Temperature Steerable Flows and Boltzmann Generators
Statistical Mechanics
2022-09-07 v2
Abstract
Boltzmann generators approach the sampling problem in many-body physics by combining a normalizing flow and a statistical reweighting method to generate samples in thermodynamic equilibrium. The equilibrium distribution is usually defined by an energy function and a thermodynamic state. Here we propose temperature-steerable flows (TSF) which are able to generate a family of probability densities parametrized by a choosable temperature parameter. TSFs can be embedded in generalized ensemble sampling frameworks to sample a physical system across multiple thermodynamic states.
Cite
@article{arxiv.2108.01590,
title = {Temperature Steerable Flows and Boltzmann Generators},
author = {Manuel Dibak and Leon Klein and Andreas Krämer and Frank Noé},
journal= {arXiv preprint arXiv:2108.01590},
year = {2022}
}
Comments
arXiv admin note: substantial text overlap with arXiv:2012.00429