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NeuMC – 用于晶格场理论的神经采样包

NeuMC – a package for neural sampling for lattice field theories

Piotr Bialas, Piotr Korcyl, Tomasz Stebel, Dawid Zapolski

arXiv
2025年3月14日

我们介绍了基于 的软件包,旨在促进格子场理论中神经采样器的研究。 基于正常化流动的神经采样器在蒙特卡洛模拟的背景下越来越受欢迎,因为它们可以有效地近似目标概率分布,可能减轻马尔可夫链蒙特卡洛方法的一些缺点。 我们的软件包提供了为二维场理论创建此类采样器的工具。

We present the software package, based on , 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. Our package provides tools to create such samplers for two-dimensional field theories.