Efficient, automated Monte Carlo methods for radiation transport

Authors:
Rong Kong;Martin Ambrose;Jerome Spanier
Affiliations:
Claremont Graduate University, 150 E. 10th Street, Claremont, CA 91711, United States;Claremont Graduate University, 150 E. 10th Street, Claremont, CA 91711, United States;Claremont Graduate University, 150 E. 10th Street, Claremont, CA 91711, United States and Beckman Laser Institute and Medical Clinic, University of California, 1002 Health Science Road E., Irvine, ...
Venue:
Journal of Computational Physics
Year:
2008

Citing 2
Cited 3

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Simulation and the Monte Carlo Method
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Abstract

Monte Carlo simulations provide an indispensible model for solving radiative transport problems, but their slow convergence inhibits their use as an everyday computational tool. In this paper, we present two new ideas for accelerating the convergence of Monte Carlo algorithms based upon an efficient algorithm that couples simulations of forward and adjoint transport equations. Forward random walks are first processed in stages, each using a fixed sample size, and information from stage k is used to alter the sampling and weighting procedure in stage k+1. This produces rapid geometric convergence and accounts for dramatic gains in the efficiency of the forward computation. In case still greater accuracy is required in the forward solution, information from an adjoint simulation can be added to extend the geometric learning of the forward solution. The resulting new approach should find widespread use when fast, accurate simulations of the transport equation are needed.