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Artists illustration of ghost particles moving through a quantum spin liquid. Credit: Jenny Nuss/Berkeley Lab

An unexpected finding by scientists at Berkeley Lab and UC Berkeley could advance quantum computers and high-temperature superconductors.

Scientists have taken the clearest picture yet of electronic particles that make up a mysterious magnetic state called a quantum spin liquid (QSL).

The achievement could facilitate the development of superfast quantum computers and energy-efficient superconductors.

The scientists are the first to capture an image of how electrons in a QSL decompose into spin-like particles called spinons and charge-like particles called chargons.

Artists illustration of ghost particles moving through a quantum spin liquid. Credit: Jenny Nuss/Berkeley Lab

Other studies have seen various footprints of this phenomenon, but we have an actual picture of the state in which the spinon lives. This is something new, said study leader Mike Crommie, a senior faculty scientist at Lawrence Berkeley National Laboratory (Berkeley Lab) and physics professor at UC.

Spinons are like ghost particles. They are like the Big Foot of quantum physics people say that theyve seen them, but its hard to prove that they exist, said co-author Sung-Kwan Mo, a staff scientist at Berkeley Labs Advanced Light Source. With our method weve provided some of the best evidence to date.

In a QSL, spinons freely move about carrying heat and spin but no electrical charge. To detect them, most researchers have relied on techniques that look for their heat signatures.

Now, as reported in the journal Nature Physics, Crommie, Mo, and their research teams have demonstrated how to characterize spinons in QSLs by directly imaging how they are distributed in a material.

Schematic of the triangular spin lattice and star-of-David charge density wave pattern in a monolayer of tantalum diselenide. Each star consists of 13 tantalum atoms. Localized spins are represented by a blue arrow at the star center. The wavefunction of the localized electrons is represented by gray shading. Credit: Mike Crommie et al./Berkeley Lab

To begin the study, Mos group at Berkeley Labs Advanced Light Source (ALS) grew single-layer samples of tantalum diselenide (1T-TaSe2) that are only three-atoms thick. This material is part of a class of materials called transition metal dichalcogenides (TMDCs). The researchers in Mos team are experts in molecular beam epitaxy, a technique for synthesizing atomically thin TMDC crystals from their constituent elements.

Mos team then characterized the thin films through angle-resolved photoemission spectroscopy, a technique that uses X-rays generated at the ALS.

Scanning tunneling microscopy image of a tantalum diselenide sample that is just 3 atoms thick. Credit: Mike Crommie et al./Berkeley Lab

Using a microscopy technique called scanning tunneling microscopy (STM), researchers in the Crommie lab including co-first authors Wei Ruan, a postdoctoral fellow at the time, and Yi Chen, then a UC Berkeley graduate student injected electrons from a metal needle into the tantalum diselenide TMDC sample.

Images gathered by scanning tunneling spectroscopy (STS) an imaging technique that measures how particles arrange themselves at a particular energy revealed something quite unexpected: a layer of mysterious waves having wavelengths larger than one nanometer (1 billionth of a meter) blanketing the materials surface.

The long wavelengths we saw didnt correspond to any known behavior of the crystal, Crommie said. We scratched our heads for a long time. What could cause such long wavelength modulations in the crystal? We ruled out the conventional explanations one by one. Little did we know that this was the signature of spinon ghost particles.

With help from a theoretical collaborator at MIT, the researchers realized that when an electron is injected into a QSL from the tip of an STM, it breaks apart into two different particles inside the QSL spinons (also known as ghost particles) and chargons. This is due to the peculiar way in which spin and charge in a QSL collectively interact with each other. The spinon ghost particles end up separately carrying the spin while the chargons separately bear the electrical charge.

Illustration of an electron breaking apart into spinon ghost particles and chargons inside a quantum spin liquid. Credit: Mike Crommie et al./Berkeley Lab

In the current study, STM/STS images show that the chargons freeze in place, forming what scientists call a star-of-David charge-density-wave. Meanwhile, the spinons undergo an out-of-body experience as they separate from the immobilized chargons and move freely through the material, Crommie said. This is unusual since in a conventional material, electrons carry both the spin and charge combined into one particle as they move about, he explained. They dont usually break apart in this funny way.

