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HAMBURG, Germany, April 17, 2023 ISC 2023 attendees can look forward to captivating talks for the events Tuesday and Wednesday conference keynotes. The Tuesday, May 23 keynote will be delivered by Google Principal Engineer Dr. Valentina Salapura, who will sketch out the emerging dynamic between the hyperscaler and HPC ecosystems. On Wednesday, May 24, Professor Dr. Thomas Sterling of Indiana University, and Professor Dr. Estela Suarez, of the Jlich Supercomputing Centre will recap the past year in HPC and offer predictions about its future.

Tuesdays keynote by Dr. Salapura will bring her perspective on how the escalating demand for enormous amounts of cloud-based compute power is bringing supercomputing technologies into hyperscale data centers. AI, as well as other commercial workloads requiring large amounts of data and compute power, are the main drivers of this demand, having a profound effect on the technologies employed by big cloud providers.

Heterogeneous computing, accelerators, and GPUs, which until recently were technologies mainly confined to HPC, are now being employed at scale by major tech companies. These same companies are pursuing their own custom chips and systems along the same lines and are developing software that can tap into all this powerful new hardware. In the process, both the hyperscale cloud and HPC domains are transformed.

Salapuras expertise on these topics stems from her work at Google, AMD, and IBM. At Google, where she is currently employed, she focuses on system architecture for cloud and edge computing. Before that, she worked on distributed computing and supercomputing at AMD Research. Before joining AMD, Dr. Salapura was a system architect and IBM master inventor focusing on cloud computing resiliency for several IBM cloud offerings. Her IBM Research stint also included working as a Blue Gene programs computer architect.

Wednesdays keynote will feature Professor Thomas Sterlings perennial talk highlighting the most crucial HPC-related news and events since last years conference. The 2023 rundown, though, will offer a couple of new twists: To begin with, this year, Sterling will be joined by Professor Estela Suarez, a research group leader at the Jlich Supercomputing Centre, who will be a co-presenter for the talk. Also, in addition to delivering a retrospective of the year just past, Sterling and Suarez will offer a peek into the future of HPC.

Some of this future has already been foreshadowed. With Moores Law fading and artificial intelligence workloads coming to the fore, HPC engineers and practitioners are increasingly adopting more exotic hardware, especially heterogeneous ones that use tensor accelerators, AI accelerators, ASIC-based processors, and even neuromorphic devices. As noted in Tuesdays keynote, some of this technology is being developed and commercialized by big cloud providers, who now require such HPC-capable hardware for AI and other demanding workloads. At the same time, cloud computing is becoming a more common delivery system for HPC.

Thomas Sterling is uniquely equipped to bring such wide-ranging topics into focus. Since receiving his Ph.D. from MIT as a Hertz Fellow in 1984, he has engaged in applied research in parallel computing system structures, semantics, and operation in industry, government labs, and academia. He is best known as the father of Beowulf for his pioneering research in commodity/Linux cluster computing, for which he shared the Gordon Bell Prize in 1997. He has also co-authored the introductory textbook, High Performance Computing, published by Morgan-Kaufmann in 2018. He is currently a Full Professor of Intelligent Systems Engineering at Indiana University (IU), serving as Director of the AI Computing Systems Laboratory at IUs Luddy School of Informatics, Computing, and Engineering.

Estela Suarez brings a contemporary perspective to the field, focusing on HPC system architectures and codesign. As the European DEEP project series leader, she has driven the development of the Modular Supercomputing Architecture, including hardware, software, and application implementation and validation. Additionally, she leads the codesign and validation efforts within the European Processor Initiative. Her current position is Research Group Leader at the Jlich Supercomputing Centre, which she joined in 2010. She is also a Professor of High Performance Computing at the University of Bonn. Suarez holds a Ph.D. in Physics from the University of Geneva and a Masters in Astrophysics from the University Complutense of Madrid.

As announced previously, Professor Dr. Dan Reed will kick off the conference with his opening keynote on the post-Moore environment and the technical and financial challenges the HPC industry faces, ending his talk by sharing ideas on how the HPC industry can overcome these difficulties.

Early-Bird Registration

Attendees who register by April 19 qualify for the early-bird rates, which provide considerable savings. ISC 2023 will be held in person, offering rich on-demand content to attendees who will join the event remotely.

Join ISC High Performance 2023 and Imagine Tomorrow

ISC 2023 will be held at the Congress Center Hamburg from May 21 25. Join the HPC community of attendees, speakers, and exhibitors. The exhibition will showcase the latest advancements in HPC, encompassing all the key developments in system design, applications, programming models, machine learning, quantum computing, and emerging technologies.

