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.

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Publication Details

Journal
SoftwareX
Published
2025-07-19
DOI
https://doi.org/10.1016/j.softx.2025.102253
Primary Topic
Quantum many-body systems
Type
article
Field-Weighted Citation Impact
0.00

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article

NeuMC — A package for neural sampling for lattice field theories

Tomasz Stebel, P. Białas, Piotr Korcyl, Dawid Zapolski
SoftwareX
Quantum many-body systems
article

NeuMC — A package for neural sampling for lattice field theories

Tomasz Stebel, P. Białas, Piotr Korcyl, Dawid Zapolski
article en

Abstract

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.

SoftwareXVol. 31
Jagiellonian University (PL)
Infrastruktura PL-Grid, Academic Computer Centre Cyfronet, AGH University of Science and Technology
Openalex Percentile: Top 67%
Quantum many-body systems
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