Solving spin glasses with optimized trees of clustered spins

Solving spin glasses with optimized trees of clustered spins We present an algorithm for the optimization and thermal equilibration of spin glasses, or more generally, cost functions of the Ising form H=∑⟨ij⟩Jijsisj+∑ihisi, defined on graphs with arbitrary connectivity. The algorithm consists of two repeated steps: (i) the optimized construction of a random tree of spin clusters on the input problem graph, and (ii) the thermal sampling of the generated tree. The randomly generated trees are constructed so as to optimize a balance between the size of the tree and the complexity required to draw Boltzmann samples from it. We benchmark the algorithm on several classes of problems and demonstrate its advantages over existing approaches. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Physical Review E American Physical Society (APS)

Solving spin glasses with optimized trees of clustered spins

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Solving spin glasses with optimized trees of clustered spins

Abstract

We present an algorithm for the optimization and thermal equilibration of spin glasses, or more generally, cost functions of the Ising form H=∑⟨ij⟩Jijsisj+∑ihisi, defined on graphs with arbitrary connectivity. The algorithm consists of two repeated steps: (i) the optimized construction of a random tree of spin clusters on the input problem graph, and (ii) the thermal sampling of the generated tree. The randomly generated trees are constructed so as to optimize a balance between the size of the tree and the complexity required to draw Boltzmann samples from it. We benchmark the algorithm on several classes of problems and demonstrate its advantages over existing approaches.
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Publisher
The American Physical Society
Copyright
Copyright © ©2017 American Physical Society
ISSN
1539-3755
eISSN
550-2376
D.O.I.
10.1103/PhysRevE.96.022105
Publisher site
See Article on Publisher Site

Abstract

We present an algorithm for the optimization and thermal equilibration of spin glasses, or more generally, cost functions of the Ising form H=∑⟨ij⟩Jijsisj+∑ihisi, defined on graphs with arbitrary connectivity. The algorithm consists of two repeated steps: (i) the optimized construction of a random tree of spin clusters on the input problem graph, and (ii) the thermal sampling of the generated tree. The randomly generated trees are constructed so as to optimize a balance between the size of the tree and the complexity required to draw Boltzmann samples from it. We benchmark the algorithm on several classes of problems and demonstrate its advantages over existing approaches.

Journal

Physical Review EAmerican Physical Society (APS)

Published: Aug 2, 2017

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