Variational autoencoder reconstruction of complex many-body physics

Given the notably increasing complexity of mathematical models to study realistic systems and their coupling to their environment that constrains their dynamics, both analytical approaches and numerical methods that build on these models, show limitations in scope or applicability. On the other hand...

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Veröffentlicht in:	arXiv.org
Hauptverfasser:	Luchnikov, I, Ryzhov, A, Stas, P -J C, Filippov, S N, Ouerdane, H
Format:	Paper
Sprache:	Englisch
Veröffentlicht:	Ithaca Cornell University Library, arXiv.org 09.10.2019
Schlagworte:	Complex systems Complexity Computer simulation Ising model Machine learning Mathematical models Neural networks Numerical methods Phase transitions Quantum mechanics Reconstruction Statistical analysis
ISSN:	2331-8422
Online-Zugang:	Volltext
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