Multilevel Monte-Carlo front tracking for random scalar conservation laws


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2012-07

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Report

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Abstract

We consider random scalar hyperbolic conservation laws (RSCLs) in spatial dimension $d\ge 1$ with bounded random flux functions which are $\mathbb{P}$-a.s. Lipschitz continuous with respect to the state variable, for which there exists a unique random entropy solution (i.e., a measurable mapping from the probability space into $C(0,T;L^1(\mathbb{R}^d))$ with finite second moments). We present a convergence analysis of a Multi-Level Monte-Carlo Front-Tracking (MLMCFT) algorithm. Due to the first order convergence of front tracking, we obtain an improved complexity estimate in one space dimension.

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2012-17

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Seminar for Applied Mathematics, ETH Zurich

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03435 - Schwab, Christoph / Schwab, Christoph check_circle

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