Microcanonical Langevin Monte Carlo

03/31/2023

∙

by   Jakob Robnik, et al.

∙

0

∙

share

We propose a method for sampling from an arbitrary distribution exp[-S()] with an available gradient ∇ S(), formulated as an energy-preserving stochastic differential equation (SDE). We derive the Fokker-Planck equation and show that both the deterministic drift and the stochastic diffusion separately preserve the stationary distribution. This implies that the drift-diffusion discretization schemes are bias-free, in contrast to the standard Langevin dynamics. We apply the method to the ϕ^4 lattice field theory, showing the results agree with the standard sampling methods but with significantly higher efficiency compared to the current state-of-the-art samplers.