Estimating the Density of States of Frustrated Spin Systems

Lev Yu Barash, Jeffrey Marshall, Martin Weigel, Itay Hen

Research output: Contribution to journalArticle

2 Citations (Scopus)
18 Downloads (Pure)

Abstract

Estimating the density of states (DOS) of systems with rugged free energy landscapes is a notoriously difficult task of the utmost importance in many areas of physics ranging from spin glasses to biopolymers. DOS estimation has also recently become an indispensable tool for the benchmarking of quantum annealers when these function as samplers. Some of the standard approaches suffer from a spurious convergence of the estimates to metastable minima, and these cases are particularly hard to detect. Here, we introduce a sampling technique based on population annealing enhanced with a multi-histogram analysis and report on its performance for spin glasses. We demonstrate its ability to overcome the pitfalls of other entropic samplers, resulting in some cases in large scaling advantages that can lead to the uncovering of new physics. The new technique avoids some inherent difficulties in established approaches and can be applied to a wide range of systems without relevant tailoring requirements. Benchmarking of the studied techniques is facilitated by the introduction of several schemes that allow us to achieve exact counts of the degeneracies of the tested instances.

Original languageEnglish
Article number073065
Number of pages20
JournalNew Journal of Physics
Volume21
Issue number7
DOIs
Publication statusPublished - 30 Jul 2019

Bibliographical note

CC-BY Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

Keywords

  • Density of states
  • Entropic sampling methods
  • Phase transitions
  • Quantum computation
  • Spin glasses
  • Statistical mechanics

ASJC Scopus subject areas

  • Physics and Astronomy(all)

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