Nvidia Launches Accelerated Quantum Research Center to Advance AI-Quantum Integration

Nvidia Teams Up With Harvard, MIT to Supercharge Quantum Computing With AI

Nvidia GB200 NVL72 rack-scale system on display at CES 2025 (Credit: Emily Forlini) Nvidia is building a Boston-based research center where it will partner with researchers from Harvard and the Massachusetts Institute of Technology (MIT) to advance the field of quantum computing with AI. The so-called Nvidia Accelerated Quantum Research Center (NVAQC) will "integrate leading quantum hardware with AI supercomputers, enabling what is known as accelerated quantum supercomputing," Nvidia says. It opens later this year. While it remains to be seen what comes out of this partnership, Nvidia CEO Jensen Huang pointed to "drug discovery" and "materials development" as initial focuses. But that could take time. Huang said in January that quantum computers won't be "very useful" for another 20 years or so. Nvidia invites "commercial partners" to use the facility in addition to academics. All are searching for breakthroughs that will make large-scale, accelerated quantum supercomputers a reality. The center will run on Nvidia's latest GB200 NVL72 rack-scale systems. With a lot of power in a small space, these systems could "accelerate the adoption of AI algorithms in quantum computing research" and start to solve some of quantum computing's most challenging problems. "The NVAQC is a very special addition to the unique Boston area quantum ecosystem," says Mikhail Lukin, co-director of Harvard Quantum Initiative in Science and Engineering (HQI). "[It] has the potential to advance the research in areas ranging from quantum error correction to applications of quantum computing systems, accelerating quantum computing research and pulling useful quantum computing closer to reality." Nvidia is also hosting its first Quantum Day at its GTC 2025 conference this week, calling it "one of the most exciting areas in computer science." It will bring together industry experts "seeking to chart a course into the future of quantum computing."

Nvidia building quantum computing research center in Boston

GTC Nvidia is investing in a research center to advance quantum computing development, just weeks after its head honcho torpedoed the share price of quantum firms by declaring the tech is decades away from being useful. The California-based GPU biz announced at its GTC 2025 event in San Jose that it is building a research center on the opposite coast in Boston to develop cutting-edge technologies aimed at advancing quantum computing. Named the Nvidia Accelerated Quantum Research Center (NVAQC), it will focus on combining quantum tech with the company's AI hardware to develop what it calls "accelerated quantum supercomputers" capable of solving some of the world's toughest problems. We asked Nvidia how much it is investing in this venture, but it declined to add anything beyond the details in its announcement. The company is not short of spare change, having reported 2025 net income of $72.88 billion last month, up 145 percent year-on-year. Nevertheless, the AI chips maker can't be expecting to see a return on its quantum investment in the near future: CEO Jensen Huang famously remarked that practical quantum systems are likely still 20 years away. Speaking at a financial analyst session at the CES show in January, Huang claimed the industry is probably five to six orders of magnitude away from the number of qubits needed to make practical quantum computers. "If you said 15 years for very useful quantum computers that would probably be on the early side," he said. "If you said 30, it's probably on the late side. If you picked 20, I think a whole bunch of us would believe it." Several of the most prominent quantum computing specialists saw their share price plunge 50 percent following the remarks. Now Nvidia is teaming up with Quantinuum, Quantum Machines, and QuEra Computing as part of its NVAQC project, along with researchers from academia, including the Harvard Quantum Initiative in Science and Engineering (HQI) and the Engineering Quantum Systems (EQuS) group at the Massachusetts Institute of Technology (MIT). The center will deploy an "AI supercomputer" built around Nvidia's GB200 NVL72 rack-scale systems and Quantum-2 InfiniBand networking, incorporating 576 Blackwell GPUs. This hardware will be used for complex simulations of quantum systems and to develop low-latency hardware control algorithms essential for error correction, along with hybrid AI-quantum applications using Nvidia's DGX Quantum hardware and CUDA-Q development platform. Integrating quantum with conventional systems remains a major challenge. The decoding required for error correction can only function if data from millions of qubits can be transferred between quantum and classical hardware at ultralow latencies. Nvidia indicated that some of the work with Quantum Machines at the NVAQC will be on developing high-bandwidth interfaces for its GB200 superchips. Mikhail Lukin, a Professor at Harvard and co-director of HQI, said of the GPU giant's investment in the quantum research facility: "The accelerated quantum and classical computing technologies Nvidia is bringing together has the potential to advance the research in areas ranging from quantum error correction to applications of quantum computing systems, accelerating quantum computing research and pulling useful quantum computing closer to reality." Nvidia expects the NVAQC to begin operations later this year. ®

