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An unsupervised machine-learning checkpoint-restart algorithm using Gaussian mixtures for particle-in-cell simulations

By G. Chen and others
We propose an unsupervised machine-learning checkpoint-restart (CR) algorithm for particle-in-cell (PIC) algorithms using Gaussian mixtures (GM). The algorithm features a particle compression stage and a particle reconstruction stage, where a continuum particle distribution function (PDF) is constructed and resampled, respectively. To guarantee fidelity of the CR process, we ensure the... Show more
July 23, 2020
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An unsupervised machine-learning checkpoint-restart algorithm using Gaussian mixtures for particle-in-cell simulations
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