Optimization of population annealing Monte Carlo for large-scale spin-glass simulations

Abstract

Population annealing Monte Carlo is an efficient sequential algorithm for simulating k-local Boolean Hamiltonians. Because of its structure, the algorithm is inherently parallel and therefore well suited for large-scale simulations of computationally hard problems. Here we present various ways of optimizing population annealing Monte Carlo using 2-local spin-glass Hamiltonians as a case study. We demonstrate how the algorithm can be optimized from an implementation, algorithmic accelerator, as well as scalable parallelization points of view. This makes population annealing Monte Carlo perfectly suited to study other frustrated problems such as pyrochlore lattices, constraint-satisfaction problems, as well as higher-order Hamiltonians commonly found in, e.g., topological color codes.

14 pages, 11 figures, 1 table. See also arXiv:1711.02146 by Amey and Machta

References in corpus (6)

• Universality in three-dimensional Ising spin glasses: A Monte Carlo study
• Comparing Monte Carlo methods for finding ground states of Ising spin glasses: population annealing, simulated annealing and parallel tempering
• Temperature and Disorder Chaos in Three-Dimensional Ising Spin Glasses
• Universality-class dependence of energy distributions in spin glasses
• Evidence against a mean field description of short-range spin glasses revealed through thermal boundary conditions
• Analysis and Optimization of Population Annealing

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