NVIDIA Accelerated Quantum Research Center to Bring Quantum Computing Closer

Boston-based NVAQC offers powerful tools for helping overcome the biggest quantum computing challenges. As quantum computers continue to develop, they will integrate with AI supercomputers to form accelerated quantum supercomputers capable of solving some of the world's hardest problems. Integrating quantum processing units (QPUs) into AI supercomputers is key for developing new applications, helping unlock breakthroughs critical to running future quantum hardware and enabling developments in quantum error correction and device control. The NVIDIA Accelerated Quantum Research Center, or NVAQC, announced today at the NVIDIA GTC global AI conference, is where these developments will happen. With an NVIDIA GB200 NVL72 system and the NVIDIA Quantum-2 InfiniBand networking platform, the facility will house a supercomputer with 576 NVIDIA Blackwell GPUs dedicated to quantum computing research. "The NVAQC draws on much-needed and long-sought-after tools for scaling quantum computing to next-generation devices," said Tim Costa, senior director of computer-aided engineering, quantum and CUDA-X at NVIDIA. "The center will be a place for large-scale simulations of quantum algorithms and hardware, tight integration of quantum processors, and both training and deployment of AI models for quantum." Quantum computing innovators like Quantinuum, QuEra and Quantum Machines, along with academic partners from the Harvard Quantum Initiative and the Engineering Quantum Systems group at the MIT Center for Quantum Engineering, will work on projects with NVIDIA at the center to explore how AI supercomputing can accelerate the path toward quantum computing. "The NVAQC is a powerful tool that will be instrumental in ushering in the next generation of research across the entire quantum ecosystem," said William Oliver, professor of electrical engineering and computer science, and of physics, leader of the EQuS group and director of the MIT Center for Quantum Engineering. "NVIDIA is a critical partner for realizing useful quantum computing." There are several key quantum computing challenges where the NVAQC is already set to have a dramatic impact. Protecting Qubits With AI Supercomputing Qubit interactions are a double-edged sword. While qubits must interact with their surroundings to be controlled and measured, these same interactions are also a source of noise -- unwanted disturbances that affect the accuracy of quantum calculations. Quantum algorithms can only work if the resulting noise is kept in check. Quantum error correction provides a solution, encoding noiseless, logical qubits within many noisy, physical qubits. By processing the outputs from repeated measurements on these noisy qubits, it's possible to identify, track and correct qubit errors -- all without destroying the delicate quantum information needed by a computation. The process of figuring out where errors occurred and what corrections to apply is called decoding. Decoding is an extremely difficult task that must be performed by a conventional computer within a narrow time frame to prevent noise from snowballing out of control. A key goal of the NVAQC will be exploring how AI supercomputing can accelerate decoding. Studying how to collocate quantum hardware within the center will allow the development of low-latency, parallelized and AI-enhanced decoders, running on NVIDIA GB200 Grace Blackwell Superchips. The NVAQC will also tackle other challenges in quantum error correction. QuEra will work with NVIDIA to accelerate its search for new, improved quantum error correction codes, assessing the performance of candidate codes through demanding simulations of complex quantum circuits. "The NVAQC will be an essential tool for discovering, testing and refining new quantum error correction codes and decoders capable of bringing the whole industry closer to useful quantum computing," said Mikhail Lukin, Joshua and Beth Friedman University Professor at Harvard and a codirector of the Harvard Quantum Initiative. Developing Applications for Accelerated Quantum Supercomputers The majority of useful quantum algorithms draw equally from classical and quantum computing resources, ultimately requiring an accelerated quantum supercomputer that unifies both kinds of hardware. For example, the output of classical supercomputers is often needed to prime quantum computations. The NVAQC provides the heterogeneous compute infrastructure needed for research on developing and improving such hybrid algorithms. New AI-based compilation techniques will also be explored at the NVAQC, with the potential to accelerate the runtime of all quantum algorithms, including through work with Quantinuum. Quantinuum will build on its previous integration work with NVIDIA, offering its hardware and emulators through the NVIDIA CUDA-Q platform. Users of CUDA-Q are currently offered access to Quantinuum's System H1 QPU hardware and emulator for 90 days. "We're excited to collaborate with NVIDIA at this center," said Rajeeb Hazra, president and CEO of Quantinuum. "By combining Quantinuum's powerful quantum systems with NVIDIA's cutting-edge accelerated computing, we're pushing the boundaries of hybrid quantum-classical computing and unlocking exciting new possibilities." QPU Integration Integrating quantum hardware with AI supercomputing is one of the major remaining hurdles on the path to running useful quantum hardware. The requirements of such an integration can be extremely demanding. The decoding required by quantum error correction can only function if data from millions of qubits can be sent between quantum and classical hardware at ultralow latencies. Quantum Machines will work with NVIDIA at the NVAQC to develop and hone new controller technologies supporting rapid, high-bandwidth interfaces between quantum processors and GB200 superchips. "We're excited to see NVIDIA's growing commitment to accelerating the realization of useful quantum computers, providing researchers with the most advanced infrastructure to push the boundaries of quantum-classical computing," said Itamar Sivan, CEO of Quantum Machines. Key to integrating quantum and classical hardware is a platform that lets researchers and developers quickly shift context between these two disparate computing paradigms within a single application. The NVIDIA CUDA-Q platform will be the entry point for researchers to harness the NVAQC's quantum-classical integration. Building on tools like NVIDIA DGX Quantum -- a reference architecture for integrating quantum and classical hardware -- and CUDA-Q, the NVAQC is set to be an epicenter for next-generation developments in quantum computing, seeding the evolution of qubits into impactful quantum computers.

