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DTSTART:19700308T020000
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DTSTART:19701101T020000
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BEGIN:VEVENT
DTSTAMP:20230831T095747Z
LOCATION:Wisshorn
DTSTART;TZID=Europe/Stockholm:20230628T113000
DTEND;TZID=Europe/Stockholm:20230628T120000
UID:submissions.pasc-conference.org_PASC23_sess155_msa299@linklings.com
SUMMARY:Novel Neural Network Architectures for Simulations of Quantum Fiel
 d Theories
DESCRIPTION:Minisymposium\n\nMarina Krstic Marinkovic (ETH Zurich)\n\nMach
 ine learning methods have been suggested as alternatives to the standard a
 lgorithms used for simulations of lattice field theories. In this talk, I 
 will present new neural network architectures inspired by effective field 
 theories, designed to improve the scaling of the training cost for the gen
 eration of lattice field theory configurations. We first address poor acce
 ptance rates in simulations of large lattices for scalar field theory in t
 wo dimensions and then discuss possible extensions to gauge theories in hi
 gher dimensions.\n\nDomain: Physics\n\nSession Chair: Luigi Del Debbio (Un
 iversity of Edinburgh)
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