Quantum researchers at the University of Bristol have achieved a billion-fold speedup in simulating optical quantum computers compared to previous approaches.

Their work aids our understanding of what is needed to address global challenges in clean energy and healthcare using quantum computing.

A new technique utilizes lasers as "optical tweezers" to trap atoms for quantum experiments.

The adoption of the Direct Digital Synthesis (DDS) option has allowed rapid research progress by reducing system complexity.

DDS has proven versatile for lab applications, eliminating the need for dedicated equipment for several functions.

Researchers chose Spectrum AWG cards for their excellent analogue performance, large memory, and high data transfer speeds, making them popular for quantum research.

DDS is a widely employed signal generation technique.

A research consortium aims to build the Rymax One QC, a quantum optimizer.

Recent studies show that under some conditions, classical computers can match or outperform quantum computers.

New York University researchers have combined quantum computing and generative AI for drug discovery.

The classic GAN (Generative Adversarial Network) comprises a generator and a discriminator.

Insilico Medicine calls this progress an initial step in a long journey.

IBM’s quantum computing moves are projected to increase demand for industrial space.

The U.S. “China Initiative” led to increased targeting of Chinese-born academics and researchers, resulting in many being dismissed or pressured to leave, raising concerns about international research collaboration.

Intel has introduced a new chip, Tunnel Falls, to advance research in silicon spin qubits for quantum computing.

Silicon spin qubits are up to one million times smaller than other types of qubits, enabling a wider range of quantum experiments and research on qubits and quantum dots.

Advances now allow for greater control over the direction of light emitted from quantum dots.

Quantum researchers at the University of Bristol have achieved a billion-fold speedup in simulating optical quantum computers compared to previous approaches.

Title:

Content: Newswise — Quantum researchers at the University of Bristol have dramatically reduced the time to simulate an optical quantum computer, with a speedup of around one billion over previous approaches.

Quantum computers promise exponential speedups for certain problems, with potential applications in areas from drug discovery to new materials for batteries. But quantum computing is still in its early stages, so these are long-term goals. Nevertheless, there are exciting intermediate milestones on the journey to building a useful device. One currently receiving a lot of attention is “quantum advantage”, where a quantum computer performs a task beyond the capabilities of even the world’s most powerful supercomputers.

Experimental work from the University of Science and Technology of China (USTC) was the first to claim quantum advantage using photons - particles of light, in a protocol called "Gaussian Boson Sampling" (GBS). Their paper claimed that the experiment, performed in 200 seconds, would take 600 million years to simulate on the world's largest supercomputer.

Taking up the challenge, a team at the University of Bristol’s Quantum Engineering Technology Labs (QET Labs), in collaboration with researchers at Imperial College London and Hewlett Packard Enterprise, have reduced this simulation time down to just a few months, a speedup factor of around one billion.

Their paper “The boundary for quantum advantage in Gaussian boson sampling”, published today in the journal Science Advances, comes at a time when other experimental approaches claiming quantum advantage, such as from the quantum computing team at Google, are also leading to improved classical algorithms for simulating these experiments.

Joint first author Jake Bulmer, PhD student in QET Labs, said: “There is an exciting race going on where, on one side, researchers are trying to build increasingly complex quantum computing systems which they claim cannot be simulated by conventional computers. At the same time, researchers like us are improving simulation methods so we can simulate these supposedly impossible to simulate machines!”

“As researchers develop larger scale experiments, they will look to make claims of quantum advantage relative to classical simulations. Our results will provide an essential point of comparison by which to establish the computational power of future GBS experiments,” said joint first author, Bryn Bell, Marie Curie Research Fellow at Imperial College London, now Senior Quantum Engineer at Oxford Quantum Circuits.

The team’s methods do not exploit any errors in the experiment and so one next step for the research is to combine their new methods with techniques that exploit the imperfections of the real-world experiment. This would further speed up simulation time and build a greater understanding of which areas require improvements.

“These quantum advantage experiments represent a tremendous achievement of physics and engineering. As a researcher, it is exciting to contribute to the understanding of where the computational complexity of these experiments arises. We were surprised by the magnitude of the improvements we achieved – it is not often that you can claim to find a one-billion-fold improvement!” said Jake Bulmer.

Anthony Laing, co-Director of QET Labs and an author on the work, said: “As we develop more sophisticated quantum computing technologies, this type of work is vital. It helps us understand the bar we must get over before we can begin to solve problems in clean energy and healthcare that affect us all. The work is a great example of teamwork and collaboration among researchers in the UK Quantum Computing and Simulation Hub and Hewlett Packard Enterprise.”

Further information

The Quantum Engineering Technology Labs (QET Labs) The QET Labs at the University of Bristol launched in April 2015 and encompass the activity of over 100 academics, staff and students. The aim is to maximise opportunities for new scientific discoveries that underpin engineering and technology development. The QET Labs bring together the Quantum Engineering Centre for Doctoral Training (QE-CDT), the Quantum Technology Enterprise Centre (QTEC) and the research teams of their staff and students. Working together, we aim to transform science into real concept demonstrators and entrepreneurial innovation that will be the springboard for the commercial success of quantum technologies.

