds of corrections. The technologies needed are certainly plausible, Jérémie Guillaud at French quantum computing startup Alice & Bob told New Scientist, and could be here in just a matter of years.

A bigger open question, though, is the fact that so far the approach only works with a small number of logical operations. This means that while it works for reading and writing to a quantum memory in a fault-tolerant way, it wouldn’t support most quantum computations.

But the IBM researchers say the techniques they’ve unveiled are just a stepping stone that points toward a rich new vein of even better error-correction approaches. If they’re right and scientists are able to find more efficient alternatives to the surface code, it could significantly accelerate the advent of practical quantum computing.

Image Credit: IBM

Edd Genthttp://www.eddgent.com/
I am a freelance science and technology writer based in Bangalore, India. My main areas of interest are engineering, computing and biology, with a particular focus on the intersections between the three.
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The new approach connects each qubit to six others, increasing the information that can be encoded.

Title:

Content: New Codes Could Accelerate the Advent of Practical Quantum Computing

One of the biggest stumbling blocks for quantum computers is their tendency to be error-prone and the massive computational overhead required to clean up their mistakes. IBM has now made a breakthrough by dramatically reducing the number of qubits required to do so.

All computers are prone to errors, and even the computer chip in your laptop runs code designed to fix things when a bit flips accidentally. But fragile quantum states are far more vulnerable to things like environmental noise, which means correcting errors in quantum processors will require considerable resources.

Most estimates predict that creating just a single fault-tolerant qubit, or logical qubit, that can carry out useful operations will require thousands of physical qubits dedicated to error correction. Given that today’s biggest processors have just hundreds of qubits, this suggests we’re still a long way from building practical quantum computers that can solve real problems.

But now researchers at IBM say they’ve discovered a new approach that slashes the number of qubits required for error correction by a factor of 10. While the approach currently only works on quantum memory rather than computation, the technique could open the door to efficient new approaches to creating fault-tolerant devices.

Practical error correction is far from a solved problem,” the researchers write in a blog post. “However, these new codes and other advances across the field are increasing our confidence that fault tolerant quantum computing isn’t just possible, but is possible without having to build an unreasonably large quantum computer.”

The leading approach to error correction today is known as the surface code, which involves arranging qubits in a specially configured 2D lattice and using some to encode data and others to make measurements to see if an error has occurred. The approach is effective, but it requires a large number of physical qubits to pull off—as many as 20 million for some key problems of interest, according to IBM.

The new technique, outlined in a preprint on arXiv, comes from the same family of error-correction approaches as the surface code. But while each qubit in the surface code is connected to four others, the new technique connects them to six others, which makes it possible to encode more information into the same number of physical qubits.

As a result, the researchers say they can reduce the number of qubits required by an order of magnitude. Creating 12 logical qubits using their approach would require only 288 physical qubits, compared to more than 4,000 when using the surface code.

There are some significant caveats, though. For a start, it’s currently impossible to achieve the kind of six-way connectivity the team envisages. While the surface code operates on a single plane and can therefore be easily implemented on the kind of flat chip already found in quantum processors, the new approach requires connections to distant qubits that aren’t located on the same surface.

The researchers say this isn’t an insurmountable barrier, and IBM is already developing the kind of long-range couplers required to make these kinds of corrections. The technologies needed are certainly plausible, Jérémie Guillaud at French quantum computing startup Alice & Bob told New Scientist, and could be here in just a matter of years.

A bigger open question, though, is the fact that so far the approach only works with a small number of logical operations. This means that while it works for reading and writing to a quantum memory in a fault-tolerant way, it wouldn’t support most quantum computations.

But the IBM researchers say the techniques they’ve unveiled are just a stepping stone that points toward a rich new vein of even better error-correction approaches. If they’re right and scientists are able to find more efficient alternatives to the surface code, it could significantly accelerate the advent of practical quantum computing.

Image Credit: IBM

Edd Genthttp://www.eddgent.com/
I am a freelance science and technology writer based in Bangalore, India. My main areas of interest are engineering, computing and biology, with a particular focus on the intersections between the three.
RELATED
latest
Don't miss a trend
Get Hub delivered to your inbox

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Entropica Labs, a Singapore-based quantum software startup, has received $4.7 million in A-round funding.

