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arXiv · 2002.00607

Global Minimum Depth In Edwards-Anderson Model

Iakov Karandashev·Boris Kryzhanovsky
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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 $N\to\infty$. 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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BibTeXRIS

Iakov Karandashev, Boris Kryzhanovsky. 2020-02-03. Global Minimum Depth In Edwards-Anderson Model. https://doi.org/10.1007/978-3-030-20257-6_33

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