First held in 1986, ISC High Performance distinguishes itself as the worlds oldest and Europes most significant forum for the HPC and related domains.

Source: ISC

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ISC 2023: Google's Valentina Salapura and Leading HPC Experts ... - HPCwire

April 13, 2023• Physics 16, s53

Researchers propose a way to relieve the material requirements needed to realize topological quantum computers.

Todays quantum computers are delicate devicessensitive to disruption by environmental noise. Physicists are thus pursuing alternatives called topological quantum computers, which harness quasiparticlesMajorana fermionspredicted to be resilient to noise (see Viewpoint: A Roadmap for a Scalable Topological Quantum Computer). Now Kristian Mland and Asle Sudb at the Norwegian University of Science and Technology in Trondheim propose a way to generate Majorana fermions without the superconducting materials that were previously thought to be required for such fermions to emerge [1]. By expanding the material choice, the approach could bring topological quantum computers a step closer to realization.

Majorana fermions are hallmarks of an exotic state called a topological superconductor. To date, most proposals for generating such a state involve structures combining a superconductor and a material with strong spin-orbit coupling. Under an applied magnetic field, a topological superconductor should form at the interface between the materials.

In the model proposed by Mland and Sudb, a one-atom-thick layer of a magnetic material is sandwiched between a normal metal and a heavy metal with strong spin-orbit coupling. This coupling causes the magnetic layer to adopt a skyrmion crystal configuration, in which skyrmionstwists in the spin textureare arranged on a lattice. By scattering electrons, spin fluctuations in this skyrmion crystal produce an electronelectron interaction in the normal metal that creates a topological superconducting state at its boundary.

Besides removing the need for superconductors, the design would have another advantage over other proposed systems, say the researchers. By controlling the skyrmions, the device could manipulate the Majorana fermions, which are located at the centers of the skyrmions, to realize logical operations.

Marric Stephens

Marric Stephens is a Corresponding Editor forPhysics Magazine based in Bristol, UK.

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Physics - Topological Superconductivity without Superconductors - Physics

Quantum 101

Quantum computers harness the laws of physics at the tiniest scales. Classical computers encode information in bits, usually represented as either a 0 or a 1. But quantum computers use quantum bits, or qubits, which can exist in a superposition of states a combination of both 0 and 1 simultaneously. This translates to more computational power.

Quantum information processors are still nascent and fragile, requiring careful setup and controls in specialized labs. To scale up quantum computers so that they can solve big problems, researchers need to advance technologies to support larger numbers of qubits for longer periods of time.

Quantum computers could someday perform certain calculations faster than classical computers, with applications in science, medicine, security, finance, and beyond but first, researchers need to improve the underlying science and technology. Since its launch in 2020, the Quantum Systems Accelerator (QSA) has already made major advances in both hardware and programming, improving the quantum tools that researchers hope will help solve some of humanitys biggest questions.

QSA is one of the Department of Energys five national quantum information science research centers with a focus on all three major technologies for quantum computing: superconducting circuits, trapped-ion systems, and neutral atoms.

We believe there are synergies between these three big technologies and that each one may have unique abilities and applications for solving different kinds of problems, said Rick Muller, the director of QSA and a senior manager at Sandia National Laboratories. By looking at all three of them together, we can more easily find their strengths, apply innovations across technologies, and design a path forward to a universal quantum computer.

Led by Lawrence Berkeley National Laboratory (Berkeley Lab), QSA brings together more than 250 experts from 14 other institutions: Sandia National Laboratories, University of Colorado Boulder, MIT Lincoln Laboratory, Caltech, Duke University, Harvard University, Massachusetts Institute of Technology, Tufts University, UC Berkeley, University of Maryland, University of New Mexico, University of Southern California, University of Texas at Austin, and Canadas Universit de Sherbrooke.

Together, QSA researchers are developing ways to better control qubits (the building blocks of quantum computers), finding algorithms and applications for current and emerging quantum information systems, and speeding their transfer to industry. QSA is also preparing the next generation of quantum scientists through activities, including peer mentoring programs, career fairs, and training for high school students and teachers.

Were catalyzing national leadership in quantum information through co-design of quantum devices, algorithms, and engineering solutions, with the goal of delivering quantum advantage, said Bert de Jong, the deputy director of QSA and a senior scientist at Berkeley Lab. Were advancing imperfect quantum technologies and figuring out how we in academia and the national laboratories working with our partners in industry can start using them today. At the same time, were preparing scientists to use them to solve big science questions.