Nvidia will build accelerated quantum computing research center

Nvidia said it is building a Boston-based research center to provide cutting-edge technologies to advance quantum computing. The Nvidia Accelerated Quantum Research Center, or NVAQC, will integrate leading quantum hardware with AI supercomputers, enabling what is known as accelerated quantum supercomputing. The NVAQC will help solve quantum computing's most challenging problems, ranging from tackling qubit noise to the transformation of experimental quantum processors into practical devices. Building this new center seems to be politically symbolic. The Trump administration has been hostile toward big companies building anything offshore. By creating an important new center in the U.S., Nvidia can show it's creating American jobs in a technology field that is critical to U.S. competitiveness. Leading quantum computing innovators, including Quantinuum, Quantum Machines and QuEra Computing, will tap into NVAQC to drive advancements through collaborations with researchers from leading universities, such as the Harvard Quantum Initiative in Science and Engineering (HQI) and the Engineering Quantum Systems (EQuS) group at the Massachusetts Institute of Technology (MIT). "Quantum computing will augment AI supercomputers to tackle some of the world's most important problems, from drug discovery to materials development," said Jensen Huang, founder and CEO of Nvidia, in a statement. "Working with the wider quantum research community to advance CUDA-quantum hybrid computing, the Nvidia Accelerated Quantum Research Center is where breakthroughs will be made to create large-scale, useful, accelerated quantum supercomputers." Through the NVAQC, commercial and academic partners will work with Nvidia to use Nvidia GB200 NVL72 rack-scale systems, or powerful hardware for quantum computing applications. This enables complex simulations of quantum systems and the deployment of the low-latency quantum hardware control algorithms essential for quantum error correction. Nvidia GB200 NVL72 systems will also accelerate the adoption of AI algorithms in quantum computing research. To address the challenges of integrating GPU and QPU hardware, the NVAQC will employ the Nvidia CUDA-Q™ quantum development platform, enabling researchers to develop new hybrid quantum algorithms and applications. The HQI -- a community of researchers dedicated to advancing the science and engineering of quantum systems and their applications -- will collaborate with the NVAQC to advance their research on next-generation quantum computing technologies. "The NVAQC is a very special addition to the unique Boston area quantum ecosystem, including word-leading university groups and startup companies," said Mikhail Lukin, professor at Harvard and a co-director of HQI, in a statement. "The accelerated quantum and classical computing technologies NVIDIA is bringing together has the potential to advance the research in areas ranging from quantum error correction to applications of quantum computing systems, accelerating quantum computing research and pulling useful quantum computing closer to reality." Researchers from the EQuS group, a member of the MIT Center for Quantum Engineering -- which serves as a hub for research, education and engagement in support of quantum engineering -- will use NVAQC to develop techniques such as quantum error correction. "The Nvidia Accelerated Quantum Research Center will provide EQuS group researchers with unprecedented access to technologies and expertise needed to solve the challenges of useful quantum computing," said William Oliver, professor of electrical engineering and computer science, and of physics, leader of the EQuS group, and director of the MIT Center for Quantum Engineering, in a statement. "We anticipate the future will also include other members of the Center for Quantum Engineering at MIT. Integrating the Nvidia accelerated computing platform with qubits will help tackle core challenges like quantum error correction, hybrid application development and quantum device characterization." The NVAQC is expected to begin operations later this year.

