{"title":"Neural Network Gauge Field Transformation for 4D SU(3) gauge fields","authors":"Xiao-Yong Jin","doi":"arxiv-2405.19692","DOIUrl":null,"url":null,"abstract":"We construct neural networks that work for any Lie group and maintain gauge\ncovariance, enabling smooth, invertible gauge field transformations. We\nimplement these transformations for 4D SU(3) lattice gauge fields and explore\ntheir use in HMC. We focus on developing loss functions and optimizing the\ntransformations. We show the effects on HMC's molecular dynamics and discuss\nthe scalability of the approach.","PeriodicalId":501191,"journal":{"name":"arXiv - PHYS - High Energy Physics - Lattice","volume":"36 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - PHYS - High Energy Physics - Lattice","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2405.19692","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We construct neural networks that work for any Lie group and maintain gauge
covariance, enabling smooth, invertible gauge field transformations. We
implement these transformations for 4D SU(3) lattice gauge fields and explore
their use in HMC. We focus on developing loss functions and optimizing the
transformations. We show the effects on HMC's molecular dynamics and discuss
the scalability of the approach.
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