BPS spectroscopy with reinforcement learning

IF 4.5 2区 物理与天体物理 Q1 ASTRONOMY & ASTROPHYSICS
Federico Carta , Asa Gauntlett , Finley Griffin , Yang-Hui He
{"title":"BPS spectroscopy with reinforcement learning","authors":"Federico Carta ,&nbsp;Asa Gauntlett ,&nbsp;Finley Griffin ,&nbsp;Yang-Hui He","doi":"10.1016/j.physletb.2025.139646","DOIUrl":null,"url":null,"abstract":"<div><div>We apply reinforcement learning (RL) to establish whether at a given position in the Coulomb branch of the moduli space of a 4d <span><math><mi>N</mi><mo>=</mo><mn>2</mn></math></span> quantum field theory (QFT) the BPS spectrum is finite. If it is, we furthermore determine the full BPS spectrum at such point in moduli space. We demonstrate that using a RL model one can efficiently determine the suitable sequence of quiver mutations of the BPS quiver that will generate the full BPS spectrum. We analyse the performance of the RL model on random BPS quivers and show that it converges to a solution various orders of magnitude faster than a systematic brute-force scan. As a result, we show that our algorithm can be used to identify all minimal chambers of a given <span><math><mi>N</mi><mo>=</mo><mn>2</mn></math></span> QFT, a task previously intractable with computer scanning. As an example, we recover all minimal chambers of the <span><math><mtext>SU</mtext><mo>(</mo><mn>2</mn><mo>)</mo></math></span> <span><math><msub><mrow><mi>N</mi></mrow><mrow><mi>f</mi></mrow></msub><mo>=</mo><mn>4</mn></math></span> gauge theory, and discover new minimal chambers for theories that can be realized by IIB geometric engineering.</div></div>","PeriodicalId":20162,"journal":{"name":"Physics Letters B","volume":"868 ","pages":"Article 139646"},"PeriodicalIF":4.5000,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physics Letters B","FirstCategoryId":"101","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0370269325004071","RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ASTRONOMY & ASTROPHYSICS","Score":null,"Total":0}
引用次数: 0

Abstract

We apply reinforcement learning (RL) to establish whether at a given position in the Coulomb branch of the moduli space of a 4d N=2 quantum field theory (QFT) the BPS spectrum is finite. If it is, we furthermore determine the full BPS spectrum at such point in moduli space. We demonstrate that using a RL model one can efficiently determine the suitable sequence of quiver mutations of the BPS quiver that will generate the full BPS spectrum. We analyse the performance of the RL model on random BPS quivers and show that it converges to a solution various orders of magnitude faster than a systematic brute-force scan. As a result, we show that our algorithm can be used to identify all minimal chambers of a given N=2 QFT, a task previously intractable with computer scanning. As an example, we recover all minimal chambers of the SU(2) Nf=4 gauge theory, and discover new minimal chambers for theories that can be realized by IIB geometric engineering.
BPS光谱与强化学习
我们应用强化学习(RL)来确定在4d N=2量子场论(QFT)模空间的库仑分支的给定位置上BPS谱是否有限。如果是,我们进一步确定在模空间中此点的全BPS谱。我们证明了使用RL模型可以有效地确定合适的BPS颤振突变序列,从而产生完整的BPS谱。我们分析了RL模型在随机BPS颤振上的性能,并表明它收敛到解决方案的速度比系统暴力扫描快几个数量级。结果表明,我们的算法可用于识别给定N=2 QFT的所有最小腔室,这是以前计算机扫描难以处理的任务。作为一个例子,我们恢复了SU(2) Nf=4规范理论的所有最小室,并发现了可以通过IIB几何工程实现的理论的新的最小室。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Physics Letters B
Physics Letters B 物理-物理:综合
CiteScore
9.10
自引率
6.80%
发文量
647
审稿时长
3 months
期刊介绍: Physics Letters B ensures the rapid publication of important new results in particle physics, nuclear physics and cosmology. Specialized editors are responsible for contributions in experimental nuclear physics, theoretical nuclear physics, experimental high-energy physics, theoretical high-energy physics, and astrophysics.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信