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arXiv · 2310.07016

Discovering the Unknowns: A First Step

V. Roshan Joseph·William E. Lewis·Henry S. Yuchi·Kathryn A. Maupin
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Abstract

This article aims at discovering the unknown variables in the system through data analysis. The main idea is to use the time of data collection as a surrogate variable and try to identify the unknown variables by modeling gradual and sudden changes in the data. We use Gaussian process modeling and a sparse representation of the sudden changes to efficiently estimate the large number of parameters in the proposed statistical model. The method is tested on a realistic dataset generated using a one-dimensional implementation of a Magnetized Liner Inertial Fusion (MagLIF) simulation model and encouraging results are obtained.

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V. Roshan Joseph, William E. Lewis, Henry S. Yuchi, Kathryn A. Maupin. 2023-10-10. Discovering the Unknowns: A First Step. https://arxiv.org/abs/2310.07016

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