Quantum accelerated supercomputing for energy materials simulations

Despite recent progress, current Quantum Processing Units (QPUs) remain limited in size and computational capabilities due to noise and scaling challenges, which impedes progress in algorithmic research. To address this challenge, circuit simulation techniques are meeting the critical need to advance research boundaries. An open-source platform for seamlessly integrating and programming QPUs, GPUs, and CPUs within a single system is provided by NVIDIA's CUDA-Q.



In this talk, we discuss NVIDIA’s hybrid quantum classical framework, CUDA-Q, and demonstrate how CUDA-Q can be utilized to accelerate and scale up quantum circuit simulations. Specifically, we develop a hybrid application for energy materials. We employ CUDA-Q to simulate energy materials at a scale, aiming to deepen our understanding of their structure-property relationships and improve their design. We showcase the largest numerical study to date, seamlessly integrating quantum-classical computing, which can be easily scaled to larger system sizes as quantum hardware matures