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Author (up) Albandea, D.; Del Debbio, L.; Hernandez, P.; Kenway, R.; Marsh Rossney, J.; Ramos, A. url  doi
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  Title Learning trivializing flows Type Journal Article
  Year 2023 Publication European Physical Journal C Abbreviated Journal Eur. Phys. J. C  
  Volume 83 Issue 7 Pages 676 - 14pp  
  Keywords  
  Abstract The recent introduction of machine learning techniques, especially normalizing flows, for the sampling of lattice gauge theories has shed some hope on improving the sampling efficiency of the traditional hybrid Monte Carlo (HMC) algorithm. In this work we study a modified HMC algorithm that draws on the seminal work on trivializing flows by L & uuml;scher. Autocorrelations are reduced by sampling from a simpler action that is related to the original action by an invertible mapping realised through Normalizing Flows models with a minimal set of training parameters. We test the algorithm in a f(4) theory in 2D where we observe reduced autocorrelation times compared with HMC, and demonstrate that the training can be done at small unphysical volumes and used in physical conditions. We also study the scaling of the algorithm towards the continuum limit under various assumptions on the network architecture.  
  Address [Albandea, D.; Hernandez, P.; Ramos, A.] Edificio Inst Invest, IFIC CSIC UVEG, Apt 22085, Valencia 46071, Spain, Email: david.albandea@uv.es  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1434-6044 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:001066712500003 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5698  
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