Title:

Content: Singapore-based quantum software startup Entropica Labs has recently secured a $4.7 million Series A funding round.
It is understood that the financing was jointly led by Italian deep technology investment institution Liftt and its existing investor Wavemaker Partners, with participation from SEEDS Capital (the investment arm of Singapore Enterprise Development Authority), CerraCap Ventures, SUTD Venture Holdings, Elev8 and others.
According to the statement, the funds will be used to expand Entropica Labs ’ team building in the areas of quantum error correction, software engineering and computational architecture.
Entropica Labs was founded in 2018 to provide developers and users with software development tools that enable quantum computers to recognize and correct errors during computation, helping them improve accuracy and efficiency in quantum computing.
Entropica Labs says that as hardware companies continue to roll out larger and more advanced quantum computing systems, some of which have crossed computational thresholds, the demand for complex error correction schemes in the field has become more intense, so Entropica Labs hopes to enhance the space for quantum computers with scalable software tools.
According to the official website, Entropica Labs has now launched two products, OpenQAOA and JEPOS, the former is a multi-end and open source Python software development kit for quantum computer optimization, and the latter can be used for benchmarking quantum performance.
It is worth mentioning that earlier this year, another Singapore-based quantum computing startup called Horizon Quantum Computing also received a Series A funding round.
It is understood that the size of the financing is 18.1 million US dollars, and the investors include Tencent.

Developing large-scale quantum computers is hindered by the need for robust error correction and noise reduction.

Title:

Content: Singapore-based quantum software startup Entropica Labs has recently secured a $4.7 million Series A funding round.
It is understood that the financing was jointly led by Italian deep technology investment institution Liftt and its existing investor Wavemaker Partners, with participation from SEEDS Capital (the investment arm of Singapore Enterprise Development Authority), CerraCap Ventures, SUTD Venture Holdings, Elev8 and others.
According to the statement, the funds will be used to expand Entropica Labs ’ team building in the areas of quantum error correction, software engineering and computational architecture.
Entropica Labs was founded in 2018 to provide developers and users with software development tools that enable quantum computers to recognize and correct errors during computation, helping them improve accuracy and efficiency in quantum computing.
Entropica Labs says that as hardware companies continue to roll out larger and more advanced quantum computing systems, some of which have crossed computational thresholds, the demand for complex error correction schemes in the field has become more intense, so Entropica Labs hopes to enhance the space for quantum computers with scalable software tools.
According to the official website, Entropica Labs has now launched two products, OpenQAOA and JEPOS, the former is a multi-end and open source Python software development kit for quantum computer optimization, and the latter can be used for benchmarking quantum performance.
It is worth mentioning that earlier this year, another Singapore-based quantum computing startup called Horizon Quantum Computing also received a Series A funding round.
It is understood that the size of the financing is 18.1 million US dollars, and the investors include Tencent.

What are important areas in quantum research?

What are the challenges in quantum computing research?

sensitivity to environment
high error rates

Quantum error correction is a key challenge in developing large-scale quantum computers, with companies like Entropica Labs working on software solutions.

Title:

Content: Singapore-based quantum software startup Entropica Labs has recently secured a $4.7 million Series A funding round.
It is understood that the financing was jointly led by Italian deep technology investment institution Liftt and its existing investor Wavemaker Partners, with participation from SEEDS Capital (the investment arm of Singapore Enterprise Development Authority), CerraCap Ventures, SUTD Venture Holdings, Elev8 and others.
According to the statement, the funds will be used to expand Entropica Labs ’ team building in the areas of quantum error correction, software engineering and computational architecture.
Entropica Labs was founded in 2018 to provide developers and users with software development tools that enable quantum computers to recognize and correct errors during computation, helping them improve accuracy and efficiency in quantum computing.
Entropica Labs says that as hardware companies continue to roll out larger and more advanced quantum computing systems, some of which have crossed computational thresholds, the demand for complex error correction schemes in the field has become more intense, so Entropica Labs hopes to enhance the space for quantum computers with scalable software tools.
According to the official website, Entropica Labs has now launched two products, OpenQAOA and JEPOS, the former is a multi-end and open source Python software development kit for quantum computer optimization, and the latter can be used for benchmarking quantum performance.
It is worth mentioning that earlier this year, another Singapore-based quantum computing startup called Horizon Quantum Computing also received a Series A funding round.
It is understood that the size of the financing is 18.1 million US dollars, and the investors include Tencent.

What are important areas in quantum research?

development of high-level software
implementations of quantum processors

What are the challenges in quantum computing research?

The Cloud-based Quantum Computing Market is projected to reach USD 6,289.8 Million by 2030, growing at a 35.5% CAGR.

Major vendors in the Global Cloud-Based Quantum Computing Market include Accenture, AWS, Baidu, Cambridge Quantum, D-Wave, Google, IBM, and Microsoft.

What countries and blocs are leading in developing quantum computing?

The market is growing as organizations seek to harness quantum processors through cloud services.

What are important areas in quantum research?

Cloud-based quantum computing democratizes access, allowing businesses to explore without extensive on-premises infrastructure.

Investment in quantum technology reached a record $2.35 billion in 2022.

