#hybridcomputing

NERSC Requests Proposals for 2026: Quantum Information Science Research Can Use 20,000 GPU Node Hours

QIS@Perlmutter

The National Energy Research Scientific Computing Centre (NERSC) has issued the QIS@Perlmutter 2026 Call for Proposals for quantum information science (QIS) experiments on the powerful Perlmutter supercomputer. This contest offers large computing resources with up to 20,000 GPU node hours for accepted proposals. Berkeley Lab hosts NERSC, the U.S. Department of Energy Office of Science's mission computing facility, which supports physics, chemistry, and materials science research.

Boosting QIS and Hybrid Computing

A key goal of QIS@Perlmutter is to develop quantum tools, methodologies, software, and algorithms to further QIS. Hybrid computing, which links quantum systems to classical HPC to promote materials science and chemistry, is a priority.

Accepted quantum science research includes many significant topics. All aspects of quantum information science are project-friendly:

Quantum chemical and material modelling.

Compilation and simulation schemes for quantum circuits.

Quantum computing error prevention.

Software development for quantum computing stacks.

Developing and testing hybrid quantum-classical codes.

Studies comparing HPC with quantum computing systems.

Quantum physics is accelerated by employing Perlmutter's GPUs and other cutting-edge classical computers to solve challenging problems.

High-performance Perlmutter resources and software

This allocation uses the NVIDIA A100 GPU-powered Perlmutter supercomputer. For the NERSC 2026 Allocation Year, selected candidates can use up to 20,000 GPU node hours. Importantly, each Perlmutter GPU node has four A100 GPUs.

Researchers will have access to modern quantum research software and libraries. These include NVIDIA's CUDA-QX and cuQuantum tools, which simplify GPU tensor network and state vector simulation. Qiskit, PennyLane, Quimb, and ITensor are better, more accessible software.

Additionally, winners will work with Nvidia and NERSC staff. This relationship aids recipients with workflow optimisation, project issues, and GPU use.

Qualifications and Allocation Year

All applicants can apply, and NERSC users are not required. Computer science, physics, and materials researchers in academia, industry, and national labs should submit proposals.

In addition to quantum information science research, proposals are evaluated on utilisation criteria:

Leveraging Perlmutter Features: Candidates must demonstrate a well-planned approach to using the system's all-flash scratch file system and over 6,000 NVIDIA A100 GPUs.

Planning for Doudna Capabilities: Proposals should describe how they will leverage the future supercomputer's functionalities. Interactive workflows, Quantum-X800 InfiniBand networking, and NVIDIA Vera-Rubin CPU-GPU compatibility are included.

Social and DOE Impact: Projects that assist the Department of Energy Office of Science's research aims or society will be prioritised.

The allotment spans January 16, 2027, to NERSC 2026. Projects must finish by this date. Project winners must submit a final summary and bimonthly progress reports.

Application and Open Science Needs

Applications are accepted online and reviewed continuously. Please submit by March 1, 2026, to be considered.

Since NERSC is a national user facility of the Department of Energy Office of Science dedicated to open scientific research, all awarded projects must be published or presented in open forums. Every project must fulfil NERSC permissible usage policies. An “Institutional User Agreement” is needed if the study doesn't secure federal funding.

ICDS Quantum Hub awards Quantum SuperSEED funds

Quantum SuperSEED

Three cooperating research teams will receive Penn State Institute for Computational and Data Sciences' Quantum Hub funding to study basic quantum physics.

Quantum SuperSEED funding was awarded to three Penn State faculty research teams by the Quantum Hub of the Penn State Institute for Computational and Data Sciences. The Quantum Hub of the Institute for Computational and Data Sciences will support Penn State faculty-led collaborative research teams.

Also see Penn State ICDS Funds 20 AI and quantum science fellows.

