Population size bias in diffusion Monte Carlo (Articolo in rivista)

Type
Label
  • Population size bias in diffusion Monte Carlo (Articolo in rivista) (literal)
Anno
  • 2012-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1103/PhysRevE.86.056712 (literal)
Alternative label
  • Boninsegni, M; Moroni, S (2012)
    Population size bias in diffusion Monte Carlo
    in Physical review. E, Statistical, nonlinear, and soft matter physics (Print)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Boninsegni, M; Moroni, S (literal)
Pagina inizio
  • 056712 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 86 (literal)
Rivista
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Univ Alberta, Dept Phys, Edmonton, AB T6G 2G7, Canada; SISSA, I-34136 Trieste, Italy; CNR, DEMOCRITOS Natl Simulat Ctr, Ist Officina Mat, I-34136 Trieste, Italy (literal)
Titolo
  • Population size bias in diffusion Monte Carlo (literal)
Abstract
  • The size of the population of random walkers required to obtain converged estimates in DMC increases dramatically with system size. We illustrate this by comparing ground state energies of small clusters of parahydrogen (up to 48 molecules) computed by Diffusion Monte Carlo (DMC) and Path Integral Ground State (PIGS) techniques. We contend that the bias associated to a finite population of walkers is the most likely cause of quantitative numerical discrepancies between PIGS and DMC energy estimates reported in the literature, for this few-body Bose system. We discuss the viability of DMC as a general-purpose ground state technique, and argue that PIGS, and even finite temperature methods, enjoy more favorable scaling, and are therefore a superior option for systems of large size. (literal)
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