68% of total quantum technology investment since 2001 has occurred in the last two years.

Quantum technology could add $1.3 trillion in value by 2035, a McKinsey report says.

Four industries will likely be impacted first by quantum technology: automotive, chemicals, financial services, and life sciences.

What fields can quantum computers advance?

The next stage in quantum computing requires developing 'fault-tolerant' processors to solve real-world problems more accurately and faster.

What advantages do quantum computers have over conventional computers?

What are important areas in quantum research?

What are the challenges in quantum computing research?

IBM is developing two types of quantum processors: one with over 1,000 qubits and another with fewer, but higher-quality qubits.

What are important areas in quantum research?

new types of qubits
implementations of quantum processors

What companies are leading in developing quantum computing?

What seminal quantum computers/ processors have been developed?

Difficult challenges remain in the five main approaches to quantum computers, including scaling control and cooling systems.

What are important areas in quantum research?

Quantum computing scale-up requires top talent, but a significant gap still exists.

The talent gap is narrowing, with nearly two-thirds of open jobs potentially fillable with new master's-level graduates.

In 2022, 717 job postings remained unfilled despite 450 applicable master's-level graduates.

The EU and UK were top destinations for quantum technology graduates in 2020, with 303 and 217 graduates per million inhabitants, respectively.

What countries and blocs are leading in developing quantum computing?

North America leads the Cloud-based Quantum Computing market, driven by the US and Canada.

What countries and blocs are leading in developing quantum computing?

The research and academia segment is expected to hold the largest market share due to its active involvement in advancing quantum technologies.

Cloud-based platforms enable researchers and students to experiment with quantum computing collaboratively.

The market is growing as organizations seek to harness quantum processors through cloud services.

What are important areas in quantum research?

Cloud-based quantum computing democratizes access, allowing businesses to explore without extensive on-premises infrastructure.

Quantum computers use qubits that can be 0, 1, or both, enabling exponential increases in computing power.

What advantages do quantum computers have over conventional computers?

extremely fast calculations
extremely complex calculations

Google's Sycamore processor completed a calculation in 200 seconds that would take a classical computer 10,000 years.

What advantages do quantum computers have over conventional computers?

extremely fast calculations
extremely complex calculations

What companies are leading in developing quantum computing?

What have been the landmark achievements in quantum computing?

Google's Sycamore quantum supremacy experiment

Quantum error-correction protocols, like surface code and cat code, are being developed to detect and correct qubit errors.

What are important areas in quantum research?

What are the challenges in quantum computing research?

High hardware costs hinder quantum computing adoption.

A shortage of skilled quantum computing experts hinders its adoption.

Technical difficulties hinder the development of large-scale quantum computers.

Limited access to quantum experts restrains the quantum computing market's growth.

Few practical quantum computing applications have been developed, hindering its adoption.

Title:

Content: TIMES ENTERPRISE NETWORK: RISING STARS

Start-up leads charge in widening access to quantum computing

Oxford Quantum Circuits sells access to its supercomputer via Amazon Web Services
new

Dr Ilana Wisby is the chief executive of Europe’s first “quantum computing-as-a-service” company and one of very few women leading start-ups in the field.

Quantum computing is developing rapidly, and global investment in the sector has topped $35.5 billion (£27 million) as industry and governments look to seize on the opportunity it presents. In his most recent budget, Jeremy Hunt unveiled a £2.5 billion funding pot for quantum research, even as he slashed funding for other tech areas.

Quantum computers can operate much faster than conventional computers and perform multiple calculations simultaneously. The technology is still maturing, but in the near future it could solve previously intractable problems, enhance artificial intelligence and transform processes such as drug discovery.

Wisby, 32, who holds a PhD in

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Content: Keysight Technologies, Inc. (NYSE: KEYS) and Q-CTRL, a pioneer of quantum infrastructure software to make quantum technologies useful, are partnering to integrate key infrastructure quantum software to accelerate quantum processor development, characterization, and key proof of principle scientific demonstrations.

An interesting feature of quantum computation is that as qubits are added to a quantum processor, the computational space available to the end user expands exponentially. However, as quantum systems grow exponentially, they become increasingly more complex to design, test, and operate. This means quantum hardware developers face a slow and complex design cycle as current software tools require users to exhaustively test and calibrate an ever-growing number of configurations and combinations.

To address these design challenges, Keysight and Q-CTRL are partnering to provide an integrated solution enabling quantum developers to effectively scale both quantum processor quantity and quality. The solution will integrate Q-CTRL’s Boulder Opal hardware optimization and automation functionality into Keysight’s Quantum Control System (QCS) providing enhanced capability in quantum processor characterization and optimization to rapidly decrease characterization time and improve device up-time.

