Quantum annealing of an ising spin-glass by Green's function Monte Carlo

Lorenzo Stella*, Giuseppe E. Santoro

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)

Abstract

We present an implementation of quantum annealing (QA) via lattice Green's function Monte Carlo (GFMC), focusing on its application to the Ising spin glass in transverse field. In particular, we study whether or not such a method is more effective than the path-integral Monte Carlo- (PIMC) based QA, as well as classical simulated annealing (CA), previously tested on the same optimization problem. We identify the issue of importance sampling, i.e., the necessity of possessing reasonably good (variational) trial wave functions, as the key point of the algorithm. We performed GFMC-QA runs using such a Boltzmann-type trial wave function, finding results for the residual energies that are qualitatively similar to those of CA (but at a much larger computational cost), and definitely worse than PIMC-QA. We conclude that, at present, without a serious effort in constructing reliable importance sampling variational wave functions for a quantum glass, GFMC-QA is not a true competitor of PIMC-QA.

Original languageEnglish
Article number036703
Number of pages6
JournalPhysical Review E
Volume75
Issue number3
DOIs
Publication statusPublished - Mar 2007

Keywords

  • GLOBAL OPTIMIZATION
  • MINIMIZATION
  • CONVERGENCE

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