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2019 | OriginalPaper | Chapter

Global Minimum Depth in Edwards-Anderson Model

Authors : Iakov Karandashev, Boris Kryzhanovsky

Published in: Engineering Applications of Neural Networks

Publisher: Springer International Publishing

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Abstract

In the literature the most frequently cited data are quite contradictory, and there is no consensus on the global minimum value of 2D Edwards-Anderson (2D EA) Ising model. By means of computer simulations, with the help of exact polynomial Schraudolph-Kamenetsky algorithm, we examined the global minimum depth in 2D EA-type models. We found a dependence of the global minimum depth on the dimension of the problem N and obtained its asymptotic value in the limit N → ∞. We believe these evaluations can be further used for examining the behavior of 2D Bayesian models often used in machine learning and image processing.

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Title: Global Minimum Depth in Edwards-Anderson Model
Authors: Iakov Karandashev
Boris Kryzhanovsky
Publisher: Springer International Publishing
Book: Engineering Applications of Neural Networks
Print ISBN: 978-3-030-20256-9

Electronic ISBN: 978-3-030-20257-6

Copyright Year: 2019
DOI: https://doi.org/10.1007/978-3-030-20257-6_33

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