To accelerate quantum development, the joint solution will:

  • Help navigate complexity – Provide advanced AI/ML tools to navigate complex design and characterization spaces.
  • Automate device optimization – Enable closed loop, autonomous agents to efficiently determine the relationship between Hamiltonian parameters and QCS hardware settings.
  • Accelerate the quantum design cycle – Less time calibrating and characterizing a quantum processor means faster development cycles and more use case development time available.
  • Customizable experiments – Allow users to program and optimize experiments specific to their quantum device.
  • Enhanced exploration – Enable more avenues of exploration and innovation for quantum scientists and engineers.

The Keysight QCS combines dedicated quantum control hardware and full-stack software capabilities to provide an easy-to-use solution for the control and readout of quantum devices. Q-CTRL Boulder Opal delivers cloud-accelerated hardware design, AI-based automation, and quantum control optimization, giving professional teams everything they need to get ahead of the competition.

Alex Shih, Head of Product, Q-CTRL, said: "We are delighted to be working with Keysight to bring Q-CTRL’s hardware characterization and optimization capabilities to their end users and empowering experimentalists and researchers to build and scale real quantum systems. We designed our products to be easily integrated and interoperable across hardware and software architectures, and we are proud to see this help activate the quantum ecosystem. To us, making quantum technology useful relies on not just developing new technologies, but supporting researchers to easily leverage them in building and scaling their quantum systems.”

Eric T. Holland, Director of Strategic Initiatives, Quantum at Keysight, said: "Customer success is at the core of all that we do at Keysight. We are continually seeking feedback from our quantum users to drive our roadmap and spur innovation. This collaboration with Q-CTRL comes from such feedback and we are thrilled to begin our journey to improve the end-user experience and capabilities for our customers."

About Keysight

At Keysight (NYSE: KEYS), we inspire and empower innovators to bring world-changing technologies to life. As an S&P 500 company, we're delivering market-leading design, emulation, and test solutions to help engineers develop and deploy faster, with less risk, throughout the entire product life cycle. We're a global innovation partner enabling customers in quantum, communications, industrial automation, aerospace and defense, automotive, semiconductor, and general electronics markets to accelerate innovation to connect and secure the world. Learn more at Keysight Newsroom and www.keysight.com.

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Content: New Codes Could Accelerate the Advent of Practical Quantum Computing

One of the biggest stumbling blocks for quantum computers is their tendency to be error-prone and the massive computational overhead required to clean up their mistakes. IBM has now made a breakthrough by dramatically reducing the number of qubits required to do so.

All computers are prone to errors, and even the computer chip in your laptop runs code designed to fix things when a bit flips accidentally. But fragile quantum states are far more vulnerable to things like environmental noise, which means correcting errors in quantum processors will require considerable resources.

Most estimates predict that creating just a single fault-tolerant qubit, or logical qubit, that can carry out useful operations will require thousands of physical qubits dedicated to error correction. Given that today’s biggest processors have just hundreds of qubits, this suggests we’re still a long way from building practical quantum computers that can solve real problems.

But now researchers at IBM say they’ve discovered a new approach that slashes the number of qubits required for error correction by a factor of 10. While the approach currently only works on quantum memory rather than computation, the technique could open the door to efficient new approaches to creating fault-tolerant devices.

Practical error correction is far from a solved problem,” the researchers write in a blog post. “However, these new codes and other advances across the field are increasing our confidence that fault tolerant quantum computing isn’t just possible, but is possible without having to build an unreasonably large quantum computer.”

The leading approach to error correction today is known as the surface code, which involves arranging qubits in a specially configured 2D lattice and using some to encode data and others to make measurements to see if an error has occurred. The approach is effective, but it requires a large number of physical qubits to pull off—as many as 20 million for some key problems of interest, according to IBM.

The new technique, outlined in a preprint on arXiv, comes from the same family of error-correction approaches as the surface code. But while each qubit in the surface code is connected to four others, the new technique connects them to six others, which makes it possible to encode more information into the same number of physical qubits.

As a result, the researchers say they can reduce the number of qubits required by an order of magnitude. Creating 12 logical qubits using their approach would require only 288 physical qubits, compared to more than 4,000 when using the surface code.

There are some significant caveats, though. For a start, it’s currently impossible to achieve the kind of six-way connectivity the team envisages. While the surface code operates on a single plane and can therefore be easily implemented on the kind of flat chip already found in quantum processors, the new approach requires connections to distant qubits that aren’t located on the same surface.

The researchers say this isn’t an insurmountable barrier, and IBM is already developing the kind of long-range couplers required to make these kinds of corrections. The technologies needed are certainly plausible, Jérémie Guillaud at French quantum computing startup Alice & Bob told New Scientist, and could be here in just a matter of years.

