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Adaptive Thouless-Anderson-Palmer approach to inverse Ising problems with quenched random fields
Haiping Huang1, Yoshiyuki Kabashima
1Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Yokohama 226-8502, Japan.
Abstract:
The adaptive Thouless-Anderson-Palmer equation is derived for inverse Ising problems in the presence of quenched random fields. We test the proposed scheme on Sherrington-Kirkpatrick, Hopfield, and random orthogonal models and find that the adaptive Thouless-Anderson-Palmer approach allows accurate inference of quenched random fields whose distribution can be either Gaussian or bimodal. In particular, another competitive method for inferring external fields, namely, the naive mean field method with diagonal weights, is compared and discussed.
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