Multi-level Monte Carlo Finite Difference Methods for Fractional Conservation Laws with Random Data
Abstract
We establish a notion of random entropy solution for degenerate fractional conservation laws incorporating randomness in the initial data, convective flux and diffusive flux. In order to quantify the solution uncertainty, we design a multi-level Monte Carlo Finite Difference Method (MLMC-FDM) to approximate the ensemble average of the random entropy solutions. Furthermore, we analyze the convergence rates for MLMC-FDM and compare it with the convergence rates for the deterministic case. Additionally, we formulate error vs. work estimates for the multi-level estimator. Finally, we present several numerical experiments to demonstrate the efficiency of these schemes and validate the theoretical estimates obtained in this work.
Cite
@article{arxiv.2010.00537,
title = {Multi-level Monte Carlo Finite Difference Methods for Fractional Conservation Laws with Random Data},
author = {Ujjwal Koley and Deep Ray and Tanmay Sarkar},
journal= {arXiv preprint arXiv:2010.00537},
year = {2020}
}
Comments
To be published in SIAM/ASA Journal on Uncertainty Quantification