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Applied Math Seminar
Multiscale Markov Chain Simulation for Particulate Processes
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This talk outlines accelerated methods for forward-time simulations of continuous-time Markov Chains arising from models of particulate processes. The problem of interest is the formation of rain-droplets from condensation nuclei, and determination of the final chemical composition. This simulation is challenging because of the large problem size (10^9 particles or more), the high dimensionality (5-10 variables per particle) and the continuum of active scales that prevents the direct application of scale-separated methods. We present a numerical scheme based on multi-scale accept-reject and clustered-particle dynamics that achieves significant acceleration of the simulation. |