In March, the Quantum Systems Accelerator issued a full impact report on advances made since the center launched in 2020. Here are five highlights achieved by QSA scientists and partners so far:

QSA researchers from Harvard University and MIT used a special quantum device to observe several exotic states of matter for the first time and studied magnetism at the quantum level. Their findings help explain the physics underlying materials properties and could be used to engineer exotic materials of the future. Their research was performed using a programmable quantum simulator similar to a quantum computer. The team at Harvard built the simulator using hundreds of laser beams known as optical tweezers, arranging 256 ultra-cold rubidium atoms that acted as qubits. By some measures, that makes it the largest programmable quantum processor demonstrated to date. By moving the atoms into shapes such as squares, honeycombs, and triangles, QSA scientists manipulated how the qubits would interact with one another and made important measurements of quantum phases of matter and quantum spin liquids.

One way to build a useful quantum computer is by connecting qubits with superconducting circuits, which can conduct electricity without energy loss when extremely cold. But with every qubit added, engineering the connections and electronics becomes more difficult. You can imagine a group of qubits spread out like a grid on a piece of paper; trying to snake connections to the innermost qubits causes crowding that can degrade the qubits or signals. To address the challenge, scientists at MIT and MIT Lincoln Laboratory are taking inspiration from commercial electronics and investigating qubits with layers. These stacks of electronic chips reroute the connections to attach vertically, as though perpendicular to our grid a kind of 3D integration. The change allows researchers to potentially connect, control, and read larger numbers of qubits. Through funding from QSA and other partners, theyve already built and tested a 2-stack qubit chip (with two layers), and QSA researchers are working on further enhanced versions. This milestone is an important step toward more densely packed qubits that can perform more complex calculations.

This illustration of the quantum sensor shows trapped beryllium ions (red dots) arranged into a 2D crystal. (Credit: S. Burrows/JILA/UC Boulder)

Any study that uses electronics is limited by random variations or noise that can hide the information researchers are searching for. Quantum systems, such as arrays of ultracold atoms, can be used to make extremely precise measurements that are better at picking the signal from the noise. Led by the University of Colorado Boulder, QSA researchers built a quantum sensor from 150 beryllium ions (atoms with an electric charge) arranged in a flat crystal. By using entangled particles, where a change in one immediately impacts the other, the quantum sensor measured electric fields with more than 10 times the sensitivity of any previously demonstrated atomic sensor. Picking up incredibly tiny changes makes such a sensor a powerful tool that could potentially enhance gravitational wave detectors or look for dark matter, one of the biggest mysteries in modern physics.

To improve quantum computers, researchers need a way to find and correct errors, such as a qubit randomly flipping between 0 and 1. Methods such as continuous quantum error correction (CQEC) keep an eye on qubits and look for telltale signs of problems but they too are subject to noise that can hide issues. QSA researchers at UC Berkeley designed a machine learning algorithm that can process the CQEC signals and find errors more accurately than current real-time methods. Because the new algorithm is flexible, learns on the job, and requires small amounts of computing power, it could improve continuous error correction systems and support larger and more stable quantum computers.

Our everyday computers use circuits with logic gates (such as AND, OR, and NOT) to perform operations. Quantum circuits can also use gates as their building blocks but instead of devices like transistors, their gates are made of qubits and interactions between qubits. While one or two entangled qubits can be used for basic operations, linking together many qubits can speed up computations, simplify quantum circuits, and make computers more powerful. QSA researchers led by Duke University developed a new, one-step method of creating these more versatile gates with multiple entangled qubits. Their technique expands logic operations for quantum computers, and includes a particular kind of gate (known as an N-Toffoli gate) that experts predict will be important in quantum adders, multipliers, and other algorithms including ones with applications in cryptography.

# # #

Founded in 1931 on the belief that the biggest scientific challenges are best addressed by teams, Lawrence Berkeley National Laboratory and its scientists have been recognized with 16 Nobel Prizes. Today, Berkeley Lab researchers develop sustainable energy and environmental solutions, create useful new materials, advance the frontiers of computing, and probe the mysteries of life, matter, and the universe. Scientists from around the world rely on the Labs facilities for their own discovery science. Berkeley Lab is a multiprogram national laboratory, managed by the University of California for the U.S. Department of Energys Office of Science.

DOEs Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.

