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Chinese scientists are one step closer to a future large-scale quantum computer after building the worlds largest quantum simulation machine based on the trapped-ion technique, praised by one academic journal reviewer as a milestone to be recognised.

The breakthrough was achieved under the leadership of Duan Luming, a quantum physicist renowned for his pioneering research, who returned to China in 2018 after 15 years of teaching in the United States.

Duan received his doctorate in 1998 from the University of Science and Technology of China, the countrys premier institute for quantum research, before joining the University of Michigan in the early 2000s.

Since his return, he has been a full-time professor at Tsinghua Universitys Institute for Interdisciplinary Information Sciences.

Duan and his colleagues, along with several research groups at universities and hi-tech companies around the world, have been chasing the trapped-ion approach to qubits.

Quantum bits, or qubits, are the building blocks of quantum computers, just as bits are in regular computers.

However, qubits are extremely difficult to harness in a controlled and repeatable way because of what is called their hazy nature.

Regular bits can be described as switches that are either on or off. But because uncertainty and probability hold sway in quantum physics, qubits can be both on and off at the same time, and also exist in a variety of in-between states.

Ions, or charged atomic particles, can be trapped and suspended in free space using electromagnetic fields. The qubits are stored in stable electronic states of each ion, and quantum information can be transferred through the collective motion of the ions in a shared trap.

But scalability remains a key challenge for this system.

This is where the trapped-ion approach comes in, as it offers one of the most promising architectures for a scalable, universal quantum computer.

Researchers earlier achieved quantum simulations with up to 61 ions in a one-dimensional crystal. Ion crystals are solids made up of ions bound together in a regular lattice the symmetrical three-dimensional structural arrangements of atoms, ions or molecules inside a solid.

But Duan and his teams quantum simulator was able to achieve the stable trapping and cooling of a two-dimensional crystal of up to 512 ions, in a first for science.

The feat holds great significance for the future of quantum computing, given that scalability is a major hurdle. The teams scaling up of the ions in a stable simulation system is seen as likely to pave the way to building more powerful quantum computers.

The findings of their study were published on Wednesday in the peer-reviewed journal Nature.

This is the largest quantum simulation or computation performed to date in a trapped-ion system, commented one reviewer.

Quantum simulators are devices that actively use quantum effects to answer questions about model systems and, through them, real systems. They are increasingly popular tools in the world of quantum computing for their role in advancing scientific knowledge and developing technologies.

Duan and his team also managed to perform a quantum simulation calculation using 300-ion qubits. They found the computational complexity of 300-ion quantum bits working simultaneously to be astronomical, far exceeding the direct simulation capability of classical computers.

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US-returned Chinese physicist and team achieve world first in quantum computing - South China Morning Post

May 31 2024Reviewed by Lexie Corner

Recent findings from IBM and Cleveland Clinic researchersmay pave the way for applying quantum computing techniques to protein structure prediction. These findings are publishedin the Journal of Chemical Theory and Computation.This publication represents the Cleveland Clinic-IBM Discovery Accelerator collaboration's first peer-reviewed paper on quantum computing.

For many years, researchers have used computational methods to predict protein structures. A protein folds into a structure that controls its molecular interactions and mode of action. These structures determine numerous facets of human health and illness.

Researchers can create more effective treatments by better understanding how diseases spread through precise protein structure predictions. Bryan Raubenolt, Ph.D., a Postdoctoral Fellow at the Cleveland Clinic, and Hakan Doga, Ph.D., a researcher at IBM, led a team to discover how quantum computing can enhance existing techniques.

Machine learning techniques have significantly advanced the prediction of protein structure in recent years. To make predictions, these techniques rely on training data, a database of protein structuresdetermined through experimentation. This indicates that the number of proteins they have been trained to identify is a limitation. When programs or algorithms come across a protein that is mutated or significantly different from the ones they were trained on, as is frequently the case with genetic disorders, this can result in decreased accuracy levels.

A different approach is to model the physics involved in protein folding. Through simulations, scientists can examine multiple protein configurations and determine the most stable form, whichis essential for drug design.

The challenge is that these simulations are nearly impossible on a classical computer beyond a certain protein size. In a way, increasing the size of the target protein is comparable to increasing the dimensions of a Rubik's cube. For a small protein with 100 amino acids, a classical computer would need the time equal to the age of the universe to exhaustively search all the possible outcomes.

Dr. Bryan Raubenolt, Postdoctoral Fellow, Cleveland Clinic

The research team combined quantum and classical computing techniques to get around these restrictions. Within this framework, quantum algorithms can tackle problems that current state-of-the-art classical computing finds difficult, such as the physics of protein folding, intrinsic disorder, mutations, and protein size.