Bristol Quantum Information Institute

Quantum information and its translation into technologies is one of the most exciting research activities in science and technology today. Long at the forefront of the growing worldwide activity in this area, the Bristol Quantum Information Institute crystallises our research across the entire spectrum, from theory to technology. With our expert cross-disciplinary team, including founders of the field, we have expertise in all major areas of theoretical quantum information science and in experiment. We foster partnerships with the private sector and provide superb teaching and training for the future generation of quantum scientists and engineers and the prototypes of tomorrow.

The Quantum Computing & Simulation Hub

The Quantum Computing & Simulation Hub (QCS) is a collaboration between 17 UK universities, working with an extensive network of academic, industrial, and governmental partners. It is one of four hubs in the UK National Quantum Technologies Programme, which represents £1 billion of public and private investment to accelerate the translation of quantum technologies into the marketplace. The Hub is focused on the critical research challenges for quantum computing, across a broad range of hardware and software disciplines. As well as addressing the technical challenges in providing quantum computing and simulation at scale, the Hub engages with industries, end users, government, and citizens to help the UK become ‘quantum ready’. For more information visit https://www.qcshub.org

MEDIA CONTACT
Register for reporter access to contact details
CITATIONS

Science Advances

What advantages do quantum computers have over conventional computers?

What are important areas in quantum research?

What countries and blocs are leading in developing quantum computing?

Their work aids our understanding of what is needed to address global challenges in clean energy and healthcare using quantum computing.

Title:

Content: University Kaiserslautern fast tracks Quantum Computer development with new DDS firmware option

Graduate physicist Jonas Witzenrath at the quantum experimental setup of University Kaiserslautern, Germany

The acousto-optic deflector (AOD, red arrow) splits one laser beam into many controllable single beams which catch and hold the atoms

Widely used by quantum researchers around the word: The M4i.6631-x8 Arbitrary Waveform Generator with 1.25 GS/s sampling speed, 16-bit resolution and 2 channels

AWG cards by Spectrum Instrumentation used to position atoms as qubits in an optical tweezer array

Spectrum AWG cards were chosen as they are becoming the solution of choice for quantum research due to their great analogue performance paired with large memory and high transfer speed onto the card.”
— Dipl.-Phys. Jonas Witzenrath
GROSSHANSDORF, GERMANY, June 12, 2024 /EINPresswire.com/ -- There are many ways to build a Quantum Computer (QC) and RPTU Kaiserslautern’s approach within the Rymax One collaboration is to create an array of single atoms that act as qubits. The challenge is moving and holding each atom in its precise location. This is done by using a laser on each atom that traps it into the center of the laser beam effectively acting as an optical tweezer. However, point-by-point programming of each movement of the beam currently requires a lot of programming and a huge amount of data. This has now been cut dramatically with the use of the new Direct Digital Synthesis (DDS) firmware option from Spectrum Instrumentation so that the position of the lasers can be controlled with a few simple commands that define the start and stop parameters instead of making time consuming, large data array calculations.

Dipl.-Phys. Jonas Witzenrath said, “This is making a huge difference to the progress of our research. Using the new DDS option, we have been able to make rapid progress and reduce the complexity in the system allowing us to focus on advancing the research. The next step is to do the reordering of atoms in a static two-dimensional array using the dynamic capabilities of the DDS-firmware." Furthermore, in the next phase, they will use the AWGs to shape ideal UV laser pulses for precisely controlling interactions between qubits.

“DDS has become a vital tool in our project and we are finding that it can actually be used in other things in the lab as it is very flexible and can be used for other functions so we don’t have to buy dedicated equipment for them. For example, pulsed lasers, chirp generation, etc. We worked very closely with Spectrum to develop this DDS feature and are now working on expanding its possible uses in research so that it can help other laboratories.”

He added that the Spectrum AWG cards were chosen as they are becoming the solution of choice for quantum research due to their great analogue performance paired with large memory and high transfer speed onto the card. The latter is crucial as the experiment has to pause until the re-ordering waveforms are computed and uploaded onto the cards. The transfer speed sets the Spectrum AWG cards apart from other products and that is the main reason why they are widely used in the AMO/QC community. The speed of the card’s operation was also very important. Fast AWGs have the intrinsic problem of latencies on the order of tens of milliseconds or large jitter which results in inaccuracies and longer processing times as the system corrects and recorrects. The DDS firmware enables Spectrum’s AWGs to generate commands within twenty microsecond and, due to the intrinsic timing, the commands are practically jitter-free.

In one example experiment, the Spectrum Instrumentation AWG card M4i.6631-x8 is used to drive an AOD (Acousto-Optic Deflector) that generates a tweezer to trap the atoms. The AOD is driven with an RF-signal with a frequency around 82 MHz. With their current setup, a change of 1 MHz moves the tweezer with an atom by about 8 μm within 100 μs, using s-shaped frequency ramps to minimize heating. During this time, the amplitude of the signal is linearly changed to compensate for changes in light intensity.

