Quantum Monte Carlo method using a stochastic Poisson solver.

Phys Rev E Stat Nonlin Soft Matter Phys

University of Illinois at Urbana-Champaign, 1110 W. Green Street, Urbana, Illinois 61801, USA.

Published: April 2006

The quantum Monte Carlo (QMC) technique is an extremely powerful method to treat many-body systems. Usually the quantum Monte Carlo method has been applied in cases where the interaction potential has a simple analytic form, like the 1/r Coulomb potential. However, in a complicated environment as in a semiconductor heterostructure, the evaluation of the interaction itself becomes a nontrivial problem. Obtaining the potential from any grid-based finite-difference method for every walker and every step is infeasible. We demonstrate an alternative approach of solving the Poisson equation by a classical Monte Carlo calculation within the overall quantum Monte Carlo scheme. We have developed a modified "walk on spheres" algorithm using Green's function techniques, which can efficiently account for the interaction energy of walker configurations, typical of quantum Monte Carlo algorithms. This stochastically obtained potential can be easily incorporated with variational, diffusion, and other Monte Carlo techniques. We demonstrate the validity of this method by studying a simple problem, the polarization of a helium atom in the electric field of an infinite capacitor.

Download full-text PDF

Source
http://dx.doi.org/10.1103/PhysRevE.73.046702DOI Listing

Publication Analysis

Top Keywords

monte carlo
28
quantum monte
20
carlo method
8
carlo
7
monte
6
quantum
5
method
5
method stochastic
4
stochastic poisson
4
poisson solver
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!