An efficient backward Monte Carlo estimator for solving of a quantum-kinetic equation with memory kernel

Authors:
T. V. Gurov;P. A. Whitlock
Affiliations:
Department of Computer and Information Science, Brooklyn College CUNY, 2900 Bedford Avenue, Brooklyn, NY 11210-2889, USA, Central Laboratory for Parallel Processing, Bulgarian Academy of Sciences, ...;Central Laboratory for Parallel Processing, Bulgarian Academy of Sciences, Acad. G. Bonchev St., bl. 25 A, 1113 Sofia, Bulgaria
Venue:
Mathematics and Computers in Simulation
Year:
2002

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Abstract

An efficient backward Monte Carlo (MC) estimator and a corresponding algorithm for solving a quantum-kinetic equation describing an ultrafast semiconductor carrier transport is proposed and studied. In order to obtain the electron energy distribution for long evolution times, variance reduction techniques are applied. The balancing of errors (both systematic and stochastic) and computational cost are investigated.The presented algorithm is implemented using the scalable parallel random number generator (SPRNG) and one by P. L'Ecuyer based on a combination of two linear congruential sequences.Numerical results for long and short evolution times are obtained. They show that the SPRNG is preferable to that by P. L'Ecuyer.