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Five Ways QSA is Advancing Quantum Computing Berkeley Lab ... - Lawrence Berkeley National Laboratory (.gov)

Market Overview:Quantum computing is an area of computing focused on developing computer technology based on the principles of quantum theory (which explains the behavior of energy and material on the atomic and subatomic levels). Computers used today can only encode information in bits that take the value of 1 or 0-restricting their ability. Quantum computing, on the other hand, uses quantum bits or qubits. It harnesses the unique ability of subatomic particles that allows them to exist in more than one state (i.e., a 1 and a 0 at the same time).DriversFully scaled quantum technology is still a way off, but as quantum computing matures and becomes more readily available, we will see a rapid increase in the number of companies applying it to various industries. Some of the impacts is already being felt in different sectors. Many financial industry players rely on computing power to improve decision-making and better serve customers. Quantum computing is likely to drive these activities in the next few years. From a business line perspective, the most promising use cases are likely to be those that require highly complex and/or particularly fast models. For example, in valuation, the ability to quickly determine the best risk-adjusted portfolio may create a significant competitive advantage. For loan and bond portfolios, more accurate estimates of credit risk should lead to better optimization decisions. More broadly, capital allocation across a range of corporate finance activities could be improved through insight into the scale and importance of risk, while payments and transfers could be protected through better encryption. The impact of the COVID-19 pandemic shows that accurate and timely risk assessment remains a challenge for financial institutions. Even before 2020, the financial and economic crisis of the last 20 years has led to rapid changes in the way banks and other market participants assess and price risk across different asset classes. This has driven the introduction of increasingly sophisticated and real-time risk models infused by artificial intelligence (AI), but still based on classical computing. The arrival of quantum computing has the potential to be a game-changer. However, there is still some way to go before the technology can be rolled out on a large scale. Financial institutions have already started to acquire the necessary hardware and develop the quantum algorithms they need. The financial industry, including banks, could use quantum computing to increase the speed of transactions exponentially, enabling institutions to scale up processing at a lower cost than employing more IT or human resources.

Quantum Computing market reached a value of USD 785.27 million in 2022. It's expected that the market will achieve USD 6682.38 million by 2028, exhibiting a CAGR of 42.88% during the forecast period.

A thorough understanding of the Information Technology sector and its commercial potential is the aim of the market study. The Quantum Computing Market Report has 116 pages and has a detailed table of contents, a list of data, tables, and charts, along with an in-depth analysis.

Get a Sample PDF of report - https://www.precisionreports.co/enquiry/request-sample/22903697

Market Segmentation:Leading Players in the Quantum Computing Industry:Intel CorporationRigetti ComputingQC Ware CorpD-Wave Systems Inc.Atos SEGoogleQRA CorpIBM CorporationCambridge Quantum Computing Ltd.

To preserve their position, these big corporations relied on primary growth tactics such as product portfolio expansion, current trends, financing, mergers and acquisitions, partnerships, new product invention, and geographical development.

Based on Type:HardwareSoftwareServices

Based on Application:OptimizationMachine LearningSimulationOthers

Inquire or Share your Questions If any before the Purchasing this Report - https://www.precisionreports.co/enquiry/pre-order-enquiry/22903697

Key Factors Considered:COVID-19 - Amid the COVID-19 crisis, the Quantum Computing market has definitely taken a hit. The report describes the market scenario during and post the pandemic in the vision of upstream raw materials, major market participants, downstream major customers, etc. Other aspects, such as changes in consumer behavior, demand, transport capacity, trade flow under COVID-19, have also been taken into consideration during the process of the research. The epidemic is still causing tremendous disruption in industries throughout the world. We've been tracking the direct and indirect consequences of the COVID-19 outbreak on the Quantum Computing market. To Know How Covid-19 Pandemic will Impact this Industry - https://www.precisionreports.co/enquiry/request-covid19/22903697

Regional Conflict / Russia-Ukraine War - The report also presents the impact of regional conflict on this market in an effort to aid the readers to understand how the market has been adversely influenced and how it's going to evolve in the years to come.

Challenges & Opportunities - Factors that may help create opportunities and boost profits for market players, as well as challenges that may restrain or even pose a threat to the development of the players, are revealed in the report, which can shed a light on strategic decisions and implementation.

Organization: Precision ReportsPhone: US: +1 424 253 0807 | UK: +44 203 239 8187Email: sales@precisionreports.coWebsite: https://www.precisionreports.co/

Market is changing rapidly with the ongoing expansion of the industry. Advancement in the technology has provided today's businesses with multifaceted advantages resulting in daily economic shifts. Thus, it is very important for a company to comprehend the patterns of the market movements in order to strategize better. An efficient strategy offers the companies with a head start in planning and an edge over the competitors. Precision Reports is the credible source for gaining the market reports that will provide you with the lead your business needs.

