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A Fast Stratified Sampling Simulation of Coagulation Processes

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  • Sabelfeld K.

    (1. Weierstrass Institute for Applied Analysis and Stochastics, Mohrenstraße 39, D–10117 Berlin, and Institute of Computational Mathematics and Mathem. Geophysics, Russian Acad. Sci., Lavrentieva str., 6, 630090 Novosibirsk, Germany/Russia.)

  • Levykin A.

    (2. Institute of Computational Mathematics and Mathem. Geophysics, Russian Acad. Sci., Lavrentieva str., 6, 630090 Novosibirsk, Russia.)

  • Privalova T.

    (3. Institute of Computational Mathematics and Mathem. Geophysics, Russian Acad. Sci., Lavrentieva str., 6, 630090 Novosibirsk, Russia.)

Abstract

We develop a new version of the direct simulation Monte Carlo method for coagulation processes governed by homogeneous Smoluchowsky equations. The method is based on a subdivision of the set of particle pairs into classes, and on an efficient algorithm for sampling from a discrete distribution, the so-called Walker's alias method. The efficiency of the new method is drastically increased compared to the conventional methods, especially when the coagulation kernel is strongly varying. The method is applied to solving a problem of islands formation on a surface due to a diffusion controlled coagulation

Suggested Citation

  • Sabelfeld K. & Levykin A. & Privalova T., 2007. "A Fast Stratified Sampling Simulation of Coagulation Processes," Monte Carlo Methods and Applications, De Gruyter, vol. 13(1), pages 71-88, April.
    • Handle: RePEc:bpj:mcmeap:v:13:y:2007:i:1:p:71-88:n:4
    DOI: 10.1515/MCMA.2007.004
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    References listed on IDEAS

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    1. Sabelfeld K.K. & Rogasinsky S.V. & Kolodko A.A. & Levykin A.I., 1996. "Stochastic algorithms for solving Smolouchovsky coagulation equation and applications to aerosol growth simulation," Monte Carlo Methods and Applications, De Gruyter, vol. 2(1), pages 41-88, December.
    2. Sabelfeld, Karl & Kolodko, Anastasia, 2003. "Stochastic Lagrangian models and algorithms for spatially inhomogeneous Smoluchowski equation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 61(2), pages 115-137.
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