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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Vydané v:	New journal of physics Ročník 24; číslo 4; s. 43040 - 43065
Hlavní autori:	Giataganas, Dimitrios, Huang, Ching-Yu, Lin, Feng-Li
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Bristol IOP Publishing 01.04.2022
Predmet:	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
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