The accuracy with which the framework predicted, on a quantum computer, the folding of a small fragment of the Zika virus protein, compared to the most advanced classical methods, served as validation.

The initial results of the quantum-classical hybrid framework outperformed both AlphaFold2 and a method based on classical physics. The latter shows that this framework can produce accurate models without directly relying on large amounts of training data, even though it is optimized for larger proteins.

The most computationally intensive part of the calculation usually involves modeling the lowest energy conformation for the fragment's backbone, which the researchers accomplish using a quantum algorithm. After that, classical methods were employed to translate the quantum computer's output, rebuild the protein along with its sidechains, and refine the structure one last time using force fields from classical molecular mechanics.

The project illustrates how problems can be broken down into smaller components for better accuracy. Some components can be addressed by quantum computing techniques, while classical computing methods can handle others.

Working across disciplines was crucial to creating this framework.

One of the most unique things about this project is the number of disciplines involved. Our teams expertise ranges from computational biology and chemistry, structural biology, software, and automation engineering to experimental atomic and nuclear physics, mathematics, and, of course,quantum computing and algorithm design. It took the knowledge from each of these areas to create a computational framework that can mimic one of the most important processes for human life.

Dr. Bryan Raubenolt, Postdoctoral Fellow, Cleveland Clinic

The teams combination of classical and quantum computing methods is essential for advancing our understanding of protein structures and how they impact our ability to treat and prevent disease. The team plans to continue developing and optimizing quantum algorithms that can predict the structure of larger and more sophisticated proteins.

This work is an important step forward in exploring where quantum computing capabilities could show strengths in protein structure prediction. Our goal is to design quantum algorithms that can find how to predict protein structures as realistically as possible.

Dr. Hakan Doga, Researcher, IBM

Doga, H., et al. (2024) A Perspective on Protein Structure Prediction Using Quantum Computers. Chemical Theory and Computation. doi.org/10.1021/acs.jctc.4c00067

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Unveiling Protein Structures with Quantum Computing - AZoQuantum

By Ken Briodagh

Senior Technology Editor

Embedded Computing Design

May 30, 2024

News

According to a recent release, NXP Semiconductors has partnered with eleQtron and ParityQC, with theQSea consortiumof theDLR Quantum Computing Initiative (DLR QCI), to create what is reportedly the first full-stack, ion-trap based quantum computer demonstrator made entirely in Germany. The new quantum computer demonstrator is in Hamburg.

Hamburg is one of our most important R&D locations. We are proud that, together with DLR and our partners eleQtron and ParityQC, we are able to present the first ion-trap based quantum computer demonstrator developed entirely in Germany, said Lars Reger, CTO at NXP Semiconductors. We are convinced that industry and research communities in Hamburg and throughout Germany will benefit from this project. It will help to build up and expand important expertise in quantum computing, to use it for the economic benefit of us all, and also to further strengthen our digital sovereignty in Germany and the EU.

The goal of this demonstrator is to enable early access to quantum computing resources and help companies and research teams leverage it for applications like climate modeling, global logistics and materials sciences, the companies said.

DLR QCI says it aims to build necessary skills by creating a quantum computing ecosystem in which economy, industry and science cooperate closely to fully leverage the potential of this technology. Quantum computers are expected to tackle complex problems across industries, and will likely dramatically change the cybersecurity landscape.

NXP, eleQtron and ParityQC have used their expertise to build this ion-trap based quantum computer demonstrator by combining eleQtrons MAGIC hardware, ParityQC architecture, and NXP chip design and technology. To speed innovation and iteration, they have also developed a digital twin, which reportedly will be used to help this QSea I demonstrator to evolve to a quantum computer with a modular architecture, scalable design, and error correction capabilities. That evolution will be the goal of the ongoing work with the project.

The demonstrator is set up at the DLR QCI Innovation Center in Hamburg and will be made available to industry partners and DLR research teams, the release said. The three partners and the DLR QCI say they aim to foster and strengthen the development of an advanced quantum computing ecosystem in Germany.

To achieve a leading international position in quantum computing, we need a strong quantum computing ecosystem. Only together will research, industry and start-ups overcome the major technological challenges and successfully bring quantum computers into application. The QSea I demonstrator is an important step for the DLR Quantum Computing Initiative and for Hamburg. It enables partners from industry and research to run quantum algorithms on real ion trap qubits in a real production environment for the first time. This hands-on experience will enable them to leverage the advantages of quantum computers and become part of a strong and sovereign quantum computing ecosystem in Germany and Europe, said Dr.-Ing. Robert Axmann, Head of DLR Quantum Computing Initiative (DLR QCI).