The effort intends to enhance quantum science, engineering, and computation by bringing together Penn State experts from several departments and disciplines to solve difficult issues. The hub will fund research projects over $500,000. The Quantum Hub is investing this money to support sixteen faculty members in three funded initiatives. Eberly College of Science and Penn State College of Engineering faculty participate. The funds will also assist postdocs, graduate students, and ICDS research equipment and computer resources.

Mahmut Kandemir, director of the Quantum Hub and a computer science and engineering professor, says the grant program is funding three projects that demonstrate Penn State's quantum strengths and ability to lead in new national fields. “With this one-year seed support, we hope that participating faculty will launch new research directions, establish long-lasting partnerships, boost competitiveness for significant external opportunities, and help establish Penn State as a leading quantum innovation hub,” Kandemir said.

ICDS director Guido Cervone said the recently founded Quantum Hub is sponsoring prominent quantum research in several scientific and technical sectors, advancing ICDS's goal. The Quantum SuperSEED grant program is funding three academic teams to study materials, many-body systems, and quantum computing to promote Penn State's quantum research. The cooperative research endeavours will use quantum science tools including simulations, hybrid computing, and AI to materials science, engineering, and computer science.

Professor of engineering science, mechanics, physics, and materials science and engineering Venkatraman Gopalan leads one of the selected teams. The institution must promote and advance quantum research, he said. Gopalan says the endeavour joins diverse experts who want Penn State to lead electro-optic quantum transduction globally. He said the funding is timely and connects quantum research and education, harnessing strengths across disciplines. He hopes this continues in the future.

Selection of Faculty and Projects: "Open Quantum Systems Beyond Markovianity:

Establishing a Multidisciplinary Quantum Computing and Simulation Community

The lead investigator is physics assistant professor Zhen Bi.

Xiantao Li, Thomas Iadecola, Sarah Shandera, and Chunhao Wang, assistant professors of computer science and engineering, are co-PIs.

“Superior Cryogenic Electro-Optical Thin Films for Quantum Transduction from Microwave to Optical” PI: Venkatraman Gopalan, professor of engineering science, mechanics, physics, and materials science.

Yang Yang, an associate professor of engineering science and mechanics; Binghai Yan, a physics professor; Yinming Shao, a physics assistant professor; and Long-Qing Chen, a math, engineering, and materials science educator, are co-PIs.

Penn State Quantum Information Science Research Gateway: Coherent Rock Salt Josephson Junctions

Jon-Paul Maria, Dorothy Pate Enright Materials Science and Engineering Professor, is Principal Investigator.

NVIDIA and AIST present the world's largest quantum research supercomputer, ABCI-Q. NVIDIA announced that Global Research and Development Centre for Business by Quantum-AI Technology (G-QuAT) houses ABCI-Q, the largest quantum computing research supercomputer.

Quantum processors could help AI supercomputers solve complex problems in healthcare, energy, and finance. ABCI-Q enables unprecedented quantum-GPU computation, advancing the development of usable, accelerated quantum systems.

G-QuAT ABCI-Q supercomputer

Quantum computing research advanced today with the opening of the Global Research and Development Centre for Business by Quantum-AI Technology (G-QuAT) and the ABCI-Q supercomputer. Japan's National Institute of Advanced Industrial Science and Technology (AIST) deployed ABCI-Q, the world's largest quantum computing research supercomputer, with NVIDIA. This alliance accelerates quantum error correction and application development to build viable, faster quantum supercomputers.

ABCI-Q prepares researchers to use quantum computing fully. It provides a strong hybrid architecture to accelerate quantum computing application development. Japanese researchers can examine quantum computing technology's basic difficulties and accelerate real-world application development. Researchers can test quantum computing stepping-stone devices with the technique.

Advanced Hardware-Software Integration

The powerful ABCI-Q has cutting-edge hardware. NVIDIA Quantum-2 InfiniBand links 2,020 H100 GPUs. For complex quantum computing applications, this configuration enables fast data transfer and parallel computation.

