Self-learning quantum Monte Carlo method in interacting fermion systems

Abstract

The self-learning Monte Carlo method is a powerful general-purpose numerical method recently introduced to simulate many-body systems. In this work, we extend it to an interacting fermion quantum system in the framework of the widely used determinant quantum Monte Carlo. This method can generally reduce the computational complexity and moreover can greatly suppress the autocorrelation time near a critical point. This enables us to simulate an interacting fermion system on a $100\ifmmode\times\else\texttimes\fi{}100$ lattice even at the critical point and obtain critical exponents with high precision.