Journal Article/Contribution to a conference proceedings

FZJ-2023-05418

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png From Theory to Practice: Applying Neural Networks to Simulate Real Systems with Sign Problems

Rodekamp, M. (Corresponding author)FZJ* ; Berkowitz, E.FZJ* ; Dincă, M. ; Gäntgen, C.FZJ* ; Krieg, S.FZJ* ; Luu, T.FZJ*

2023
SISSA Trieste

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Please use a persistent id in citations: doi:10.34734/FZJ-2023-05418

Abstract: The numerical sign problem poses a seemingly insurmountable barrier to the simulation of many fascinating systems. We apply neural networks to deform the region of integration, mitigating the sign problem of systems with strongly correlated electrons. In this talk we present our latest architectural developments as applied to contour deformation. We also demonstrate its applicability to real systems, namely perylene.

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Contributing Institute(s):

1. Theorie der Starken Wechselwirkung (IAS-4)
2. Institut 3 (Theoretische Kernphysik) (IKP-3)
3. Jülich Supercomputing Center (JSC)
4. Center for Advanced Simulation and Analytics (CASA)

Research Program(s):

1. 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511) (POF4-511)

Appears in the scientific report 2023

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Database coverage:
; ; ; ; DOAJ Seal

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