Crommie added that QSLs might one day form the basis of robust quantum bits (qubits) used for quantum computing. In conventional computing a bit encodes information either as a zero or a one, but a qubit can hold both zero and one at the same time, thus potentially speeding up certain types of calculations. Understanding how spinons and chargons behave in QSLs could help advance research in this area of next-gen computing.

Another motivation for understanding the inner workings of QSLs is that they have been predicted to be a precursor to exotic superconductivity. Crommie plans to test that prediction with Mos help at the ALS.

Part of the beauty of this topic is that all the complex interactions within a QSL somehow combine to form a simple ghost particle that just bounces around inside the crystal, he said. Seeing this behavior was pretty surprising, especially since we werent even looking for it.

Reference: Evidence for quantum spin liquid behaviour in single-layer 1T-TaSe2 from scanning tunnelling microscopy by Wei Ruan, Yi Chen, Shujie Tang, Jinwoong Hwang, Hsin-Zon Tsai, Ryan L. Lee, Meng Wu, Hyejin Ryu, Salman Kahn, Franklin Liou, Caihong Jia, Andrew Aikawa, Choongyu Hwang, Feng Wang, Yongseong Choi, Steven G. Louie, Patrick A. Lee, Zhi-Xun Shen, Sung-Kwan Mo & Michael F. Crommie, 19 August 2021, Nature Physics.DOI: 10.1038/s41567-021-01321-0

Researchers from SLAC National Accelerator Laboratory; Stanford University; Argonne National Laboratory; the Massachusetts Institute of Technology; the Chinese Academy of Sciences, Shanghai Tech University, Shenzhen University, Henan University of China; and the Korea Institute of Science and Technology and Pusan National University of Korea contributed to this study. (Co-first author Wei Ruan is now an assistant professor of physics at Fudan University in China; co-first author Yi Chen is currently a postdoctoral fellow at the Center for Quantum Nanoscience, Institute for Basic Science of Korea.)

This work was supported by the DOE Office of Science, and used resources at Berkeley Labs Advanced Light Source and Argonne National Laboratorys Advanced Photon Source. The Advanced Light Source and Advanced Photon Source are DOE Office of Science user facilities.

Additional support was provided by the National Science Foundation.

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This Exotic Particle Had an Out-of-Body Experience These Surprised Scientists Took a Picture of It - SciTechDaily

Though quantum computing is likely five to 10 years away, waiting until it happens will put your organization behind. Don't play catch-up later.

TechRepublic's Karen Roby spoke with Christopher Savoie, CEO and co-founder of Zapata Computing, a quantum application company, about the future of quantum computing. The following is an edited transcript of their conversation.

SEE: The CIO's guide to quantum computing (free PDF) (TechRepublic)

Christoper Savoie: There are two types of quantum-computing algorithms if you will. There are those that will require what we call a fault-tolerant computing system, one that doesn't have error, for all intents and purposes, that's corrected for error, which is the way most classical computers are now. They don't make errors in their calculations, or at least we hope they don't, not at any significant rate. And eventually we'll have these fault-tolerant quantum computers. People are working on it. We've proven that it can happen already, so that is down the line. But it's in the five- to 10-year range that it's going to take until we have that hardware available. But that's where a lot of the promises for these exponentially faster algorithms. So, these are the algorithms that will use these fault-tolerant computers to basically look at all the options available in a combinatorial matrix.

So, if you have something like Monte Carlo simulation, you can try significantly all the different variables that are possible and look at every possible combination and find the best optimal solution. So, that's really, practically impossible on today's classical computers. You have to choose what variables you're going to use and reduce things and take shortcuts. But with these fault-tolerant computers, for significantly many of the possible solutions in the solution space, we can look at all of the combinations. So, you can imagine almost an infinite amount or an exponential amount of variables that you can try out to see what your best solution is. In things like CCAR [Comprehensive Capital Analysis and Review], Dodd-Frank [Dodd-Frank Wall Street Reform and Consumer Protection Act] compliance, these things where you have to do these complex simulations, we rely on a Monte Carlo simulation.