The open-source hybrid computing platform NVIDIA CUDA-Q complements the hardware. Practical, large-scale quantum computing applications require hardware and software coordination, which CUDA-Q provides. It provides one framework for classical and quantum devices to work smoothly.

Multiple Quantum Processor Integration

ABCI-Q's capacity to integrate with partner quantum computers is a key feature. This flexible setup lets researchers study qubit modalities and construct hybrid quantum-GPU workloads. The system includes:

Fujitsu superconducting qubit.

A neutral-atom quantum processor from QuEra.

OptQC's photon processor.

ABCI-Q's versatility and research potential are boosted by using cutting-edge quantum processors from top companies, allowing full testing of quantum technologies. The architecture supports large-scale quantum applications and hybrid quantum-GPU workloads across these qubit modalities.

Impact on Industry and Research

ABCI-Q advances the development of useful, quicker quantum systems. Integrating AI supercomputing with quantum hardware is expected to accelerate quantum computing's promise for everyone. AI supercomputers could solve the world's hardest issues with quantum processors.

The system can solve complex healthcare, energy, and financial issues. AI and quantum computing allow scientists to examine previously inconceivable solutions.

ABCI-Q is crucial to working quantum systems and error correction and application development, according to NVIDIA's senior director of computer-aided engineering, quantum, and CUDA-X, Tim Costa. Masahiro Horibe, deputy director of G-QuAT and AIST, noted that ABCI-Q's NVIDIA accelerated computing platform lets researchers evaluate quantum computing's foundational technologies.

From GenAI to Quantum Computing: Tech trends that will define 2025

As we approach 2025, the technology environment is poised for dramatic change, predicted to redefine many sectors and affect how people live and work. The following are the key trends to watch as we enter this new era of innovation:

Advancement of quantum computing.

Quantum computing is no longer a future idea; it is poised to become a game changer for sectors that rely on intricate problem-solving. By 2025, quantum computing capabilities will likely develop, with substantial implications for banking and healthcare.

Use case

Material simulation: Researching medicines and battery chemistry.

Banking and Finance: Pricing optimization and the identification of fraud

Automotive and Aerospace: The dilemma of the paint shop and fluid dynamics

Metaverse's Evolution

By 2025, the metaverse, a virtual realm where individuals may communicate, work, and play, will have evolved significantly. Companies like Meta (previously Facebook) and Epic Games are at the forefront of developing virtual environments where users can conduct business meetings, social interactions, and entertainment. Nike, for example, has already built a virtual store in the metaverse, where people can purchase and experience the brand digitally.

Usage

Virtual event management, Metaverse e-commerce, virtual education platforms, Metaverse games, social networking platforms, tourism experiences, NFT markets, and other offerings.

Agentic AI

Organizations have long wanted to promote high-performing teams, improve cross-functional collaboration, and coordinate issues across team networks. Agentic AI, a popular software program, helps CIOs achieve their vision for generative AI to boost productivity by performing tasks independently and providing insights from derivative events.

Use Cases:

Customer interactions are becoming automated by data analysis to make calculated judgments at every step.

Using plain language, workers may build and manage increasingly complex technological tasks.

AI Governance Platforms

AI governance platforms are rapidly being employed in businesses with stringent requirements to manage and oversee AI systems ethically and responsibly. By 2028, organizations that use AI governance systems are likely to outperform their competitors in terms of consumer trust ratings and regulatory compliance scores. These platforms help verify that AI systems make fair judgments, secure data, and follow rules, making them an essential tool for IT leaders in industries like banking.

Use Cases:

Assessing the possible risks and problems that AI systems may cause, such as prejudice, privacy infringement, and negative social consequences.

Guiding AI models through the model governance process, ensuring that all required gates and controls are followed throughout the model's life cycle.

