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Asymptotic-Preserving Monte Carlo Methods for Transport Equations in the Diffusive Limit
Author(s) -
Giacomo Dimarco,
Lorenzo Pareschi,
Giovanni Samaey
Publication year - 2018
Publication title -
siam journal on scientific computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.674
H-Index - 147
eISSN - 1095-7197
pISSN - 1064-8275
DOI - 10.1137/17m1140741
Subject(s) - monte carlo method , scaling , mathematics , discretization , statistical physics , limit (mathematics) , diffusion equation , monte carlo molecular modeling , dynamic monte carlo method , mathematical optimization , mathematical analysis , physics , markov chain monte carlo , geometry , statistics , economy , economics , service (business)
We develop a new Monte Carlo method that solves hyperbolic transport equations with stiff terms, characterized by a (small) scaling parameter. In particular, we focus on systems which lead to a reduced problem of parabolic type in the limit when the scaling parameter tends to zero. Classical Monte Carlo methods suffer severe time step limitations in these situations, due to the fact that the characteristic speeds go to infinity in the diffusion limit. This makes the problem a real challenge, since the scaling parameter may differ by several orders of magnitude in the domain. To circumvent these time step limitations, we construct a new, asymptotic-preserving Monte Carlo method that is stable independently of the scaling parameter and degenerates to a standard probabilistic approach for solving the limiting equation in the diffusion limit. The method uses an implicit time discretization to formulate a modified equation in which the characteristic speeds do not grow indefinitely when the scaling factor tend...

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