Uncertainty Quantification for Atomistic Reaction Models: An Equation-Free Stochastic Simulation Algorithm Example

DOI10.1137/060671887zbMath1154.65003arXivmath/0610444OpenAlexW2051825507MaRDI QIDQ3545645

Ioannis G. Kevrekidis, Yu Zou

Publication date: 11 December 2008

Published in: Multiscale Modeling & Simulation (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/math/0610444

zbMATH Keywords

numerical examplesmultiscalerandom dynamical systemuncertainty quantificationcatalytic reactionequation-freestochastic Galerkin methodgeneralized polynomial chaoscoarse fixed point computationCoarse projective integrationstochastic Gillespie algorithm

Mathematics Subject Classification ID

Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Ordinary differential equations and systems with randomness (34F05) Generation, random and stochastic difference and differential equations (37H10) Numerical solutions to stochastic differential and integral equations (65C30) Finite element, Rayleigh-Ritz, Galerkin and collocation methods for ordinary differential equations (65L60)

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Quantifying Sampling Noise and Parametric Uncertainty in Atomistic-to-Continuum Simulations Using Surrogate Models ⋮ A numerical method for the approximation of stable and unstable manifolds of microscopic simulators

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