The DDS firmware option
DDS is a method for generating arbitrary periodic sine waves from a single, fixed-frequency reference clock. It is a technique widely used in a variety of signal generation applications. The new option by Spectrum Instrumentation allows users to define 23 DDS cores per AWG card, that can be routed to the hardware output channels. Each DDS core (sine wave) can be programmed for frequency, amplitude, phase, frequency slope and amplitude slope. The DDS output can be synchronized with external trigger events or by a programmable timer with a resolution of 6.4 ns.

In DDS-mode, the AWG acts as a generator for the multi-tone DDS signal. The unit’s built-in 4 GByte of memory and fast DMA transfer mode then allows the streaming of DDS commands at a rate as high as 10 million commands per second! This unique capability provides the flexibility to perform user-defined slopes (e.g. s-shaped) as well as various modulation types (e.g. FM and AM) with simple, easy-to-use, DDS commands.

The Rymax One QC design
Since 2021, Spectrum Instrumentation and the University Kaiserslautern have been part of the BMBF (German federal ministry of education and research) funding program ‘quantum technologies – from basic research to market’ as part of the Rymax One consortium. The aim of this consortium is building a Quantum Optimizer. For this purpose, individual Ytterbium atoms are suspended in a vacuum in a Rydberg state using optical tweezers. The Rymax collaboration specifically focuses on quantum optimization problems, such as the Maximum Independent Set problem, and algorithms such QAOA or quantum annealing to find solutions. This allows them to build optimized hardware for “analog” quantum computing. One key-aspect of the design is dynamic control over (UV-)laser light, for which full control over the different RF-signals is required. This is where Spectrum Instrumentation’s long-standing expertise is valuable.

Sven Harnisch
Spectrum Instrumentation
+49 4102 69560
info@spec.de
Visit us on social media:
LinkedIn

A new technique utilizes lasers as "optical tweezers" to trap atoms for quantum experiments.

The adoption of the Direct Digital Synthesis (DDS) option has allowed rapid research progress by reducing system complexity.

DDS has proven versatile for lab applications, eliminating the need for dedicated equipment for several functions.

Researchers chose Spectrum AWG cards for their excellent analogue performance, large memory, and high data transfer speeds, making them popular for quantum research.

DDS is a widely employed signal generation technique.

A research consortium aims to build the Rymax One QC, a quantum optimizer.

What are important areas in quantum research?

Recent studies show that under some conditions, classical computers can match or outperform quantum computers.

Title:

Content: New! Sign up for our free email newsletter.
Science News
from research organizations

Researchers show classical computers can keep up with, and surpass, their quantum counterparts

Researchers adopt innovative method to boost speed and accuracy of traditional computing

Date:
February 9, 2024
Source:
New York University
Summary:
A team of scientists has devised means for classical computing to mimic a quantum computing with far fewer resources than previously thought. The scientists' results show that classical computing can be reconfigured to perform faster and more accurate calculations than state-of-the-art quantum computers.
Share:
FULL STORY

Quantum computing has been hailed as a technology that can outperform classical computing in both speed and memory usage, potentially opening the way to making predictions of physical phenomena not previously possible.

Many see quantum computing's advent as marking a paradigm shift from classical, or conventional, computing. Conventional computers process information in the form of digital bits (0s and 1s), while quantum computers deploy quantum bits (qubits) to store quantum information in values between 0 and 1. Under certain conditions this ability to process and store information in qubits can be used to design quantum algorithms that drastically outperform their classical counterparts. Notably, quantum's ability to store information in values between 0 and 1 makes it difficult for classical computers to perfectly emulate quantum ones.

However, quantum computers are finicky and have a tendency to lose information. Moreover, even if information loss can be avoided, it is difficult to translate it into classical information -- which is necessary to yield a useful computation.

Classical computers suffer from neither of those two problems. Moreover, cleverly devised classical algorithms can further exploit the twin challenges of information loss and translation to mimic a quantum computer with far fewer resources than previously thought -- as recently reported in a research paper in the journal PRX Quantum.

The scientists' results show that classical computing can be reconfigured to perform faster and more accurate calculations than state-of-the-art quantum computers.

This breakthrough was achieved with an algorithm that keeps only part of the information stored in the quantum state -- and just enough to be able to accurately compute the final outcome.

"This work shows that there are many potential routes to improving computations, encompassing both classical and quantum approaches," explains Dries Sels, an assistant professor in New York University's Department of Physics and one of the paper's authors. "Moreover, our work highlights how difficult it is to achieve quantum advantage with an error-prone quantum computer."

In seeking ways to optimize classical computing, Sels and his colleagues at the Simons Foundation focused on a type of tensor network that faithfully represents the interactions between the qubits. Those types of networks have been notoriously hard to deal with, but recent advances in the field now allow these networks to be optimized with tools borrowed from statistical inference.

The authors compare the work of the algorithm to the compression of an image into a JPEG file, which allows large images to be stored using less space by eliminating information with barely perceivable loss in the quality of the image.

"Choosing different structures for the tensor network corresponds to choosing different forms of compression, like different formats for your image," says the Flatiron Institute's Joseph Tindall, who led the project. "We are successfully developing tools for working with a wide range of different tensor networks. This work reflects that, and we are confident that we will soon be raising the bar for quantum computing even further."

