NVIDIA is urging Congress to reauthorize the National Quantum Initiative (NQI), established in 2018, to maintain US leadership in a rapidly advancing field poised to revolutionize technology and national security. Dramatic progress in qubit coherence and system scaling since the NQI’s inception has clarified a path toward practical quantum systems, but a renewed strategy is now critical. Under Secretary for Science, Dr. Darío Gil, describes the current moment as “the precipice of a scientific revolution driven by the convergence of AI, high-performance computing and quantum systems.”
The “Genesis Mission” aims to mobilize national resources to build an integrated discovery platform, doubling R&D productivity within a decade by unifying AI, accelerated computing, and quantum processors into a new class of “supercomputers.”
AI & Quantum Convergence Drives R&D Productivity
The convergence of artificial intelligence and quantum computing is poised to revolutionize scientific discovery, shifting the landscape of research and development as we know it, according to experts. Under Secretary for Science, Dr. Crucially, the most impactful quantum applications won’t arise from treating AI and quantum technologies as separate endeavors, but through their deliberate synthesis. NVIDIA has already begun building the necessary infrastructure, offering technologies like The Bridge – quantum-GPU interconnects providing “low-latency, high-throughput connections” – and the Platform, CUDA-Q, an “open source programming model” designed to democratize access to these complex systems. AI is proving vital in tackling key challenges within quantum computing itself, including “real-time tasks such as quantum error correction and hardware calibration.”
A truly scientifically useful quantum system—capable of delivering hundreds of logical qubits and millions of operations—demands a seamless unification of classical and quantum resources. This system-level integration, where GPUs, CPUs, and quantum processing units work in concert, is what elevates quantum capability beyond isolated demonstrations and transforms it into a practical scientific resource. To ensure the U.S. maintains leadership, a reauthorized National Quantum Initiative (NQI) must “explicitly recognize and support the integration of AI, accelerated computing and quantum processors.” The NQI needs to evolve from a discovery-focused program to one that also “enables integrated system-level deployment,” funding initiatives like quantum digital twins for advanced design simulation and bolstering AI infrastructure for large-scale quantum error correction.
NVIDIA NVQLink & CUDA-Q Enable Quantum-GPU Integration
The pursuit of scientifically useful quantum systems is rapidly evolving beyond isolated hardware demonstrations, demanding a cohesive integration of classical and quantum computing resources. Achieving this unification requires more than just state-of-the-art quantum processors; it necessitates a seamless interplay between GPUs, CPUs, and Quantum Processing Units (QPUs) functioning as a single, integrated capability, according to experts driving the field. NVIDIA is addressing this crucial need with technologies like NVQLink and CUDA-Q, designed to forge essential connections within this emerging quantum-GPU supercomputing landscape. Through collaborative efforts with U.S. The U.S.
Department of Energy aims “to deploy a scientifically useful quantum supercomputer in the U.S. by 2028,” a goal that hinges on evolving the National Quantum Initiative (NQI) to prioritize integrated system-level deployment.
Quantum technologies are rapidly emerging as foundational capabilities for economic competitiveness, national security and scientific leadership in the 21st century.
National Quantum Initiative: Advancing Qubit Coherence & Scaling
The pursuit of practical quantum computers demands more than just improved qubits; it requires a cohesive national strategy, and the United States is doubling down on its commitment through the National Quantum Initiative (NQI). Established in 2018, the NQI initiated a broad, multi-agency approach spanning universities, national labs, and industry, fostering sustained investment and a robust research ecosystem. Since its inception, significant strides have been made in critical areas like qubit coherence and system scaling, moving beyond isolated demonstrations toward viable architectures. This progress, according to the document, has “clarified a viable roadmap toward useful quantum systems and reinforced the value of long-term, coordinated national investment.”
A key element of this renewed push is recognizing the symbiotic relationship between artificial intelligence and quantum computing—a connection that wasn’t fully appreciated when the initial NQI strategy was formed. Under Secretary for Science, Dr. A reauthorized NQI will be crucial to propel American leadership in this rapidly evolving field.
Quantum Digital Twins & AI Support Logical Qubit Development
U.S. leadership depends on providing researchers with advanced design simulation capabilities, and Congress should fund electronic design automation innovation for simulating quantum hardware, enabling researchers to validate designs digitally before fabrication and dramatically accelerating hardware roadmaps. This push towards “Quantum Digital Twins” – virtual replicas of quantum hardware – promises to drastically shorten development cycles and optimize performance. A key challenge lies in scaling quantum systems to achieve the necessary hundreds of logical qubits and millions of operations for truly useful computation. This ambition isn’t achievable through hardware advancements alone; it fundamentally requires a unified approach leveraging AI.
Solving problems with quantum systems requires logical qubits, which in turn require techniques like quantum error correction that can only be deployed at scale with AI infrastructure. The NQI must ensure that there is adequate research and AI infrastructure funding to build large-scale systems of logical qubits. To further accelerate this synergy, the NQI should promote deeper cross-pollination between these fields by supporting the creation of quantum-simulated datasets to train the next generation of AI models and establish a powerful “AI+Quantum” hub for shared tools, data and workflows. Furthermore, establishing clear performance benchmarks is crucial.
Flagship hybrid application projects in chemistry, materials science and life sciences should be launched, creating clear performance benchmarks to demonstrate the utility of these systems for real-world problems beyond abstract experiments and accelerating open scientific use. “Scientifically useful” must be rigorously defined to ensure focused, outcome-driven investment, with organizations like the QED-C empowered to lead benchmarking initiatives, establishing transparent metrics that define true utility and enable consistent measurement of progress. Ultimately, this integrated strategy aims to temper U.S. leadership in research and AI into a durable advantage, ensuring continued dominance through and beyond the AI era.