Hybrid Computing

Hybrid computing is a system that employs different technologies to address complicated computational issues, allowing organizations to expand rapidly, save money, and remain flexible. This method enables enterprises to operate core programs on local servers for security and control, using the cloud for high-performance activities such as data analytics and artificial intelligence. It also enables firms to use emerging technologies such as biocomputing and quantum systems for disruptive impact.

Use Cases:

Cost-effective scalability: Critical workloads should be kept in-house for security reasons, with the cloud handling peak demands during busy seasons.

Optimizing Data Security and Compliance: Maintaining critical data on-premises, adhering to tight data protection standards, and leveraging the cloud for less sensitive activities or analytics.

Promoting innovation and development: Using cloud-based development tools while preserving safe on-premises settings for production.

Conclusion

The technological developments that will shape 2025 provide many opportunities for innovation and expansion in various sectors. Adopting these trends can help businesses stay competitive while fostering a safer, sustainable, and interconnected future.

Read More:

How Generative AI Can Help Transform Loan Underwriting While Meeting all Compliance Needs?

Physical qubits

Physical and logical qubits news

At Microsoft, they’re advancing a new computing paradigm by fusing quantum computing with the power of artificial intelligence and the cloud. Microsoft Azure Quantum computation platform offers integration with cloud HPC and AI, allowing the smooth execution of quantum applications that take use of hardware across a range of qubits architectures and processors.

Atom Computing

In an effort to fulfill the platform’s objective, they haven’t stopped announcing new developments and partnerships over the last year. Examples of these include providing Accelerated DFT and Generative Chemistry, as well as pushing the field toward dependable quantum computing by showcasing very dependable logical qubits. With a secure, unified, and scalable hybrid computing environment provided by this solid compute foundation, innovators may create best-in-class solutions to solve challenges that are challenging or even unsolvable for traditional computers.

They are combining Azure quantum control, processing, and error correction software with quantum hardware designs from ecosystem partners, along with features for multi-modal AI models, developer tools, copilot-assisted workflows, and classical supercomputing. This next generation of hybrid apps will be made possible by this diversified computing stack. Using both classical and scaled quantum tools at the appropriate phases to create significant insights in an iterative loop to shorten R&D and time-to-solution into days, not years, AI co-reasoning will help clarify challenges and convert them into processes.

Quantinuum Quantum Computer

Maintaining Quantinuum’s implementation of dependable quantum computing

Atom computing are pleased to announce today, in partnership with Quantinuum, the demonstration of the highest number of entangled logical qubits, as well as the best performing logical qubits ever recorded. By refining and streamlining Azure’s physical qubits -virtualization method, they were able to produce 12 logical qubits for Quantinuum’s 56 physical qubits H2 machine.

This development demonstrates Microsoft’s superior error correcting capabilities. Their enhanced qubit-virtualization technology increased countability of logical qubits in less than six months. Furthermore, all 12 logical qubits showed a 22X improvement in circuit error rate over the equivalent physical qubits when they entangled them in a complex state needed for “deeper” quantum processing.

Quantinuum Microsoft

Azure systems’ capacity to more than double their physical qubits count from 30 to 56 while tripling the amount of logical qubits is evidence of the strong fidelities and all-to-all connectivity of their H-Series trapped-ion technology. Microsoft’s qubit-virtualization solution along with it’s existing H2-1 hardware is enabling us to completely transition both the clients and ourselves into Level 2 robust quantum computing. When paired with Azure Quantum’s cutting-edge AI and HPC technologies, this strong partnership will enable even further improvements.

Noise continues to be Microsoft greatest obstacle as to work toward using quantum computers to achieve scientific and commercial advances. They pointed out in an earlier piece that robust quantum error correction cannot be achieved only by adding more physical qubits. As members of the quantum ecosystem, Atom computing need to keep their attention on logical qubit counts and fidelity improvements in order to have a strong basis for delivering significant outcomes.

