Abstract
This paper provides a review of a new method of addressing problems in diffusion Monte Carlo: the Green’s function first-passage method (GFFP). In particular, we address three new strands of thought and their interaction with the GFFP method: the use of angle-averaging methods to reduce vector or tensor Laplace equations to scalar Laplace equations; the use of the simulation-tabulation (ST) method to dramatically expand the range of the GFFP method; and the development of last-passage diffusion methods; these drastically improve the efficiency of diffusion Monte Carlo methods. All of these claims are addressed in detail, with specific examples.
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Given, J.A., Mascagni, M., Hwang, CO. (2001). Continuous Path Brownian Trajectories for Diffusion Monte Carlo via First- and Last-Passage Distributions. In: Margenov, S., Waśniewski, J., Yalamov, P. (eds) Large-Scale Scientific Computing. LSSC 2001. Lecture Notes in Computer Science, vol 2179. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45346-6_4
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DOI: https://doi.org/10.1007/3-540-45346-6_4
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