Maximum Likelihood Reconstruction for Ising Models with Asynchronous Updates
School of Science | A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Physical Review Letters, Volume 110, Issue 21
AbstractWe 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.
Ising models, asynchronous updates, spin correlations, herrington-Kirkpatrick models
Zeng, Hong-Li & Alava, Mikko J. & Aurell, Erik & Hertz, John & Roudi, Yasser. 2013. Maximum Likelihood Reconstruction for Ising Models with Asynchronous Updates. Physical Review Letters. Volume 110, Issue 21. 210601/1-5. ISSN 0031-9007 (printed). DOI: 10.1103/physrevlett.110.210601.