NVIDIA's approach to quantum computing is rooted in enabling researchers and developers across the quantum ecosystem to push the boundaries of what is possible, from advancing simulation capabilities to connecting quantum processors with GPU supercomputers into unified hybrid systems. Central to this vision is the concept of accelerated quantum supercomputing: the tight coupling of supercomputing and quantum computing into a single, coherent architecture for scientific discovery. This session introduces the NVIDIA quantum software stack, with a focus on two key components. cuQuantum is a set of GPU-accelerated libraries for quantum simulation, both as a drop-in backend for common quantum frameworks, and as high-performance primitives for researchers building their own simulation tools. CUDA-Q is an open platform for hybrid quantum-classical programming, offering a unified model where the same code can target CPU simulators, GPU simulators, and quantum hardware from multiple providers. We will discuss when to use each, how they complement one another, and how they fit into the broader vision of accelerated quantum supercomputing. The session includes demonstrations of real-world applications that have leveraged these tools at scale and concludes with resources for researchers to begin integrating GPU-accelerated quantum computing into their own workflows.
