Maximum Likelihood Reconstruction for Ising Models with Asynchronous Updates

Hong-Li Zeng; Mikko Alava; Erik Aurell; John Hertz; Yasser Roudi

doi:10.1103/PhysRevLett.110.210601

Maximum Likelihood Reconstruction for Ising Models with Asynchronous Updates

Hong-Li Zeng, Mikko Alava, Erik Aurell, John Hertz, Yasser Roudi

Biokompleksitet

22 Citationer (Scopus)

Abstract

We describe how the couplings in an asynchronous kinetic Ising model can be inferred. We consider two cases: one in which we know both the spin history and the update times and one in which we know only the spin history. For the first case, we show that one can average over all possible choices of update times to obtain a learning rule that depends only on spin correlations and can also be derived from the equations of motion for the correlations. For the second case, the same rule can be derived within a further decoupling approximation. We study all methods numerically for fully asymmetric Sherrington-Kirkpatrick models, varying the data length, system size, temperature, and external field. Good convergence is observed in accordance with the theoretical expectations.

Originalsprog	Engelsk
Artikelnummer	210601
Tidsskrift	Physical Review Letters
Vol/bind	110
Udgave nummer	21
ISSN	0031-9007
DOI	https://doi.org/10.1103/PhysRevLett.110.210601
Status	Udgivet - 20 maj 2013

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10.1103/PhysRevLett.110.210601

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title = "Maximum Likelihood Reconstruction for Ising Models with Asynchronous Updates",

abstract = "We describe how the couplings in an asynchronous kinetic Ising model can be inferred. We consider two cases: one in which we know both the spin history and the update times and one in which we know only the spin history. For the first case, we show that one can average over all possible choices of update times to obtain a learning rule that depends only on spin correlations and can also be derived from the equations of motion for the correlations. For the second case, the same rule can be derived within a further decoupling approximation. We study all methods numerically for fully asymmetric Sherrington-Kirkpatrick models, varying the data length, system size, temperature, and external field. Good convergence is observed in accordance with the theoretical expectations.",

author = "Hong-Li Zeng and Mikko Alava and Erik Aurell and John Hertz and Yasser Roudi",

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AU - Zeng, Hong-Li

AU - Alava, Mikko

AU - Aurell, Erik

AU - Hertz, John

AU - Roudi, Yasser

PY - 2013/5/20

Y1 - 2013/5/20

N2 - We describe how the couplings in an asynchronous kinetic Ising model can be inferred. We consider two cases: one in which we know both the spin history and the update times and one in which we know only the spin history. For the first case, we show that one can average over all possible choices of update times to obtain a learning rule that depends only on spin correlations and can also be derived from the equations of motion for the correlations. For the second case, the same rule can be derived within a further decoupling approximation. We study all methods numerically for fully asymmetric Sherrington-Kirkpatrick models, varying the data length, system size, temperature, and external field. Good convergence is observed in accordance with the theoretical expectations.

AB - We describe how the couplings in an asynchronous kinetic Ising model can be inferred. We consider two cases: one in which we know both the spin history and the update times and one in which we know only the spin history. For the first case, we show that one can average over all possible choices of update times to obtain a learning rule that depends only on spin correlations and can also be derived from the equations of motion for the correlations. For the second case, the same rule can be derived within a further decoupling approximation. We study all methods numerically for fully asymmetric Sherrington-Kirkpatrick models, varying the data length, system size, temperature, and external field. Good convergence is observed in accordance with the theoretical expectations.

U2 - 10.1103/PhysRevLett.110.210601

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JO - Physical Review Letters

JF - Physical Review Letters

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ER -

Maximum Likelihood Reconstruction for Ising Models with Asynchronous Updates

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