So, trying all of the possible scenarios. That's not possible today, but this fault tolerance will allow us to try significantly all of the different combinations, which will hopefully give us the ability to predict the future in a much better way, which is important in these financial applications. But we don't have those computers today. They will be available sometime in the future. I hate putting a date on it, but think about it on the decade time horizon. On the other hand, there are these nearer-term algorithms that run on these noisy, so not error-corrected, noisy intermediate-scale quantum devices. We call them NISQ for short. And these are more heuristic types of algorithms that are tolerant to noise, much like neural networks are today in classical computing and [artificial intelligence] AI. You can deal a little bit with the sparse data and maybe some error in the data or other areas of your calculation. Because it's an about-type of calculation like neural networks do. It's not looking at the exact answers, all of them and figuring out which one is definitely the best. This is an approximate algorithm that iterates and tries to get closer and closer to the right answer.

SEE: Hiring Kit: Video Game Designer (TechRepublic Premium)

But we know that neural networks work this way, deep neural networks. AI, in its current state, uses this type of algorithm, these heuristics. Most of what we do in computation nowadays and finance is heuristic in its nature and statistical in its nature, and it works good enough to do some really good work. In algorithmic trading, in risk analysis, this is what we use today. And these quantum versions of that will also be able to give us some advantage and maybe an advantage overwe've been able to show in recent workthe purely classical version of that. So, we'll have some quantum-augmented AI, quantum-augmented [machine learning] ML. We call it a quantum-enhanced ML or quantum-enhanced optimization that we'll be able to do.

So, people think of this as a dichotomy. We have these NISQ machines, and they're faulty, and then one day we'll wake up and we'll have this fault tolerance, but it's really not that way. These faulty algorithms, if you will, these heuristics that are about, they will still work and they may work better than the fault-tolerant algorithms for some problems and some datasets, so this really is a gradient. It really is. You'd have a false sense of solace, maybe two. "Oh well, if that's 10 years down the road we can just wait and let's wait till we wake up and have fault tolerance." But really the algorithms are going to be progressing. And the things that we develop now will still be useful in that fault-tolerant regime. And the patents will all be good for the stuff that we do now.

So, thinking that, "OK, this is a 10 year time horizon for those fault-tolerant computers. Our organization is just going to wait." Well, if you do, you get a couple of things. You're not going to have the workforce in place to be able to take advantage of this. You're probably not going to have the infrastructure in place to be able to take advantage of this. And meanwhile, all of your competitors and their vendors have acquired a portfolio of patents on these methodologies that are good for 20 years. So, if you wait five years from now and there's a patent four years down the line, that's good for 24 years. So there really is, I think, an incentive for organizations to really start working, even in this NISQ, this noisier regime that we're in today.

Karen Roby: You get a little false sense of security, as you mentioned, of something, oh, you say that's 10 years down the line, but really with this, you don't have the luxury of catching up if you wait too long. This is something that people need to be focused on now for what is down the road.

SEE: Quantum entanglement-as-a-service: "The key technology" for unbreakable networks (TechRepublic)

Christoper Savoie: Yes, absolutely. And in finance, if you have a better ability to detect risks then than your competitors; you're at a huge advantage to be able to find alpha in the market. If you can do that better than others, you're going to be at a huge advantage. And if you're blocked by people's patents or blocked by the fact that your workforce doesn't know how to use these things, you're really behind the eight ball. And we've seen this time and time again with different technology evolutions and revolutions. With big data and our use of big data, with that infrastructure, with AI and machine learning. The organizations that have waited generally have found themselves behind the eight ball, and it's really hard to catch up because this stuff is changing daily, weekly, and new inventions are happening. And if you don't have a workforce that's up and running and an infrastructure ready to accept this, it's really hard to catch up with your competitors.

Karen Roby: You've touched on this a little bit, but really for the finance industry, this can be transformative, really significant what quantum computing can do.

