Engineering local optimality in quantum Monte Carlo algorithms

Journal Article · Fri Aug 10 04:00:00 EDT 2007 · Journal of Computational Physics

DOI:https://doi.org/10.1016/j.jcp.2007.03.013· OSTI ID:20991617

Pollet, Lode ^[1]; Houcke, Kris Van ^[2]; Rombouts, Stefan M.A. ^[2]

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1. Theoretische Physik, ETH Zuerich, CH - 8093 Zuerich (Switzerland)
2. Vakgroep subatomaire en stralingsfysica, Proeftuinstraat 86, Universiteit Gent (Belgium)

Quantum Monte Carlo algorithms based on a world-line representation such as the worm algorithm and the directed loop algorithm are among the most powerful numerical techniques for the simulation of non-frustrated spin models and of bosonic models. Both algorithms work in the grand-canonical ensemble and can have a winding number larger than zero. However, they retain a lot of intrinsic degrees of freedom which can be used to optimize the algorithm. We let us guide by the rigorous statements on the globally optimal form of Markov chain Monte Carlo simulations in order to devise a locally optimal formulation of the worm algorithm while incorporating ideas from the directed loop algorithm. We provide numerical examples for the soft-core Bose-Hubbard model and various spin-S models.

• OSTI ID: 20991617
• Journal Information: Journal of Computational Physics, Journal Name: Journal of Computational Physics Journal Issue: 2 Vol. 225; ISSN JCTPAH; ISSN 0021-9991
• Country of Publication: United States
• Language: English

Related Subjects

71 CLASSICAL AND QUANTUM MECHANICS
GENERAL PHYSICS
ALGORITHMS
COMPUTERIZED SIMULATION
DEGREES OF FREEDOM
HUBBARD MODEL
MARKOV PROCESS
MONTE CARLO METHOD
SPIN