The work was supported by the Flatiron Institute and a grant from the Air Force Office of Scientific Research (FA9550-21-1-0236).

Story Source:

Materials provided by New York University. Note: Content may be edited for style and length.

Journal Reference:

  1. Joseph Tindall, Matthew Fishman, E. Miles Stoudenmire, Dries Sels. Efficient Tensor Network Simulation of IBM’s Eagle Kicked Ising Experiment. PRX Quantum, 2024; 5 (1) DOI: 10.1103/PRXQuantum.5.010308

Cite This Page:

New York University. "Researchers show classical computers can keep up with, and surpass, their quantum counterparts." ScienceDaily. ScienceDaily, 9 February 2024. <www.sciencedaily.com/releases/2024/02/240209134402.htm>.
New York University. (2024, February 9). Researchers show classical computers can keep up with, and surpass, their quantum counterparts. ScienceDaily. Retrieved February 9, 2024 from www.sciencedaily.com/releases/2024/02/240209134402.htm
New York University. "Researchers show classical computers can keep up with, and surpass, their quantum counterparts." ScienceDaily. www.sciencedaily.com/releases/2024/02/240209134402.htm (accessed February 9, 2024).

Explore More
from ScienceDaily

RELATED STORIES

New York University researchers have combined quantum computing and generative AI for drug discovery.

Title:

Content:
This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility:

fact-checked

peer-reviewed publication

trusted source

proofread

Study combines quantum computing and generative AI for drug discovery

Insilico Medicine, a clinical stage generative artificial intelligence (AI)-driven drug discovery company, today announced that it combined two rapidly developing technologies, quantum computing and generative AI, to explore lead candidate discovery in drug development and successfully demonstrated the potential advantages of quantum generative adversarial networks in generative chemistry.

The study, published in the Journal of Chemical Information and Modeling, was led by Insilico's Taiwan and UAE centers which focus on pioneering and constructing breakthrough methods and engines with rapidly developing technologies—including generative AI and —to accelerate drug discovery and development.

The research was supported by University of Toronto Acceleration Consortium director Alán Aspuru-Guzik, Ph.D., and scientists from the Hon Hai (Foxconn) Research Institute.

"This was a very fun project," said Alán Aspuru-Guzik, director of the Acceleration Consortium and professor of computer science and chemistry at the University of Toronto. "It sets the stage for further developments in AI as it meets drug discovery. This is a global collaboration where Foxconn, Insilico, Zapata Computing, and University of Toronto are working together."

Generative Adversarial Networks (GANs) are one of the most successful generative models in drug discovery and design and have shown remarkable results for generating data that mimics a data distribution in different tasks. The classic GAN model consists of a generator and a discriminator. The generator takes random noises as input and tries to imitate the data distribution, and the discriminator tries to distinguish between the fake and real samples. A GAN is trained until the discriminator cannot distinguish the generated data from the real data.

In this paper, researchers explored the quantum advantage in small molecule drug discovery by substituting each part of MolGAN, an implicit GAN for small molecular graphs, with a variational quantum circuit (VQC), step by step, including as the noise generator, generator with the patch method, and quantum discriminator, comparing its performance with the classical counterpart.

The study not only demonstrated that the trained quantum GANs can generate training-set-like molecules by using the VQC as the noise generator, but that the quantum generator outperforms the classical GAN in the drug properties of generated compounds and the goal-directed benchmark.

In addition, the study showed that the quantum discriminator of GAN with only tens of learnable parameters can generate valid molecules and outperforms the classical counterpart with tens of thousands parameters in terms of generated molecule properties and KL-divergence score.

"Quantum computing is recognized as the next technology breakthrough which will make a great impact, and the is believed to be among the first wave of industries benefiting from the advancement," said Jimmy Yen-Chu Lin, Ph.D., GM of Insilico Medicine Taiwan and corresponding author of the paper. "This paper demonstrates Insilico's first footprint in quantum computing with AI in molecular generation, underscoring our vision in the field."

Building on these findings, Insilico scientists plan to integrate the hybrid quantum GAN model into Chemistry42, the Company's proprietary small molecule generation engine, to further accelerate and improve its AI-driven and development process.

Insilico was one of the first to use GANs in de novo molecular design, and published the first paper in this field in 2016. The Company has delivered 11 preclinical candidates by GAN-based generative AI models and its lead program has been validated in Phase I clinical trials.

"I am proud of the positive results our quantum computing team has achieved through their efforts and innovation," said Alex Zhavoronkov, Ph.D., founder and CEO of Insilico Medicine. "I believe this is the first small step in our journey. We are currently working on a breakthrough experiment with a real quantum computer for chemistry and look forward to sharing Insilico's best practices with industry and academia."

More information: Po-Yu Kao et al, Exploring the Advantages of Quantum Generative Adversarial Networks in Generative Chemistry, Journal of Chemical Information and Modeling (2023). DOI: 10.1021/acs.jcim.3c00562

The data acquisition code and source codes associated with this study are publicly available at: github.com/pykao/QuantumMolGAN-PyTorch

Provided by Insilico Medicine

Citation: Study combines quantum computing and generative AI for drug discovery (2023, May 19) retrieved 19 May 2023 from https://phys.org/news/2023-05-combines-quantum-generative-ai-drug.html
This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only.

