Tensor network theory and quantum simulation are respectively the key classical and quantum computing methods in understanding quantum many-body physics. In this talk, we introduce a framework of the hybrid tensor network consisting of classical low-rank tensors and many-body quantum states. By leveraging the ability of tensor networks in the efficient classical representation of quantum states, we extend the power of NISQ devices to represent many-body quantum systems with a small quantum processor. With the example of hybrid tree tensor networks, we demonstrate how to use a small quantum processor to efficiently represent large quantum systems preserving certain properties. Our result provides a unified framework for the existing task-tailored schemes and could be applicable in quantum chemistry, condensed matter and quantum field theory.
Jinzhao Sun is a PhD student at University of Oxford. He obtained the Bachelor’s degree from Peking University in physics. He is interested in quantum computing, quantum simulation and quantum many-body physics.