NeuMC : a package for neural sampling for lattice field theories

We present the NeuMC software package aimed at facilitating the research on neural samplers in lattice field theories. Neural samplers based on normalizing flows are becoming increasingly popular in the context of Monte–Carlo simulations as they can effectively approximate target probability distributions, possibly alleviating some shortcomings of the Markov chain Monte–Carlo methods such as critical slowing down. Our package provides tools to create such samplers for two-dimensional field theories and is based on a popular PyTorch package.