Explore further

New study uses AlphaFold and AI to accelerate design of novel drug for liver cancer

0 shares

Feedback to editors

What countries and blocs are leading in developing quantum computing?

What fields can quantum computers advance?

The classic GAN (Generative Adversarial Network) comprises a generator and a discriminator.

Insilico Medicine calls this progress an initial step in a long journey.

IBM’s quantum computing moves are projected to increase demand for industrial space.

Title:

Content: IBM’s Quantum Computing Moves Could Put Industrial Space in Demand

IBM's quantum computing advancements and industrial collaborations are set to boost demand for specialized industrial spaces, transforming sectors like materials science and supply chain logistics.

IBM’s aggressive expansion in quantum computing is set to significantly impact various industries, potentially increasing the demand for industrial space. The company has been at the forefront of quantum research and development, advancing both its hardware and software capabilities. IBM’s recent developments in their Qiskit software stack, which includes over 100 updates, are aimed at enhancing the performance and usability of quantum circuits. These advancements are crucial for the optimization and execution of quantum algorithms, making them more accessible and practical for industrial applications.

Key Partnerships and Industrial Applications

IBM has partnered with major industry players to explore practical applications of quantum computing. For instance, Bosch has joined forces with IBM to utilize quantum computing for materials science research. This collaboration aims to develop new materials for applications such as electromobility and renewable energy, areas where classical computers fall short. The potential to design materials with higher energy efficiency and reduced resource consumption could revolutionize these sectors.

Impact on Supply Chain and Logistics

Quantum computing is poised to transform supply chain management by enhancing modeling capabilities. The complexity of supply chain models, which involve numerous variables, can be better managed with quantum computing. This technology promises to optimize logistics, improve data sharing security, and facilitate digital twin simulations. IBM’s quantum advancements could thus lead to more efficient and resilient supply chains, further driving the demand for industrial space to house these advanced computing facilities.

The Future of Quantum Computing

IBM’s roadmap includes the development of a 4,000-qubit system by 2025, which underscores the company’s commitment to scaling quantum computing capabilities. This modular architecture will enable the integration of quantum and classical computing resources, opening new frontiers in high-performance computing. As these systems become operational, industries will increasingly require specialized facilities to host and manage these advanced quantum computers, driving a surge in demand for industrial real estate.

About the author

Vishal Jain

Vishal’s reviews provide a comprehensive look at the latest software and apps in the market. His hands-on approach and detailed analysis help readers make informed decisions about the tools they use daily.

The U.S. “China Initiative” led to increased targeting of Chinese-born academics and researchers, resulting in many being dismissed or pressured to leave, raising concerns about international research collaboration.

Title:

Content: Why Trump's anti-spy 'China Initiative' is unraveling

·8 min read

After conducting days of surveillance, performing DNA tests on a hard drive that was fished out of a dumpster, and searching through personal emails, FBI officials became convinced that visiting UCLA researcher Guan Lei belonged to the Chinese military and might be stealing American industrial secrets.

They couldn’t nail down evidence of espionage but secured an indictment against Guan for allegedly lying about having secret ties to the People’s Liberation Army. He was charged with visa fraud, making false statements and destroying evidence.

For more than eight months, the 30-year-old computer science PhD student sat in a cell at Metropolitan Detention Center in downtown Los Angeles awaiting trial.

But in a sudden turnaround in late July, U.S. authorities summarily dismissed all charges. The Justice Department gave no explanation, issuing a brief statement that it had reevaluated the case, along with several others, and determined that “it is now in the interest of justice” to drop the matter.

Guan’s was one of five similar prosecutions against Chinese researchers — all but one in California — that were dropped over a two-day period in July. Earlier in the month, Justice officials dismissed charges against a Chinese American researcher in Cleveland accused of failing to disclose his affiliation with a Chinese university from which he had received funding.

And this month, a federal judge acquitted Anming Hu, a Chinese Canadian engineering professor in Tennessee, of charges stemming from allegations that he hid his joint academic appointment in China in obtaining research funding from NASA.

All seven failed prosecutions were part of the so-called China Initiative, a sweeping program launched in November 2018 under the Trump administration to counter theft of trade secrets, hacking and economic espionage.

Michael German, a former FBI agent who serves as a fellow for the Brennan Center for Justice’s Liberty & National Security Program, said the recent dismissals revealed how weak many of the cases were.

“Obviously, the FBI and Justice Department are under pressure to produce indictments against people with a so-called ‘nexus to China’ to match the political rhetoric sensationalizing the espionage threat from the Chinese government,” he said. “Even FBI analysts appear to have felt the investigators' effort to connect these defendants to the Chinese military was overwrought.”

So what went wrong?

The problem was, and remains, serious. China’s history of stealing manufacturing secrets and other valuable information that U.S. companies spent millions of dollars to develop has been a significant spur to the virtual cold war that has developed between Washington and Beijing. It has put increasing pressure on government officials to do more to stanch the flow.