A bigger open question, though, is the fact that so far the approach only works with a small number of logical operations. This means that while it works for reading and writing to a quantum memory in a fault-tolerant way, it wouldn’t support most quantum computations.

But the IBM researchers say the techniques they’ve unveiled are just a stepping stone that points toward a rich new vein of even better error-correction approaches. If they’re right and scientists are able to find more efficient alternatives to the surface code, it could significantly accelerate the advent of practical quantum computing.

Image Credit: IBM

Edd Genthttp://www.eddgent.com/
I am a freelance science and technology writer based in Bangalore, India. My main areas of interest are engineering, computing and biology, with a particular focus on the intersections between the three.
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Content: How big does your quantum computer need to be?

Quantum computers are expected to be disruptive and potentially impact many industry sectors. So researchers in the United Kingdom and the Netherlands decided to explore two very different quantum problems: breaking the encryption of Bitcoin (a digital currency) and simulating the molecule responsible for biological nitrogen fixation.

In AVS Quantum Science, from AIP Publishing, the researchers describe a tool they created to determine how big a quantum computer needs to be to solve problems like these and how long it will take.

“The majority of existing work within this realm focuses on a particular hardware platform, superconducting devices, like those IBM and Google are working toward,” said Mark Webber, of the University of Sussex. “Different hardware platforms will vary greatly on key hardware specifications, such as the rate of operations and the quality of control on the qubits (quantum bits).”

Many of the most promising quantum advantage use cases will require an error-corrected quantum computer. Error correction enables running longer algorithms by compensating for inherent errors inside the quantum computer, but it comes at the cost of more physical qubits.

Pulling nitrogen out of the air to make ammonia for fertilizers is extremely energy-intensive, and improvements to the process could impact both world food scarcity and the climate crisis. Simulation of relevant molecules is currently beyond the abilities of even the world’s fastest supercomputers but should be within the reach of next-gen quantum computers.

“Our tool automates the calculation of the error-correction overhead as a function of key hardware specifications,” Webber said. “To make the quantum algorithm run faster, we can perform more operations in parallel by adding more physical qubits. We introduce extra qubits as needed to reach the desired runtime, which is critically dependent on the rate of operations at the physical hardware level.”

Most quantum computing hardware platforms are limited, because only qubits right next to each other can interact directly. In other platforms, such as some trapped ion designs, the qubits are not in fixed positions and can instead be physically moved around — meaning each qubit can interact directly with a wide set of other qubits.

“We explored how to best take advantage of this ability to connect distant qubits, with the aim of solving problems in less time with fewer qubits,” said Webber. “We must continue to tailor the error-correction strategies to exploit the strengths of the underlying hardware, which may allow us to solve highly impactful problems with a smaller-size quantum computer than had previously been assumed.”

Quantum computers are exponentially more powerful at breaking many encryption techniques than classical computers. The world uses RSA encryption for most of its secure communication. RSA encryption and the one Bitcoin uses (elliptic curve digital signature algorithm) will one day be vulnerable to a quantum computing attack, but today, even the largest supercomputer could never pose a serious threat.

The researchers estimated the size a quantum computer needs to be to break the encryption of the Bitcoin network within the small window of time it would actually pose a threat to do so — in between its announcement and integration into the blockchain. The greater the fee paid on the transaction, the shorter this window will be, but it likely ranges from minutes to hours.

“State-of-the-art quantum computers today only have 50-100 qubits,” said Webber. “Our estimated requirement of 30 [million] to 300 million physical qubits suggests Bitcoin should be considered safe from a quantum attack for now, but devices of this size are generally considered achievable, and future advancements may bring the requirements down further.

“The Bitcoin network could perform a ‘hard-fork’ onto a quantum-secure encryption technique, but this may result in network scaling issues due to an increased memory requirement.”

The researchers emphasize the rate of improvement of both quantum algorithms and error- correction protocols.

“Four years ago, we estimated a trapped ion device would need a billion physical qubits to break RSA encryption, requiring a device with an area of 100-by-100 square meters,” said Webber. “Now, with improvements across the board, this could see a dramatic reduction to an area of just 2.5-by-2.5 square meters.”

A large-scale error-corrected quantum computer should be able to solve important problems classical computers cannot.

“Simulating molecules has applications for energy efficiency, batteries, improved catalysts, new materials, and the development of new medicines,” said Webber. “Further applications exist across the board — including for finance, big data analysis, fluid flow for airplane designs, and logistical optimizations.” The article “The impact of hardware specifications on reaching quantum advantage in the fault tolerant regime” is authored by Mark Webber, Vincent Elfving, Sebastian Weidt, and Winifried K. Hensinger. It will appear in AVS Quantum Science on Jan. 25, 2022 (DOI: 10.1116/5.0073075). After that date, it can be accessed at https://aip.scitation.org/doi/10.1116/5.0073075.

