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
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CiteScore 2016: 0.70
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The discrete-stochastic approaches to solving the linearized Boltzmann equation
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.