Christoper Savoie: Absolutely. At the end of the day, finance is math, and we can do better math and more accurate math on large datasets with quantum computing. There is no question about that. It's no longer an "if." Google has, with their experiment, proven that at some point we're going to have a machine that is definitely going to be better at doing math, some types of math, than classical computers. With that premise, if you're in a field that depends on math, that depends on numbers, which is everything, and statistics, which is finance, no matter what side you're on. If you're on the risk side or the investing side, you're going to need to have the best tools. And that doesn't mean you have to be an algorithmic trader necessarily, but even looking at tail risk and creating portfolios and this kind of thing. You're dependent on being able to quickly ascertain what that risk is, and computing is the only way to do that.

SEE: The quantum decade: IBM predicts the 2020s will see quantum begin to solve real problems (TechRepublic)

And on the regulatory side, I mentioned CCAR. I think as these capabilities emerge, it allows the regulators to ask for even more scenarios to be simulated, those things that are a big headache for a lot of companies. But it's important because our global financial system depends on stability and predictability, and to be able to have a computational resource like quantum that's going to allow us to see more variables or more possibilities or more disaster scenarios. It can really help. "What is the effect of, say, a COVID-type event on the global financial system?" To be more predictive of that and more accurate at doing that is good for everybody. I think all boats rise, and quantum is definitely going to give us that advantage as well.

Karen Roby: Most definitely. And Christopher, before I let you go, if you would just give us a quick snapshot of Zapata Computing and the work that you guys do.

Christoper Savoie: We have two really important components to try and make this stuff reality. On the one hand, we've got over 30 of the brightest young minds and algorithms, particularly for these near-term devices and how to write those. We've written some of the fundamental algorithms that are out there to be used on quantum computers. On the other hand, how do you make those things work? That's a software engineering thing. That's not really quantum science. How do you make the big data work? And that's all the boring stuff of ETL and data transformation and digitalization and cloud and multicloud and all this boring but very important stuff. So basically Zapata is a company that has the best of the algorithms, but also best-of-breed means of actually software engineering that in a modern, multicloud environment that particularly finance companies, banks, they're regulated companies with a lot of data that is sensitive and private and proprietary. So, you need to be able to work in a safe and secure multicloud environment, and that's what our software engineering side allows us to do. We have the best of both worlds there.

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Expert: Now is the time to prepare for the quantum computing revolution - TechRepublic

Tokyo IBM and the University of Tokyo have announced one of Japans most powerful quantum computers.

According to IBM, IBM Quantum System One is part of the Japan-IBM quantum partnership between the University of Tokyo and IBM, advancing Japans quest for quantum science, business and education.

IBM Quantum System One is currently in operation for researchers at both Japanese scientific institutions and companies, and access is controlled by the University of Tokyo.

IBM is committed to growing the global quantum ecosystem and facilitating collaboration between different research communities, said Dr. Dario Gil, director of IBM Research.

According to IBM, quantum computers combine quantum resources with classical processing to provide users with access to reproducible and predictable performance from high-quality qubits and precision control electronics. Users can safely execute algorithms that require iterative quantum circuits in the cloud.

see next: IBM partners with Atos on contract with Dutch Ministry of Defense

IBM Quantum System One in Japan is IBMs second system built outside the United States. In June, IBM unveiled the IBM Quantum System One, managed by the scientific research institute Fraunhofer Geselleschaft, in Munich, Germany.

IBMs commitment to quantum is aimed at advancing quantum computing and fostering a skilled quantum workforce around the world.

We are thrilled to see Japans contributions to research by world-class academics, the private sector, and government agencies, Gil said.

Together, we can take a big step towards accelerating scientific progress in different areas, Gil said.

Teruo Fujii, President of the University of Tokyo, said, In the field of rapidly changing quantum technology, it is very important not only to develop elements and systems related to quantum technology, but also to develop the next generation of human resources. To achieve a high degree of social implementation.

Our university has a wide range of research capabilities and has always promoted high-level quantum education from the undergraduate level. Now, with IBM Quantum System One, we will develop the next generation of quantum native skill sets. Further refine it.

