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Monte Carlo Methods and Applications

Managing Editor: Sabelfeld, Karl K.

Editorial Board: Binder, Kurt / Bouleau, Nicolas / Chorin, Alexandre J. / Dimov, Ivan / Dubus, Alain / Egorov, Alexander D. / Ermakov, Sergei M. / Halton, John H. / Heinrich, Stefan / Kalos, Malvin H. / Lepingle, D. / Makarov, Roman / Mascagni, Michael / Mathe, Peter / Niederreiter, Harald / Platen, Eckhard / Sawford, Brian R. / Schmid, Wolfgang Ch. / Schoenmakers, John / Simonov, Nikolai A. / Sobol, Ilya M. / Spanier, Jerry / Talay, Denis

4 Issues per year


CiteScore 2016: 0.70

SCImago Journal Rank (SJR) 2016: 0.647
Source Normalized Impact per Paper (SNIP) 2016: 0.908

Mathematical Citation Quotient (MCQ) 2016: 0.33

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1569-3961
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Volume 11, Issue 4

Issues

The discrete-stochastic approaches to solving the linearized Boltzmann equation

Mikhail Plotnikov
  • Institute of Thermophysics Russian Acad. Sci., prosp. Lavrentieva 1, 630090 Novosibirsk, Russia; e-mail:
  • Other articles by this author:
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/ Elena Shkarupa
  • Institute of Computational Mathematics and Mathematical Geophysics Russian Acad. Sci., prosp. Lavrentieva 6, 630090 Novosibirsk, Russia; e-mail:
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar

The test particle Monte Carlo method for solving the linearized Boltzmann equation is considered. The main idea of this work is the construction of the relations between the sample size and the number of grid nodes which guarantee the attainment of the given error level on the base of the theory of discrete-stochastic numerical methods. Three approaches to construction of the upper error bound of the method are suggested. The optimal (in the sense of the obtained upper error bounds) relations between the sample size and the number of grid nodes are constructed.

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Published in Print: 2005-12-01


Citation Information: Monte Carlo Methods and Applications mcma, Volume 11, Issue 4, Pages 447–462, ISSN (Online) 1569-3961, ISSN (Print) 0929-9629, DOI: https://doi.org/10.1515/156939605777438532.

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