Neural network flows of low q-state Potts and clock models

It is known that a trained restricted Boltzmann machine (RBM) on the binary Monte Carlo Ising spin configurations, generates a series of iterative reconstructed spin configurations which spontaneously flow and stabilize to the critical point of physical system. Here we construct a variety of neural...

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Veröffentlicht in:	New journal of physics Jg. 24; H. 4; S. 43040 - 43065
Hauptverfasser:	Giataganas, Dimitrios, Huang, Ching-Yu, Lin, Feng-Li
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Bristol IOP Publishing 01.04.2022
Schlagworte:	autoencoders Configurations Critical point Ising model Iterative methods neural network Neural networks Physics q-state Potts model restricted Boltzmann machine state Potts model
ISSN:	1367-2630, 1367-2630
Online-Zugang:	Volltext
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