Improvements in both hardware and software will make this feasible, allowing longer-running and more dependable quantum applications. The news made today shows that achieving these foundational skills is feasible in the direction of large-scale quantum computing.

A real paradigm shift in computing also requires an emphasis on useful and profitable applications. In the first end-to-end workflow, they had effectively finished a chemical simulation in which is to used logical qubit computing, AI, and HPC to estimate the ground state energy for a particular catalyst issue.

Microsoft Quantinuum

With the scalability of quantum technologies, a new generation of hybrid applications will gain more influence, and this demonstration was a crucial first step in that direction. Scientists at Microsoft have shown how this combination has the potential to be revolutionary, and quantum and AI will have the first real influence on scientific discoveries. Only because of Azure’s strong and ongoing partnership with Quantinuum a business that is still at the forefront of quantum computing was this work made feasible.

Latest advancements in logical qubits and the technical specifications of an end-to-end chemical simulation created by Microsoft and Quantinuum. Together, they have created 12 logical qubits.

Atom Computing Quantum

Introducing Atom Computing’s next business venture

Finally, Microsoft Azure are thrilled to be working with Atom Computing to provide consumers a new breed of dependable quantum hardware. They are refining the system to allow dependable quantum processing by combining Atom Computing’s neutral-atom hardware with Microsoft’s improved qubit-virtualization architecture. Together, they have developed logical qubits. All things considered, they think that this new commercial product will be the most powerful quantum machine ever made, capable of scaling to the limits of science and beyond.

Large numbers of high-fidelity qubits, all-to-all qubit connection, lengthy coherence durations, and mid-circuit measurements with qubit reset and reuse are just a few of the qualities that Atom Computing’s hardware uniquely combines and which are crucial for extending quantum error correction. With approximately 1,200 physical qubits in its second generation devices, the business aims to tenfold the number of physical qubits with every successive hardware generation.

Microsoft Azure Quantum computation platform can provide the clients with flexibility and future-proof their investments by offering a range of best-in-class logical qubits across several hardware platforms, all thanks to the use of Microsoft’s cutting-edge fault-tolerance protocols on alternative qubit architectures.

Together, Microsoft and Atom Computing are improving the Azure Quantum computation platform with neutral-atom hardware and customized qubit virtualization. This allows for the creation of a commercial discovery suite that can be upgraded continuously to accommodate more logical qubits.

Quantum HPC is a new discipline that combines quantum computing with high-performance computing (HPC).

Breakdown of the idea:

HPC systems use parallel processing to solve complicated problems that single computers cannot. Scientific models, medicine research, and weather forecasting use them extensively.

Quantum Computing: Quantum computers compute using quantum mechanics. Traditional computers utilise bits (0 or 1), but quantum computers employ qubits, which can be superposed. This makes them faster than classical computers at solving specific tasks.

HPC Quantum Computing

While powerful, older HPC systems have task constraints. But quantum computers excel at tackling problems that traditional computers find exponentially complex. This gap is addressed by quantum HPC:

Quantum Circuit Optimisation: HPC systems can build and optimise quantum circuits for quantum computers, enhancing efficiency and accuracy.

Verifying outcomes: HPC can verify small-scale quantum computation outcomes. Researchers are developing hybrid algorithms that use classical and quantum computers to solve complicated issues.

Quantum HPC benefits:

This connection could revolutionise fields like:

Materials Science: Simulating complicated materials for medicine, battery, and catalyst development.

Financial modelling: Portfolio optimisation and risk management.

Cryptography: Breaking encryption and creating post-quantum cryptography.

Current Status:

Quantum HPC is young. Maintaining quantum coherence and scaling quantum computers are continuing scientific issues. Japanese organisations like RIKEN Centre for Computational Science are creating quantum-HPC hybrid platforms.

Future Outlook:

Quantum HPC could boost scientific discoveries and technological innovation. We may expect to see more progress in merging classical and quantum computing to solve the world’s hardest issues.