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Content: Google, IBM and China have already achieved quantum supremacy. Now they face another challenge: the correction of errors

Quantum supremacy is no longer at the center of the debate. It was at the end of 2019 because it came to light that the Google team led by John Martinis had managed to achieve it using its Sycamore quantum processor, and no one had done it until that moment. The noise that this news caused when it broke was justified.

But a year later, in December 2020, the group of Chinese researchers led by Jian-Wei Pan published an article in Science showing that I had also reached using its Zuchongzhi superconducting processor. And a year later, in November 2021, IBM followed suit and announced that it had reached this milestone using its 127-qubit Eagle quantum processor.

At this point no one doubts that quantum computers have come a long way. And, furthermore, they have done it in a real record time if we bear in mind that the first solid theoretical proposals arrived in the mid-1990s. And they are already capable of solving a few problems (very few still). in much less time than the most advanced supercomputers we currently have.

In fact, this is what quantum supremacy consists of: in solving in a short period of time, a few minutes or a few hours, a problem in which a classical supercomputer would spend many years. Even several centuries. Or millennia. Right now it is not too important whether these problems have practical applications or not. Whether or not they are relevant. We are still establishing the foundations of quantum computing, and the important thing is to face the challenges that are around the corner.

In search of higher quality qubits

One of the biggest challenges facing researchers involved in the development of quantum computing is delaying the onset of quantum decoherence. This phenomenon occurs when the necessary conditions for a system that is in an entangled quantum state to be maintained disappear.

Perhaps a slightly simpler way of describing it is to see it as a system that stops behaving as dictated by the rules of quantum mechanics when certain conditions are met, beginning to behave from that moment on as dictated by the rules of classical physics. . When does quantum decoherence appear? quantum effects disappear. And, therefore, also the advantages that they bring in the context of quantum computing.

The time it takes for quantum decoherence to appear is closely linked to the quality of the qubits

This phenomenon is very important because it helps us understand why many macroscopic physical systems do not exhibit quantum effects. Or, what is the same, why in our daily environment we cannot observe the counterintuitive effects of quantum mechanics. In any case, what is really relevant is that as the the quality of the qubits of a quantum processor, the longer it takes for quantum decoherence to appear. And, for this reason, we have more time available to carry out operations with it.

The two qubit fabrication technologies that are currently giving us the best results are superconducting qubits, which benefit greatly from recent advances in silicon lithography, and ion traps. However, some research groups also have other very promising technologies on the table that are worth pursuing, such as neutral atoms or the ions implanted in macromolecules.

IBM already has a 127-qubit superconducting quantum processor, and by the end of 2023 it plans to have Condor ready, a promising quantum chip with no less than 1,121 qubits.

We already brush the correction of errors with the tips of our fingers

The other big challenge facing quantum computing right now is error correction. Quantum computers make errors when carrying out some operations, and when this happens, the results they return to us are not correct, of course. The problem is that implementing a quantum error correction protocol it’s not trivial. And furthermore, if they abound, it is essentially impossible to correct them and simultaneously prevent the quantum processor’s efficiency from sinking.

Fortunately, we have good news. As we told you a few days ago, three independent research groups have managed to perfect superconducting qubits that have an accuracy greater than 99%. This simply means that they make mistakes very infrequently, and the good news is that when they are so infrequent it is easier to correct them. Much easier.

When the incidence of errors is less than 1%, it is much easier for quantum fault-correction protocols to carry out their task

In fact, these research groups ensure that when the incidence of errors is less than 1% quantum fault-correction protocols find it much easier to do their job. At the moment they are working with only one or two qubits, and these quantum processors are too simple to solve significant problems, but if they manage to scale this technology to many more qubits, quantum computers could leave behind one of the biggest challenges they currently face. .

As we have just seen, quantum computing is advancing at a breakneck pace. The entry of private companies in this sector you are greatly accelerating your progress, but before we get carried away with enthusiasm, it is important that we keep in mind that there are other challenges that are also crucial to solve.

Two of the most substantial are the need to control qubits more precisely, and also the importance of implementing new quantum algorithms that they are able to help us tackle the problems that we cannot solve with the most powerful classical supercomputers that we have today. Still, the future for quantum computing is hopeful. And, above all, very promising.

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Content: A new quantum processor, a modular quantum computer and more were unveiled at the IBM Quantum Summit, held in New York on Dec. 4. This hardware is part of IBM’s effort toward large-scale quantum computing for scientific research.

In addition, IBM announced Qiskit 1.0, which is the stable release of the open source programming software development kit for quantum circuits.