Although much remains unknown about the Trump-era campaign, it appears that a major problem was its decision to focus on Chinese nationals and Chinese Americans working in major U.S. research universities.

Not only did that approach fail to turn up persuasive evidence of spying — most of the charges involved making false statements to government authorities, or tax and visa fraud — but the emphasis on going after a small number of individuals for academic fraud seemed too small-scale to make a dent in a massive problem — the equivalent of trying to win the war on drugs by rounding up a handful of street dealers.

“What I see from the outside is that the bureau [FBI] and the Department of Justice have almost routinely pursued cases for something other than economic espionage, so they’re not contributing that much to the wealth of information of what China is trying to do. Nor are they pursuing cases with the biggest bite,” said Mark Allen Cohen, a former senior intellectual property attaché at the U.S. Embassy in Beijing and now senior fellow at the Berkeley Center for Law and Technology.

Moreover, the FBI’s tactics struck many Asian Americans as heavy-handed and discriminatory. The campaign came at a time when Asian Americans across the country were under attack with hate crimes.

Defending the program, FBI Director Christopher Wray warned that Beijing, in its effort to overtake the U.S. economy, had resorted to industrial espionage using “non-traditional collectors” such as researchers and graduate students.

He told a China Initiative conference last year that the FBI had about 1,000 investigations involving China’s attempt to steal U.S.-based technology. In April, the director testified before Congress that the bureau had about 2,000 open cases of economic espionage that “tie back to the Chinese government,” representing a 1,300% increase over the last few years.

But in the nearly three years since the program’s launch, the China Initiative has brought just 12 prosecutions of people at academic institutions and has won convictions of four individuals, according to Justice Department statistics provided to the Los Angeles Times.

In none of those four cases did the government provide evidence of economic espionage or theft of trade secrets or intellectual property.

Apart from the university cases, Justice officials have obtained four convictions or guilty pleas out of 16 prosecutions involving economic espionage and trade-secret theft matters since November 2018.

Various U.S. lawmakers, academics and rights groups have called for an end to the initiative. They say the program has cast unfair suspicion on people of Chinese and Asian descent and contributed to racial profiling on campuses, chilled international research collaboration and, in the case of Hu and a number of others, ruined careers and personal lives.

“I think that they are just set on their desire to find spies,” said Rep. Judy Chu (D-Monterey Park), who as chair of the Congressional Asian Pacific American Caucus has raised concerns to President Biden.

Justice officials have said the U.S. government needs to be aggressive in countering the serious economic threat posed by China.

In a statement attributed to spokesman Wyn Hornbuckle, the department said it was taking seriously the problem of rising hate crimes targeting Asians in America and was working with communities to improve its efforts.

President Biden has said nothing specifically about the China Initiative.

In a letter to U.S. Atty Gen. Merrick Garland in July, Rep. Ted Lieu (D-Torrance) and 90 other members of Congress asked for an investigation into the wrongful targeting of people of Asian descent, and for an update on department-wide implicit bias training that was mandated in 2016.

“I wonder if the China Initiative is simply another manifestation of discrimination we’ve seen against Asian Americans” in U.S. history, he said, recalling the Chinese Exclusion Act of 1882, the internment of Japanese Americans during World War II and other incidents. Others say the initiative has echoes of the scrutiny on Muslim Americans after 9/11.

Daniel Olmos, a Silicon Valley trial attorney who worked on the first economic espionage case of a Chinese American to go to jury trial, said he'd seen a dramatic increase in the number of Chinese-born professors and research fellows who had been targeted and that he himself had counseled as many as 10 of them. In almost all of those cases, he said, the individuals have been fired or pressured to leave.

“I just think it’s a shakedown, and the endgame appears to me to get them fired,” Olmos said of the China Initiative’s efforts at universities.

The Justice Department’s move to dismiss charges against Guan and four others came after internal reports by FBI analysts noted that Chinese citizens could be affiliated with the People's Liberation Army's civilian service and that, in itself, "remains an unreliable indicator of nefarious obfuscation of one's military affiliations, and even less of an indicator of technology transfer activity."

In Guan’s case, FBI agents built their case after learning that Guan had received a scholarship linked to the PLA and uncovered photos of Guan’s university advisor in China in full military uniform.

In a late-night interview, agents repeatedly pressed Guan when he said he wore a green uniform for about a month of military training for students at his school, the National University of Defense Technology, according to an FBI interview transcript.

At UCLA, Guan worked in a lab supervised by then-math professor Wotao Yin, who told the FBI that Guan did not work on any U.S.-government funded projects and that there wasn’t any research worth taking.

“Guan wrote code, always from public data sets. … Guan’s code was the most advanced, if anything people would steal Guan’s code and not the code made by others,” Yin said, according to FBI interview notes.

Guan, who insisted he had no ties to the Chinese military, was at once surprised and relieved when he was freed. But before returning home, he filed with the court a response to the government’s dismissal motion.

“It’s truly a terrible experience for me,” he said.

Times staff writer Del Quentin Wilber in Washington contributed to this report.

This story originally appeared in Los Angeles Times.

Intel has introduced a new chip, Tunnel Falls, to advance research in silicon spin qubits for quantum computing.

