A noisy Monte Carlo algorithm

L. Lin, K. F. Liu, J. Sloan

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

We propose a Monte Carlo algorithm to promote the Kennedy-Kuti linear accept-reject algorithm which accommodates unbiased stochastic estimates of the probability to an exact one. This is achieved by adopting the Metropolis accept-reject steps for both the dynamical and noise configurations. We test it on the five state model and obtain desirable results even for the case with large noise. We also discuss its application to lattice QCD with stochastically estimated fermion determinants.

Original languageEnglish
JournalPhysical Review D - Particles, Fields, Gravitation and Cosmology
Volume61
Issue number7
DOIs
StatePublished - 2000

ASJC Scopus subject areas

  • Nuclear and High Energy Physics
  • Physics and Astronomy (miscellaneous)

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