Nvidia just announced a super computer team-up to make quantum powers usable

Nvidia is working on a computer that combines AI, super-computing and quantum in one machine to rule them all. This will be born in the newly revealed Nvidia Accelerated Quantum Research Center (NVAQC). Nvidia made the major announcement for quantum computing fans from its GTC Global AI Conference today. Recommended Videos One of the issues for quantum computing has been scaling. This new center could help to tackle that problem right away for next-generation computing, soon. Get your weekly teardown of the tech behind PC gaming ReSpec Subscribe Check your inbox! Privacy Policy A major stumbling block for quantum computing is sorting through the qubit errors that naturally occur. As qubits interact with their surrounding this creates noise which needs to be isolated. This is done by processing outputs from repeated measurements of these noisy qubits. The process of identifying, tracking and correcting qubit errors is called decoding. This is where AI and supercomputing come in, as these combined could help to accelerate decoding - the goal of this new NVAQC facility. A team effort While Nvidia is creating the space for this research to take place, it is not going it alone. Quantum computing innovators will come together to work on the problems, including Quantinuum, QuEra and Quantum Machines. Academic partners are also taking part with partners in Harvard Quantum Initiative and the Engineering Quantum Systems group at the MIT Center for Quantum Engineering. "The NVAQC draws on much-needed and long-sought-after tools for scaling quantum computing to next-generation devices," said Tim Costa, senior director of computer-aided engineering, quantum and CUDA-X at NVIDIA. He said: "The center will be a place for large-scale simulations of quantum algorithms and hardware, tight integration of quantum processors, and both training and deployment of AI models for quantum." Nvidia gave the statement: "Building on tools like NVIDIA DGX Quantum -- a reference architecture for integrating quantum and classical hardware -- and CUDA-Q, the NVAQC is set to be an epicenter for next-generation developments in quantum computing, seeding the evolution of qubits into impactful quantum computers."

Nvidia bets on quantum computing with new Boston research center

Nvidia (NVDA+0.80%) is partnering with quantum computing companies Quantinuum, QuEra Computing, and more to build a Boston-based research center that will integrate quantum computing with AI supercomputers. The Nvidia Accelerated Research Quantum Center, or NVAQC for short, will strive to make large-scale, useful, accelerated quantum supercomputers. "Quantum computing will augment AI supercomputers to tackle some of the world's most important problems, from drug discovery to materials development," Nvidia CEO Jensen Huang said in a press release. Major quantum companies will provide researchers from Harvard and MIT with "unprecedented access to the technologies and expertise needed to solve the challenges of useful quantum computing," MIT professor of electrical engineering and computer science William Oliver said in a prepared statement. The move might come as a surprise to some, considering the Nvidia chief's comments voicing uncertainty in the near-term applicability of quantum computing mere months ago. Earlier this year, Huang made headlines and tanked quantum stocks with his assessment that useful quantum computers were at least 15 to 30 years away. But he seems to have regretted his words as he hosted a league of quantum computing executives on Thursday at the first "quantum day" as part of the company's GPU tech conference (GTC). Huang started the panel on Thursday by apologizing for his comments, going on to say that this was "the first event in history where a company CEO invites all of the guests to explain why he was wrong." It's uncertain if investors are convinced, though: Quantum computing stocks IonQ (IONQ-10.00%) and Rigetti Computing (RGTI-10.10%) ended the day down more than 9% on Thursday following the panel. The center will be operational later this year, but the "plumbing for this has been in place for a while," according to Rajeeb Hazra, CEO of Quantinuum -- a founding partner of the center and a privately held company born through a merger of U.S.-based Honeywell (HON+0.69%) quantum solutions and U.K.-based Cambrige Quantum. Quantinuum's technology has been integrated with Nvidia's open-source quantum development platform CUDA-Q since 2022, the same system that will be used at the research center. The center will be accelerating research in two areas, according to Hazra: making quantum computers better and more error resilient, and developing specific use-cases for these computers in fields such as pharmaceuticals, agriculture, and carbon sequestration technology. While he acknowledges that there is more work to be done, Hazra is more optimistic than Huang on the timeline for quantum-computing usability. "I think Jensen's postulate was getting useful work out is a long time away. We disagree, because we are getting useful work out today, and particularly with the combination of classical and quantum computers," Hazra said. Quantinuum says that the company's trapped-ion quantum computers are doing work that cannot be simulated on classical computers as of 2024. "So by running a quantum computer, you are now generating unique data you could have never had before," he said. Hazra also expects to use the center as a "premier test bed to accelerate" generative AI systems that use quantum computing. Hazra and a slew of other tech executives, like IBM (IBM-3.31%) CEO Arvind Krishna, are bullish about the potential for discovery that comes from "turbocharging AI with quantum data." Quantum computers work on the subatomic level and are probabilistic models. They not only are significantly faster than classical computers in some circumstances, they also have the potential to go beyond already produced knowledge, to then give artificial intelligence agents insights about nature on a subatomic level.