Title:

Content: Intel's New Chip to Advance Silicon Spin Qubit Research for Quantum Computing

52 minutes ago

What’s New: Today, Intel announced the release of its newest quantum research chip, Tunnel Falls, a 12-qubit silicon chip, and it is making the chip available to the quantum research community. In addition, Intel is collaborating with the Laboratory for Physical Sciences (LPS) at the University of Maryland, College Park’s Qubit Collaboratory (LQC), a national-level Quantum Information Sciences (QIS) Research Center, to advance quantum computing research.

This press release features multimedia. View the full release here: https://www.businesswire.com/news/home/20230615304303/en/

A photo shows one of Intel's Tunnel Falls chips on a human finger to display its scale. Silicon spin qubits are up to 1 million times smaller than other qubit types. The Tunnel Falls chip measures approximately 50-nanometers square, potentially allowing for faster scaling. (Credit: Intel Corporation)

“Tunnel Falls is Intel’s most advanced silicon spin qubit chip to date and draws upon the company’s decades of transistor design and manufacturing expertise. The release of the new chip is the next step in Intel’s long-term strategy to build a full-stack commercial quantum computing system. While there are still fundamental questions and challenges that must be solved along the path to a fault-tolerant quantum computer, the academic community can now explore this technology and accelerate research development.”
–Jim Clarke, director of Quantum Hardware, Intel

Why It Matters: Currently, academic institutions don’t have high-volume manufacturing fabrication equipment like Intel. With Tunnel Falls, researchers can immediately begin working on experiments and research instead of trying to fabricate their own devices. As a result, a wider range of experiments become possible, including learning more about the fundamentals of qubits and quantum dots and developing new techniques for working with devices with multiple qubits.

To further address this, Intel is collaborating with LQC as part of the Qubits for Computing Foundry (QCF) program through the U.S. Army Research Office to provide Intel’s new quantum chip to research laboratories. The collaboration with LQC will help democratize silicon spin qubits by enabling researchers to gain hands-on experience working with scaled arrays of these qubits. The initiative aims to strengthen workforce development, open the doors to new quantum research and grow the overall quantum ecosystem.

The first quantum labs to participate in the program include LPS, Sandia National Laboratories, the University of Rochester, and the University of Wisconsin-Madison. LQC will work alongside Intel to make Tunnel Falls available to additional universities and research labs. The information gathered from these experiments will be shared with the community to advance quantum research and to help Intel improve qubit performance and scalability.

“The LPS Qubit Collaboratory, in partnership with the Army Research Office, seeks to tackle the hard challenges facing qubit development and develop the next generation of scientists who will create the qubits of tomorrow,” said Charles Tahan, chief of Quantum Information Science, LPS. “Intel’s participation is a major milestone to democratizing the exploration of spin qubits and their promise for quantum information processing and exemplifies LQC’s mission to bring industry, academia, national labs, and government together.”

Dr. Dwight Luhman, distinguished member of Technical Staff at Sandia National Laboratories, said, “Sandia National Laboratories is excited to be a recipient of the Tunnel Falls chip. The device is a flexible platform enabling quantum researchers at Sandia to directly compare different qubit encodings and develop new qubit operation modes, which was not possible for us previously. This level of sophistication allows us to innovate novel quantum operations and algorithms in the multi-qubit regime and accelerate our learning rate in silicon-based quantum systems. The anticipated reliability of Tunnel Falls will also allow Sandia to rapidly onboard and train new staff working in silicon qubit technologies.“

Mark A. Eriksson, department chair and John Bardeen Professor of Physics, Department of Physics, University of Wisconsin-Madison, said, “UW-Madison researchers, with two decades of investment in the development of silicon qubits, are very excited to partner in the launch of the LQC. The opportunity for students to work with industrial devices, which benefit from Intel’s microelectronics expertise and infrastructure, opens important opportunities both for technical advances and for education and workforce development.”

About Tunnel Falls: Tunnel Falls is Intel’s first silicon spin qubit device released to the research community. Fabricated on 300-millimeter wafers in the D1 fabrication facility, the 12-qubit device leverages Intel’s most advanced transistor industrial fabrication capabilities, such as extreme ultraviolet lithography (EUV) and gate and contact processing techniques. In silicon spin qubits, information (the 0/1) is encoded in the spin (up/down) of a single electron. Each qubit device is essentially a single electron transistor, which allows Intel to fabricate it using a similar flow to that used in a standard complementary metal oxide semiconductor (CMOS) logic processing line.

Intel believes silicon spin qubits are superior to other qubit technologies because of their synergy with leading-edge transistors. Being the size of a transistor, they are up to 1 million times smaller than other qubit types measuring approximately 50 nanometers by 50 nanometers, potentially allowing for efficient scaling. According to Nature+Electronics, “Silicon may be the platform with the greatest potential to deliver scaled-up quantum computing.”

At the same time, utilizing advanced CMOS fabrication lines allows Intel to use innovative process control techniques to enable yield and performance. For example, the Tunnel Falls 12 qubit device has a 95%25+yield+rate+across+the+wafer and voltage uniformity similar to a CMOS logic process, and each wafer provides over 24,000 quantum dot devices. These 12-dot chips can form between four to 12 qubits that can be isolated and used in operations simultaneously depending on how the university or lab operates its systems.