IBM Quantum system has been chosen by RIKEN to be built into the supercomputer Fugaku.

RIKEN is a Japanese national research centre that has agreed to use IBM’s best-performing quantum processor and next-generation quantum computer architecture at the RIKEN Centre for Computational Science in Kobe, Japan. This is the one and only occasion that the supercomputer Fugaku and a quantum computer will be together.

A division of the Japanese Ministry of Economy, Trade, and Industry (METI), NEDO backs the “Development of Integrated Utilisation Technology for Quantum and Supercomputers” as a component of the “Project for Research and Development of Enhanced Infrastructures for Post-5G Information and Communications Systems.”” This agreement was signed as part of RIKEN’s ongoing project.

IBM Quantum System 2

IBM’s Quantum System Two design is only used by RIKEN for the purposes of putting its project into action. RIKEN, SoftBank Corp., the University of Tokyo, and Osaka University are working together on a project to show how useful these kinds of hybrid computing platforms will be for providing services in the future after 5G. The goal is to improve business and science in Japan.

In addition to the project, IBM will work on building the software stack needed to create and run integrated quantum-classical workflows in a quantum-HPC hybrid system with different types of computers. With these new features, algorithm quality and processing times will be able to be made better.

IBM plans to introduce its next-generation quantum computing architecture with IBM Quantum System Two, which will be installed at RIKEN and connected to Fugaku. This system will include expandable cryogenic infrastructure, modular quantum control electronics, and advanced system software to provide quantum computing services that work with traditional HPC services. These are the core parts of IBM’s vision for quantum-centric supercomputing.

Quantum Centric Supercomputing

Quantum-centric supercomputing is made possible by combining quantum and classical computing tools and using them to run computations faster than ever before. IBM thinks that quantum computing will be an important part of the design of quantum-centric supercomputing, which is the future of traditional HPC. And IBM Quantum System Two is one of the most important parts of this design.

A 133-qubit “IBM Quantum Heron” processor will run the system. The IBM Heron is the first in a new line of quantum processors. Its design brings the best performance of any IBM quantum processor released so far. Experiments done on IBM Heron had the lowest error rates of any IBM Quantum processor. This was five times better than the previous best records set by IBM Eagle, which can now be accessed through the cloud.

As the number of qubits grows and the accuracy gets better, NISQ’s advanced quantum computers are now ready to be used in real life. In the eyes of the HPC, quantum computers are machines that speed up science programmes that are usually run on supercomputers and make it possible to do calculations that supercomputers can’t do yet.

The head of the Quantum HPC Collaborative Platform Division at the RIKEN Centre for Computational Science, Dr. Mitsuhisa Sato, said, “RIKEN is committed to developing system software for quantum-HPC hybrid computing by leveraging its extensive scientific research capabilities and experience in the development and operation of cutting-edge supercomputers such as Fugaku.”

“IBM’s agreement with RIKEN is a huge step towards a future dominated by quantum-centric supercomputing,” said Jay Gambetta, IBM Fellow and Vice President, IBM Quantum. “It is the first quantum system that will directly connect with the Fugaku classical supercomputer.” “This work moves the field closer to a modular and adaptable structure that combines quantum computing and communication with traditional computing resources. This way, both can be used together to solve problems that get harder to solve.”

IBM has advanced significantly in artificial intelligence, quantum computing, cloud solutions tailored to specific industries, and consulting. These innovations give our customers a lot of open and flexible choices. IBM has a long history of committing to trust, openness, responsibility, inclusion, and service.

Regarding RIKEN

The largest research institute in Japan for both basic and applied study is RIKEN. The top scientific and technology journals publish around 2500 articles authored by RIKEN researchers annually. The subjects covered in these papers are many and include biology, chemistry, physics, engineering, and medical research. RIKEN is renowned for its outstanding research all over the world because of its focus on globalisation and multidisciplinary cooperation.