机器学习用于格点QCD
Machine learning for lattice QCD
Gurtej Kanwar, Scott Lawrence, Alessandro Nada, Phiala Shanahan
AI 速读 基于摘要
综述截至2025年底已确立的、在不引入不可控近似前提下用机器学习优化格点场论计算的方法。
hep-lat · cs.LG
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Machine learning (ML) methods have been explored as a means of optimizing lattice field theory calculations, with increasing interest in recent years. This chapter gives an introduction and summary to the use of ML methods to optimize lattice field theory without introducing any uncontrolled approximations. We focus on those directions which are clearly established as of late 2025, marking the 50th anniversary of the beginning of the study of lattice gauge theory. This chapter is a contribution to the online book ``Lattice QCD at 50 years,'' (LQCD@50), edited by Tanmoy Bhattacharya, Maarten Golterman, Rajan Gupta, Laurent Lellouch, and Steve Sharpe.