What’s Next: Intel will continuously work to improve the performance of Tunnel Falls and integrate it into its full quantum stack with the Intel Quantum Software Development Kit (SDK). In addition, Intel is already developing its next-generation quantum chip based on Tunnel Falls; it is expected to be released in 2024. In the future, Intel plans to partner with additional research institutions globally to build the quantum ecosystem.

More Context: Intel+Labs+Quantum+Computing+Backgrounder | Intel+Labs (Press Kit) | Intel+Quantum+Researchers+Introduce+Tunnel+Falls+Silicon+Qubit+Research+Chip (Video) | Intel+Introduces+Tunnel+Falls+Silicon+Qubit+Research+Chip (Video) | Quantum+Computing+Laboratory+in+Oregon (B-Roll Video)

About Intel

Intel (Nasdaq: INTC) is an industry leader, creating world-changing technology that enables global progress and enriches lives. Inspired by Moore’s Law, we continuously work to advance the design and manufacturing of semiconductors to help address our customers’ greatest challenges. By embedding intelligence in the cloud, network, edge and every kind of computing device, we unleash the potential of data to transform business and society for the better. To learn more about Intel’s innovations, go to newsroom.intel.com and intel.com.

© Intel Corporation. Intel, the Intel logo and other Intel marks are trademarks of Intel Corporation or its subsidiaries. Other names and brands may be claimed as the property of others.

View source version on businesswire.com: https://www.businesswire.com/news/home/20230615304303/en/

Rating:
NaN / 5 ( votes)

What are important areas in quantum research?

implementations of quantum processors
new types of qubits

What companies are leading in developing quantum computing?

Silicon spin qubits are up to one million times smaller than other types of qubits, enabling a wider range of quantum experiments and research on qubits and quantum dots.

What are important areas in quantum research?

Advances now allow for greater control over the direction of light emitted from quantum dots.

Title:

Content:
This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility:

fact-checked

peer-reviewed publication

trusted source

proofread

New method integrates quantum dots with metasurfaces for enhanced luminescence

A study published in Nano Letters demonstrates the use of quantum dots to create metasurfaces, enabling two objects to exist in the same space.

Pohang University of Science and Technology (POSTECH) researchers employed Nanoimprint Lithography (NIL) to fabricate metasurfaces embedded with , enhancing their luminescence efficiency. The team included Professor Junsuk Rho from the Department of Mechanical Engineering, the Department of Chemical Engineering, and the Department of Electrical Engineering, Ph.D. candidates Minsu Jeong, Byoungsu Ko, and Jaekyung Kim from the Department of Mechanical Engineering, and Chunghwan Jung, a Ph.D. candidate, from the Department of Chemical Engineering.

NIL, a process for creating , utilizes patterned stamps to quickly transfer intricate patterns at the nanometer (nm) scale. This method offers cost advantages over and other processes. It has the advantage of enabling the creation of metasurfaces using materials that are not available in conventional processes.

Metasurfaces have recently been the focus of extensive research for their ability to control the polarization and emission direction of light from quantum dots.

Quantum dots, which are nanoscale semiconductor particles, are highly efficient light emitters capable of emitting light at precise wavelengths. This makes them widely used in applications such as QLEDs and quantum computing. However, conventional processes cannot embed quantum dots within metasurfaces.

As a result, research has often involved fabricating metasurfaces and quantum dots separately and then combining them, which imposes limitations on controlling the luminescence of the quantum dots.

In this study, the researchers integrated quantum dots with (TiO2), a material used in the NIL process, to create a metasurface. Unlike conventional methods, which involve separately fabricating the metasurface and quantum dots before combining them, this approach embeds the quantum dots directly within the metasurface during its creation.

The resulting metasurface enhances the proportion of photons emitted from the quantum dots that couple with the resonance mode of the metasurface. This advancement allows for more effective control over the specific direction of light emitted from the quantum dots compared to previous methods.

Experiments demonstrated that the more photons emitted from the quantum dots that were coupled to the resonant modes of the metasurface, the higher the luminescence efficiency. The team's metasurface achieved up to 25 times greater luminescence efficiency compared to a simple coating of quantum dots.

Professor Rho, who led the research, said, "The use of luminescence-controlled metasurfaces will enable sharper, brighter displays and more precise, sensitive biosensing. Further research will allow us to control luminescence more effectively, leading to advances in areas such as nano-optical sensors, optoelectronic devices, and quantum dot displays."

More information: Minsu Jeong et al, Printable Light-Emitting Metasurfaces with Enhanced Directional Photoluminescence, Nano Letters (2024). DOI: 10.1021/acs.nanolett.4c00871

Journal information: Nano Letters

Citation: New method integrates quantum dots with metasurfaces for enhanced luminescence (2024, June 12) retrieved 12 June 2024 from https://phys.org/news/2024-06-method-quantum-dots-metasurfaces-luminescence.html
This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only.

Explore further

New quantum dot approach can enhance electrical conductivity of solar cells

0 shares

Feedback to editors