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arXiv:1912.03278physics.comp-ph

The Ising Model with Hybrid Monte Carlo

Johann Ostmeyer, Evan Berkowitz, Thomas Luu, Marcus Petschlies, Ferenc Pittler

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Abstract

The Ising model is a simple statistical model for ferromagnetism. There are analytic solutions for low dimensions and very efficient Monte Carlo methods, such as cluster algorithms, for simulating this model in special cases. However most approaches do not generalise to arbitrary lattices and couplings. We present a formalism that allows one to apply Hybrid Monte Carlo (HMC) simulations to the Ising model, demonstrating how a system with discrete degrees of freedom can be simulated with continuous variables. Because of the flexibility of HMC, our formalism is easily generalizable to arbitrary modifications of the model, creating a route to leverage advanced algorithms such as shift preconditioners and multi-level methods, developed in conjunction with HMC.

arXiv comments
Journal reference
DOI
doi:10.1016/j.cpc.2021.107978
Subjects
physics.comp-phComputational Physics cond-mat.stat-mechStatistical Mechanics hep-latHigh Energy Physics, Lattice

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Linked by 1 identifiable commenter in 2 comments across 2 threads, from Jul 2021 to Sep 2025.

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Discussed in comments2 threads

    • If you're interested in HMC, we showed how to apply it to the Ising model in https://arxiv.org/abs/1912.03278 with code available in https://github.com/HISKP-LQCD/ising_hmc

      evanbView on HNParent context

    • Even though the Ising model is a model of discrete variables, it is still possible to apply HMC to perform global updates, as we explain in https://arxiv.org/abs/1912.03278 However, without further improvement, HMC’s performance is similar to the ‘obvious’ algorithms and poor…

      evanbView on HNParent context

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