While quantum computing is often experimental and used in academic settings, it can be used in the enterprise when organizations need to solve mathematical problems too complex for classical computing, such as creating new chemical combinations in materials engineering or pharmaceuticals. Quantum key distribution and quantum cryptography can be used in cybersecurity.

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Researchers can now access the new IBM Quantum Heron processor

IBM Quantum Heron (Figure A) is a 133-qubit quantum processor available today via the cloud. It is the successor to IBM Quantum Eagle, which came out in 2021 and established 3D packaging techniques that laid the groundwork for the company’s subsequent quantum processors.

Figure A

“Fundamentally, Heron looks a lot like Eagle — it’s the same type of qubits, the same fabrication and the same packaging technology; so most of Eagle has carried straight across; it’s really some details of the on-chip circuitry and our controls that have changed,” said Oliver Dial, CTO at IBM Quantum, in an email to TechRepublic. “One of the key breakthroughs from Eagle was the development of multi-level wiring, with the qubits sitting on a single plane, to provide flexibility for signal routing and device layout.”

IBM Quantum Heron includes advances in qubit fabrication and laminate size and a five-fold improvement in error reduction compared to IBM Quantum Eagle.

“We are firmly within the era in which quantum computers are being used as a tool to explore new frontiers of science,” said IBM SVP and Director of Research Dario Gil in a press release.

Specifically, IBM quantum processors are being used in scientific settings to simulate chemistry, physics and materials problems. The long-term goal is to expand these experiments to what IBM calls “utility scale” – in essence, to solve practical, widespread problems.

“In this context, ‘utility-scale’ means a processor with 100+ qubits, which allows the user to run calculations that are too big to be simulated on a classical computer,” Dial said. “It’s the combination of this scale and error-mitigation techniques that will allow users to derive real value from a quantum computer – hence ‘utility.’ Now that we’ve achieved utility-scale, we’re seeing people using quantum computing as a scientific tool.”

“I like to say users are using quantum computing to do quantum computing,” Gambetta wrote in a blog post on Dec. 4.

WATCH: Explore quantum computing myths and realities in this TechRepublic video

These institutions work with IBM to demonstrate research exploring large-scale quantum computing:

  • University of Tokyo.
  • Argonne National Laboratory.
  • Fundacion Ikerbasque.
  • Qedma.
  • Algorithmiq.
  • University of Washington.
  • University of Cologne.
  • Harvard University.
  • UC Berkeley.
  • Q-CTRL.

IBM Quantum System Two modular system combines classical and quantum computing

IBM Quantum System Two (Figure B) is the system behind IBM’s current quantum computing system architecture. IBM Quantum System Two combines classical and quantum computing, with a middleware layer in between to integrate the two. Scalable cryogenic infrastructure works alongside classical runtime servers with modular qubit control electronics.

IBM Quantum System Two is remarkable because it’s the first modular quantum computer built for utility-scale problems, IBM said. IBM expects it to be upgradeable over time, with the goal of running 1 billion operations in a single quantum circuit by 2033. That’s an extraordinary amount of supercomputing resources for a wide variety of scientific and upcoming business operations.

Figure B

Currently, IBM Quantum System Two runs three IBM Quantum Heron processors. It began operating recently at an IBM facility in Yorktown Heights, NY.

Qiskit quantum SDK reaches stable release 1.0

Qiskit 1.0, the stable release of IBM’s quantum computing software development kit, will be available in February 2024. (IBM first made Qiskit available in 2017.) Qiskit 1.0 is built around the idea of Patterns, IBM’s programming template for making quantum computing more accessible by translating classical inputs to quantum problems. Patterns are meant to be run on IBM’s Quantum Serverless computing infrastructure.

Generative AI for quantum code programming in Qiskit will be available through IBM’s enterprise AI platform watsonx. IBM revealed Qiskit Code Assistant, a generative AI assistant bot made to help users navigate Qiskit and IBM Quantum Platform. Qiskit Code Assistant is coming in alpha in early 2024 for premium subscribers of the IBM Quantum Platform.

“Generative AI and quantum computing are both reaching an inflection point, presenting us with the opportunity to use the trusted foundation model framework of watsonx to simplify how quantum algorithms can be built for utility-scale exploration,” said Jay Gambetta, vice president and IBM fellow at IBM, in a press release.

Plus, IBM announced:

  •  A new Transpiler Service in Qiskit
  •  AI Transpiler passes for Qiskit Premium users
  •  the Batch execution mode, a context manager.

IBM expands roadmap for quantum development

IBM unveiled an expanded roadmap that will shape its work on developing quantum computing. IBM Quantum System Two is part of the plan as the home of IBM’s upcoming quantum processors.

