Finite population-size effects in projection Monte Carlo methods | Zendy

Nicolas J. Cerf | Zendy; Olivier Martin | Zendy

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Finite population-size effects in projection Monte Carlo methods

Author(s) -

Nicolas J. Cerf,

Olivier Martin

Publication year - 1995

Publication title -

physical review. e, statistical physics, plasmas, fluids, and related interdisciplinary topics

Language(s) - English

Resource type - Journals

eISSN - 1095-3787

pISSN - 1063-651X

DOI - 10.1103/physreve.51.3679

Subject(s) - monte carlo method , population , statistical physics , projection (relational algebra) , monte carlo integration , physics , limit (mathematics) , kinetic monte carlo , diffusion , monte carlo molecular modeling , mathematics , statistics , mathematical analysis , markov chain monte carlo , algorithm , quantum mechanics , demography , sociology

Projection (Green's function and difFusion) Monte Carlo techniques sample a wave function by a stochastic iterative procedure. These methods converge to a stationary distribution which is biased, i.e. di8'ers from the exact ground state wave function. This bias occurs because of the use ofpopulation control procedures. We demonstrate that these biased Monte Carlo algorithms lead to a modified effective mass which is equal to the desired mass only in the limit of an infinite population of walkers. In general, the bias for the energy scales as 1/N for a population of walkers of size N and is proportional to the expectation value of the kinetic energy. Finally, we consider various strategies to reduce this bias.info:eu-repo/semantics/publishe

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