论文标题
晶格场理论的随机标准化流
Stochastic normalizing flows for lattice field theory
论文作者
论文摘要
随机归一化流是一类深入生成模型，它们将标准化流与蒙特卡洛更新结合在一起，可用于晶格场理论中，以从玻尔兹曼分布中进行样品。在此程序中，我们概述了这些混合算法的构建，并指出理论背景可以与Jarzynski的平等有关，Jarzynski的平等是一种非平衡统计力学定理，该定理已成功用于计算Lattice Field理论中的自由能。我们以二维$ ϕ^4 $字段理论的应用示例结束。
Stochastic normalizing flows are a class of deep generative models that combine normalizing flows with Monte Carlo updates and can be used in lattice field theory to sample from Boltzmann distributions. In this proceeding, we outline the construction of these hybrid algorithms, pointing out that the theoretical background can be related to Jarzynski's equality, a non-equilibrium statistical mechanics theorem that has been successfully used to compute free energy in lattice field theory. We conclude with examples of applications to the two-dimensional $ϕ^4$ field theory.