In 2020, IBM and the University of Tokyo Quantum Innovation Initiative Consortium (QIIC) aims to strategically accelerate the research and development activities of quantum computing in Japan by bringing together the academic talents of universities, research groups and industries nationwide.

Last year, IBM also announced partnerships with several organizations focusing on quantum information science and technology. Cleveland Clinic, NS Science and Technology Facilities Council in the United Kingdom, And that University of Illinois at Urbana-Champaign..

see next: Public cloud computing provider

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IBM partners with the University of Tokyo on quantum computer - Illinoisnewstoday.com

- New social paradigm shift "QX" is right around the corner -

TOKYO, August 23, 2021--(BUSINESS WIRE)--Sumitomo Corporation Quantum Transformation (QX) Project will present at the IEEE Quantum AI Sustainability Symposium on September 1st, 2021. The QX Project was launched in March 2021 by Sumitomo Corporation, a global Fortune 500 trading and investment company, with the intent to provide new value to society by applying quantum computing technology to the wide-ranging industries in which the company operates. This is the worlds first project that defines "Quantum Transformation (QX)" as the next social paradigm shift, beyond "Digital Transformation (DX)".

This press release features multimedia. View the full release here: https://www.businesswire.com/news/home/20210823005255/en/

Sumitomo Corporation Quantum Transformation (QX) Project Announces Its Vision and Activities. (Graphic: Business Wire)

The founder and head of the QX Project, Masayoshi Terabe, will present about the vision and activities of QX at the IEEE Quantum AI Sustainability Symposium. The organizer "IEEE" is the world's largest technical professional organization for the advancement of technology. In this talk, he will show how quantum computing can contribute to sustainability. For example, he will introduce the Quantum Sky project, which is a pilot experiment for developing flight routes for numerous air mobility vehicles by quantum computing. Also you can find other concepts like Quantum Smart City and Quantum Energy Management.

The objective of the QX Project is to create new value to the society by combining vast business fields of Sumitomo Corporation throughout its more than 900 consolidated companies, from underground to space, and an extensive number of business partners around the world.

A broad and deep ecosystem is necessary to achieve QX. This is because combining a wide range of technologies, not limited to quantum, and working with a crossover of various industries, is essential. If you are interested in this project, lets take on the challenge of creating a new business, and a new society together!

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[Appendix]

View source version on businesswire.com: https://www.businesswire.com/news/home/20210823005255/en/

Contacts

Contact info:Luke Hasumura, responsible for Vision & Ecosystem on Quantum Transformation.qx@sumitomocorp.com +81-3-6285-7489

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Sumitomo Corporation Quantum Transformation (QX) Project Announces Its Vision and Activities at the IEEE Quantum AI Sustainability Symposium - Yahoo...

The U.S. Department of Energy (DOE) has announced $61 million in funding for infrastructure and research projects to advance quantum information science (QIS).

Specifically, the DOE is supplying $25 million in funding for creating quantum internet testbeds, which will advance foundational building blocks including devices, protocols, technology, and techniques for quantum error correction at the internet scale.

The DOE also is providing $6 million in funding for scientists to study and develop new devices to send and receive quantum network traffic and advance a continental-scale quantum internet.

Lastly, the DOE granted $30 million of funding to five DOE Nanoscale Science Research Centers to support cutting-edge infrastructure for nanoscience-based research to strengthen the United States competitiveness in QIS and enable the development of nanotechnologies.

Harnessing the quantum world will create new forms of computers and accelerate our ability to process information and tackle complex problems like climate change, said U.S. Secretary of Energy Jennifer M. Granholm in a statement. DOE and our labs across the country are leading the way on this critical research that will strengthen our global competitiveness and help corner the markets of these growing industries that will deliver the solutions of the future.

The DOE recognized the advantages of QIS back in 2018 when it became an integral partner in theNational Quantum Initiative, which became law in December 2018. Since then, the DOE Office of Science has launched a range of multidisciplinary research programs in QIS, including developing quantum computers as testbeds, designing new algorithms for quantum computing, and using quantum computing to model fundamental physics, chemistry, and materials phenomena.

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Energy Department Sets $61M of Funding to Advance QIS Research - MeriTalk