This release was published on openPR.

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Quantum Computing Market Growth Insights 2023: Exceptional Companies Leading in Market Size and Share 2030 - openPR

Researchers have developed a new hybrid simulation process using quantum computers to solve electronic structure problems, potentially enabling quantum computers to tackle more complex chemical structures in the future.

Researchers at Argonne explore the possibility of solving the electronic structures of complex molecules using a quantum computer.

If you know the atoms that compose a particular molecule or solid material, the interactions between those atoms can be determined computationally, by solving quantum mechanical equations at least, if the molecule is small and simple. However, solving these equations, critical for fields from materials engineering to drug design, requires a prohibitively long computational time for complex molecules and materials.

Now, researchers at the U.S. Department of Energys (DOE) Argonne National Laboratory and the University of Chicagos Pritzker School of Molecular Engineering (PME) and Department of Chemistry have explored the possibility of solving these electronic structures using a quantum computer.

This is an exciting step toward using quantum computers to tackle challenging problems in computational chemistry. Giulia Galli

The research, which uses a combination of new computational approaches,was published online in the Journal of Chemical Theory and Computation. It was supported by Q-NEXT, a DOE National Quantum Information Science Research Center led by Argonne, and by the Midwest Integrated Center for Computational Materials (MICCoM).

This is an exciting step toward using quantum computers to tackle challenging problems in computational chemistry, said Giulia Galli, who led the research with Marco Govoni, a staff scientist at Argonne and member of the UChicago Consortium for Advanced Science and Engineering (CASE).

Predicting the electronic structure of a material involves solving complex equations that determine how electrons interact, as well as modeling how various possible structures compare to each other in their overall energy levels.

Unlike conventional computers that store information in binary bits, quantum computers use qubits that can exist in superposition of states, letting them solve certain problems more easily and quickly. Computational chemists have debated whether and when quantum computers might eventually be able to tackle the electronic structure problem of complex materials better than conventional computers. However, todays quantum computers remain relatively small and produce noisy data.

Prof. Giulia Galli and fellow researchers have explored the possibility of predicting the electronic structure of complex materials using a quantum computer, an advancement in fields from materials engineering to drug design. Credit: Image courtesy of Galli Group

Even with these weaknesses, Galli and her colleagues wondered whether they still could make progress in creating the underlying quantum computational methods required to solve electronic structure problems on quantum computers.

The question we really wanted to address is what is possible to do with the current state of quantum computers, Govoni said. We asked the question: Even if the results of quantum computers are noisy, can they still be useful to solve interesting problems in materials science?

The researchers designed a hybrid simulation process, using IBM quantum computers. In their approach, a small number of qubits between four and six perform part of the calculations, and the results are then further processed using a classical computer.

We designed an iterative computational process that takes advantages of the strengths of both quantum and conventional computers, said Benchen Huang, a graduate student in the Galli Group and first author of the new paper.

After several iterations, the simulation process was able to provide the correct electronic structures of several spin defects in solid-state materials. In addition, the team developed a new error mitigation approach to help control for the inherent noise generated by the quantum computer and ensure accuracy of the results.

For now, the electronic structures solved using the new quantum computational approach could already be solved using a conventional computer. Therefore, the longstanding debate of whether a quantum computer can be superior to a classical one in solving electronic structure problems is not settled yet.

However, the results provided by the new method pave the way for quantum computers to address more complex chemical structures.

When we scale this up to 100 qubits instead of 4 or 6, we think we might have an advantage over conventional computers, Huang said. But only time will tell for sure.

The research group plans to keep improving and scaling up their approach, as well as using it to solve different types of electronic problems, such as molecules in the presence of solvents, and molecules and materials in excited states.

Reference: Quantum Simulations of Fermionic Hamiltonians with Efficient Encoding and Ansatz Schemes by Benchen Huang, Nan Sheng, Marco Govoni and Giulia Galli, 15 February 2023, Journal of Chemical Theory and Computation.DOI: 10.1021/acs.jctc.2c01119

This work is supported by the U.S. Department of Energy National Quantum Information Science Research Centers as part of the Q-NEXT center and through the Midwest Integrated Center for Computational Materials (MICCoM). Headquartered at Argonne, MICCoM is funded by the DOE Office of Basic Energy Sciences.

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Quantum Leap: Unlocking the Secrets of Complex Molecules With ... - SciTechDaily