According to the roadmap, 2023 was the year of IBM adding generative AI and speeding up quantum processing by five times with quantum serverless and Execution modes. IBM plans to focus 2024 on improving quantum circuit quality and speed to allow 5,000 quantum logic gates with parametric circuits. (A quantum logic gate is a building block of quantum computing, operating on qubits instead of conventional bits.) IBM Quantum Heron and resource management are on the schedule for 2024.

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Content: IONQ

Good Stocks To Buy Right Now? 3 Quantum Computing Stocks To Know

The quantum computing industry is poised to revolutionize the way we understand computing and data processing, opening up unprecedented opportunities for advancements in various sectors such as healthcare, finance, and cybersecurity. Unlike classical computers, which use bits as the basic unit of information, quantum computers utilize quantum bits or “qubits,” which can exist in multiple states simultaneously. This inherent ability to perform complex computations at speeds unimaginable with today’s technology makes quantum computing a potential game-changer, capable of solving problems that are currently intractable for classical computers.

For investors interested in quantum computing stocks, the sector presents a high-growth, high-risk landscape filled with both opportunities and uncertainties. Many companies in this emerging field are still in the early stages of development but show significant promise in commercial applications. However, the industry also comes with its share of technical challenges, which could impact the growth of quantum computing stocks.

Despite these hurdles, if successfully navigated, the upside for investors could be substantial. Therefore, it is crucial for investors to conduct thorough due diligence, understand the market dynamics, and possibly diversify their investments across different companies focusing on various aspects of quantum computing to mitigate risk. Taking this into consideration, here are three quantum computing stocks to watch in the stock market now.

Quantum Computing Stocks To Watch Right Now

IonQ (IONQ Stock)

Leading off, IonQ Inc. (IONQ) is a leading company in the field of quantum computing. IonQ focuses on the development of quantum hardware and software with the aim of bringing quantum computing into commercial viability. Its proprietary technology aims to build scalable and fault-tolerant quantum computers that promise to outperform classical computing systems in various applications.

Earlier this month, IonQ announced its second quarter 2023 financial results. Diving in, the company posted a loss of $0.16 per share, with revenue of $5.52 million for Q2 2023. This came in line with analysts’ consensus estimates for the quarter which were a loss of $0.16 per share and revenue estimates of $4.35 million. As a result, revenue grew by 111.46% versus the same period, the year prior.

So far in 2023, shares of IONQ stock have surged by a whopping 323.99% year-to-date. Meanwhile, as of this past Friday’s closing bell, IONQ stock is trading at $14.67 a share.

[Read More] 3 REIT Stocks For Your August 2023 Watchlist

Intel Corp. (INTC Stock)

Second, Intel Corporation (INTC) is a multinational technology company. The company is known primarily for its microprocessor chips, Intel has been a leader in the computing industry for decades. The company has recently ventured into emerging technology sectors, including artificial intelligence, cloud computing, and quantum computing.

Back in July, Intel reported a beat for its second quarter 2023 earnings results. In detail, the company notched in Q2 2023 earnings of $0.10 per share, with revenue of $12.95 billion. This is compared to Wall Street’s consensus estimates which were a loss of $0.04 per share, and revenue of $12.08 billion. Though the company beat expectations, revenue fell by 15.48% on a year-over-year basis.

Year-to-date, shares of INTC stock have advanced by 24.39% thus far. Moreover, as of this past Friday’s closing bell, Intel stock closed the day up 2.03% at $33.25 a share.

[Read More] 3 High Yield Dividend Stocks To Watch In August 2023

Honeywell International (HON Stock)

Finally, Honeywell International Inc. (HON) is a diversified technology and manufacturing company. While it operates in multiple sectors including aerospace, building technologies, and safety and productivity solutions, Honeywell has also been actively involved in the development of quantum computing technologies.

At the end of July, Honeywell also reported its second quarter 2023 financial results. In the quarter, the company announced earnings per share of $2.23 with revenue of $9.15 billion. This is in comparison with analysts’ estimates which were earnings of $2.24 per share, on revenue of $9.18 billion. Though, revenue increased by 2.16% versus the same period, the previous year.

YTD, shares of Honeywell International have fallen by 13.07% so far. However, as of the end of the trading day this past Friday, shares of HON stock closed the day modestly higher by 0.62% at $186.30 a share.

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The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.

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Regulatory challenges, especially data privacy and security, may hinder quantum computing adoption.

Research and development are expected to overcome the obstacles in the quantum computing market.

Investments by governments, institutions, and companies are driving innovation in quantum computing.

Partnerships between quantum computing companies, academic institutions, and research organizations are creating opportunities for new quantum hardware and software development.

What are important areas in quantum research?

development of high-level software
implementations of quantum processors

Cloud-based quantum computing services are making the technology more accessible to companies and researchers.