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Last-passage Monte Carlo algorithm for mutual capacitance. | LitMetric

Last-passage Monte Carlo algorithm for mutual capacitance.

Phys Rev E Stat Nonlin Soft Matter Phys

Computer-Aided Molecular Design Research Center, Soongsil University, Seoul 156-743, South Korea.

Published: August 2006

AI Article Synopsis

  • Developed and tested the last-passage diffusion algorithm, a charge-based Monte Carlo method aimed at calculating mutual capacitance in conductor systems.
  • The last-passage algorithm is a time-reversal adaptation of the first-passage algorithm, which excels in efficiency by incorporating charge-based importance sampling but struggles with mutual capacitance scenarios.
  • Validation of the algorithm is achieved by calculating the mutual capacitance matrix for a circular-disk parallel-plate capacitor, showing strong agreement with established numerical results.

Article Abstract

We develop and test the last-passage diffusion algorithm, a charge-based Monte Carlo algorithm, for the mutual capacitance of a system of conductors. The first-passage algorithm is highly efficient because it is charge based and incorporates importance sampling; it averages over the properties of Brownian paths that initiate outside the conductor and terminate on its surface. However, this algorithm does not seem to generalize to mutual capacitance problems. The last-passage algorithm, in a sense, is the time reversal of the first-passage algorithm; it involves averages over particles that initiate on an absorbing surface, leave that surface, and diffuse away to infinity. To validate this algorithm, we calculate the mutual capacitance matrix of the circular-disk parallel-plate capacitor and compare with the known numerical results. Good agreement is obtained.

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Source
http://dx.doi.org/10.1103/PhysRevE.74.027701DOI Listing

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