NVIDIA has announced the establishment of the NVIDIA Accelerated Quantum Research Center (NVAQC) during its global GTC conference, a new space dedicated to bringing quantum computing closer to the real world through its integration with artificial intelligence supercomputers.
This cutting-edge center will feature an NVIDIA GB200 NVL72 system and the NVIDIA Quantum-2 InfiniBand network platform, housing 576 NVIDIA Blackwell GPUs dedicated to quantum research.
A Bridge Between AI and Quantum Computing
The goal of the NVAQC is to advance key areas such as quantum error correction, the development of hybrid applications that combine classical and quantum computing, and the efficient integration of quantum processing units (QPUs) with conventional architectures.
The interaction between qubits and their environment generates noise, which poses one of the main challenges for quantum computing. Therefore, one of the primary focuses of the center will be research on AI-accelerated decoders capable of identifying and correcting quantum errors in real time. This work will be developed on the NVIDIA GB200 Grace Blackwell superchips, aiming to reduce latency and increase the reliability of quantum systems.
International and Academic Collaborations
Pioneering companies like Quantinuum, QuEra, and Quantum Machines, along with prestigious academic institutions such as the Harvard Quantum Initiative and the MIT Quantum Engineering Center, will work alongside NVIDIA at the NVAQC.
“Collaboration with NVIDIA will be key to designing and evaluating new quantum error correction codes,” stated Mikhail Lukin, a Harvard professor and co-director of the university’s Quantum Initiative.
For its part, Quantinuum will integrate its systems and emulators with the NVIDIA CUDA-Q platform, providing researchers access to these resources for 90 days.
Quantum-Classical Integration: A Major Challenge
Another objective of the NVAQC is to overcome the difficulties of integrating quantum hardware with classical supercomputing. To this end, Quantum Machines will work with NVIDIA to develop new control technologies that enable high-speed and low-latency communication between QPUs and the GB200 superchips.
“The NVAQC will provide the necessary infrastructure to drive the next generation of quantum-classical developments,” indicated Itamar Sivan, CEO of Quantum Machines.
Practical Applications: Health, Energy, and More
In the field of health, Isomorphic Labs, led by Google DeepMind’s CEO, Demis Hassabis, will use NVIDIA and Google Cloud infrastructure to accelerate drug discovery through AI.
In the energy sector, the Tapestry project (from X, Alphabet’s experimental division) will collaborate with NVIDIA to improve the simulation of electrical grids, helping to integrate new renewable energy sources and optimize the capacity of energy infrastructures to power large-scale data centers.
Validated Infrastructure for AI Fabrication
NVIDIA has also announced the expansion of its certification program for enterprise storage systems, ensuring that technology partners meet the performance and scalability requirements needed for the most demanding AI workloads. Companies like DDN, Dell Technologies, Hewlett Packard Enterprise, IBM, NetApp, Pure Storage, and VAST Data are already part of this initiative.
Additionally, the new NVIDIA AI Data Platform will allow for the design of infrastructure tailored for complex agent-based AI tasks, with storage and networking solutions validated by NVIDIA to facilitate large-scale enterprise deployments.
The Future of Quantum Computing and AI is Closer
The NVAQC positions itself as a fundamental pillar for the evolution of hybrid supercomputers, capable of combining the best of both quantum and classical worlds. According to NVIDIA, this infrastructure will be essential for solving complex problems in fields such as material simulation, biotechnology, logistics optimization, and advanced industrial design.
To learn more about the future of quantum computing and AI, NVIDIA has made resources and special sessions available through its official website and during the GTC conference, which runs until March 21.
Reference: Nvidia