260 research outputs found
Multi-scale control variate methods for uncertainty quantification in kinetic equations
Kinetic equations play a major rule in modeling large systems of interacting
particles. Uncertainties may be due to various reasons, like lack of knowledge
on the microscopic interaction details or incomplete informations at the
boundaries. These uncertainties, however, contribute to the curse of
dimensionality and the development of efficient numerical methods is a
challenge. In this paper we consider the construction of novel multi-scale
methods for such problems which, thanks to a control variate approach, are
capable to reduce the variance of standard Monte Carlo techniques
Wealth distribution and collective knowledge. A Boltzmann approach
We introduce and discuss a nonlinear kinetic equation of Boltzmann type which
describes the influence of knowledge in the evolution of wealth in a system of
agents which interact through the binary trades introduced in Cordier,
Pareschi, Toscani, J. Stat. Phys. 2005. The trades, which include both saving
propensity and the risks of the market, are here modified in the risk and
saving parameters, which now are assumed to depend on the personal degree of
knowledge. The numerical simulations show that the presence of knowledge has
the potential to produce a class of wealthy agents and to account for a larger
proportion of wealth inequality.Comment: 21 pages, 10 figures. arXiv admin note: text overlap with
arXiv:q-bio/0312018 by other author
Fast algorithms for computing the Boltzmann collision operator
The development of accurate and fast numerical schemes for the five fold
Boltzmann collision integral represents a challenging problem in scientific
computing. For a particular class of interactions, including the so-called hard
spheres model in dimension three, we are able to derive spectral methods that
can be evaluated through fast algorithms. These algorithms are based on a
suitable representation and approximation of the collision operator. Explicit
expressions for the errors in the schemes are given and spectral accuracy is
proved. Parallelization properties and adaptivity of the algorithms are also
discussed.Comment: 22 page
Residual equilibrium schemes for time dependent partial differential equations
Many applications involve partial differential equations which admits
nontrivial steady state solutions. The design of schemes which are able to
describe correctly these equilibrium states may be challenging for numerical
methods, in particular for high order ones. In this paper, inspired by
micro-macro decomposition methods for kinetic equations, we present a class of
schemes which are capable to preserve the steady state solution and achieve
high order accuracy for a class of time dependent partial differential
equations including nonlinear diffusion equations and kinetic equations.
Extension to systems of conservation laws with source terms are also discussed.Comment: 23 pages, 12 figure
Binary interaction algorithms for the simulation of flocking and swarming dynamics
Microscopic models of flocking and swarming takes in account large numbers of
interacting individ- uals. Numerical resolution of large flocks implies huge
computational costs. Typically for interacting individuals we have a cost
of . We tackle the problem numerically by considering approximated
binary interaction dynamics described by kinetic equations and simulating such
equations by suitable stochastic methods. This approach permits to compute
approximate solutions as functions of a small scaling parameter
at a reduced complexity of O(N) operations. Several numerical results show the
efficiency of the algorithms proposed
Fluid Solver Independent Hybrid Methods for Multiscale Kinetic equations
In some recent works [G. Dimarco, L. Pareschi, Hybrid multiscale methods I.
Hyperbolic Relaxation Problems, Comm. Math. Sci., 1, (2006), pp. 155-177], [G.
Dimarco, L. Pareschi, Hybrid multiscale methods II. Kinetic equations, SIAM
Multiscale Modeling and Simulation Vol 6., No 4,pp. 1169-1197, (2008)] we
developed a general framework for the construction of hybrid algorithms which
are able to face efficiently the multiscale nature of some hyperbolic and
kinetic problems. Here, at variance with respect to the previous methods, we
construct a method form-fitting to any type of finite volume or finite
difference scheme for the reduced equilibrium system. Thanks to the coupling of
Monte Carlo techniques for the solution of the kinetic equations with
macroscopic methods for the limiting fluid equations, we show how it is
possible to solve multiscale fluid dynamic phenomena faster with respect to
traditional deterministic/stochastic methods for the full kinetic equations. In
addition, due to the hybrid nature of the schemes, the numerical solution is
affected by less fluctuations when compared to standard Monte Carlo schemes.
Applications to the Boltzmann-BGK equation are presented to show the
performance of the new methods in comparison with classical approaches used in
the simulation of kinetic equations.Comment: 31 page
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