Ken Briodagh is a writer and editor with two decades of experience under his belt. He is in love with technology and if he had his druthers, he would beta test everything from shoe phones to flying cars. In previous lives, hes been a short order cook, telemarketer, medical supply technician, mover of the bodies at a funeral home, pirate, poet, partial alliterist, parent, partner and pretender to various thrones. Most of his exploits are either exaggerated or blatantly false.

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NXP, eleQtron and ParityQC Reveal Quantum Computing Demonstrator - Embedded Computing Design

By Anne J. Manning, Harvard Gazette

Its one thing to dream up a next-generation quantum internet capable of sending highly complex, hacker-proof information around the world at ultra-fast speeds. Its quite another to physically show its possible.

Thats exactly what Harvard physicists have done, using existing Boston-area telecommunication fiber, in a demonstration of the worlds longest fiber distance between two quantum memory nodes. Think of it as a simple, closed internet carrying a signal encoded not by classical bits like the existing internet, but by perfectly secure, individual particles of light.

Thegroundbreaking work, published in Nature, was led by Mikhail Lukin, the Joshua and Beth Friedman University Professor in the Department of Physics, in collaboration with Harvard professorsMarko LonarandHongkun Park,who are all members of theHarvard Quantum Initiative.The Naturework was carried out with researchers atAmazon Web Services.

The Harvard team established the practical makings of the first quantum internet by entangling two quantum memory nodes separated by optical fiber link deployed over a roughly 22-mile loop through Cambridge, Somerville, Watertown, and Boston. The two nodes were located a floor apart in Harvards Laboratory for Integrated Science and Engineering.

Quantum memory, analogous to classical computer memory, is an important component of a quantum computing future because it allows for complex network operations and information storage and retrieval. While other quantum networks have been created in the past, the Harvard teams is the longest fiber network between devices that can store, process, and move information.

Each node is a very small quantum computer, made out of a sliver of diamond that has a defect in its atomic structure called a silicon-vacancy center. Inside the diamond, carved structures smaller than a hundredth the width of a human hair enhance the interaction between the silicon-vacancy center and light.

The silicon-vacancy center contains two qubits, or bits of quantum information: one in the form of an electron spin used for communication, and the other in a longer-lived nuclear spin used as a memory qubit to store entanglement, the quantum-mechanical property that allows information to be perfectly correlated across any distance.

(In classical computing, information is stored and transmitted as a series of discrete binary signals, say on/off, that form a kind of decision tree. Quantum computing is more fluid, as information can exist in stages between on and off, and is stored and transferred as shifting patterns of particle movement across two entangled points.)

Using silicon-vacancy centers as quantum memory devices for single photons has been a multiyear research program at Harvard. The technology solves a major problem in the theorized quantum internet: signal loss that cant be boosted in traditional ways.

A quantum network cannot use standard optical-fiber signal repeaters because simple copying of quantum information as discrete bits is impossible making the information secure, but also very hard to transport over long distances.

Silicon-vacancy-center-based network nodes can catch, store, and entangle bits of quantum information while correcting for signal loss. After cooling the nodes to close to absolute zero, light is sent through the first node and, by nature of the silicon vacancy centers atomic structure, becomes entangled with it, so able to carry the information.

Since the light is already entangled with the first node, it can transfer this entanglement to the second node, explained first author Can Knaut, a Kenneth C. Griffin Graduate School of Arts and Sciences student in Lukins lab. We call this photon-mediated entanglement.

Over the last several years, the researchers have leased optical fiber from a company in Boston to run their experiments, fitting their demonstration network on top of the existing fiber to indicate that creating a quantum internet with similar network lines would be possible.

Showing that quantum network nodes can be entangled in the real-world environment of a very busy urban area is an important step toward practical networking between quantum computers, Lukin said.

A two-node quantum network is only the beginning. The researchers are working diligently to extend the performance of their network by adding nodes and experimenting with more networking protocols.

The paper is titled Entanglement of Nanophotonic Quantum Memory Nodes in a Telecom Network. The work was supported by the AWS Center for Quantum Networkings research alliance with the Harvard Quantum Initiative, the National Science Foundation, the Center for Ultracold Atoms (an NSF Physics Frontiers Center), the Center for Quantum Networks (an NSF Engineering Research Center), the Air Force Office of Scientific Research, and other sources.

This story is reprinted with permission from The Harvard Gazette.

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Glimpse of Next-Generation Internet - The Good Men Project