Qubit-efficient quantum simulation with sequential circuits

Abstract: Simulations of strongly correlated quantum many-body physics relevant to materials science, chemistry, and fundamental physics are promising early applications of quantum computers. However, a critical practical constraint lies in the severely limited number of coherent qubits achievable with existing technology. In this talk, we present a series of sequential quantum simulation algorithms inspired by classical tensor network methods. These algorithms target various physical systems, including the ground states of interacting fermions, critical spin chains, and thermal states. Through both numerical simulation and experimental implementation on a trapped-ion quantum computer, we demonstrate that these sequential circuits accurately characterize the properties of the target physical systems while drastically saving qubit usage, highlighting the method's power and versatility. We conclude by outlining ongoing theoretical and experimental efforts.

Bio: Yuxuan Zhang, CQIQC Postdoctoral Fellow with an appointment at the University of Toronto and the Vector Institute for Artificial Intelligence, works with Yong-Baek Kim and Juan C