Abstract Details
Abstracts
Author: Samuel W Freiberger
Requested Type: Poster
Submitted: 2025-03-13 16:36:42
Co-authors: C. J. Hansen, F. Ebrahimi, P. Grate, A. Kaptanoglu
Contact Info:
Columbia University
435 W. 119th St. #3C
New York, New York 10027
USA
Abstract Text:
First principles models of plasmas, including MHD or kinetic simulations, lead to high-dimensional nonlinear systems. System identification algorithms, such as dynamic mode decomposition (DMD) and sparse identification of nonlinear dynamics (SINDy), provide a potentially powerful approach to build low-dimensional reduced models of plasma systems and to understand system dynamics. Recent advances in the application of these data-driven approaches, including the development of the “trapping SINDy” algorithm [1-3], open the door to models accurate and compact enough to be applied to real-time analysis and control. This poster will present progress on applying these algorithms to a database of MHD simulations, using the NIMROD [4] code, of magneto-curvature and magnetorotational instabilities, which exhibit multiscale turbulent dynamics [5]. Results will be evaluated by comparing the dominant dynamics extracted to those of the directly simulated physical system and traditional analysis methods (eg. Fourier and POD).
[1] - Kaptanoglu, Phys. Rev. E 104, 015206 (2021)
[2] - Kaptanoglu, Phys. Rev. Fluids 6, 094401 (2021)
[3] - Peng et al., Local stability guarantees for data-driven quadratically nonlinear models. arXiv:2403.00324 (2024)
[4] - A H Glasser et al., 1999 Plasma Phys. Control. Fusion 41 A747
[5] - Ebrahimi and Pharr, The Astrophysical Journal, 936:145 (2022)
Supported by NSF award PHY-2329765.
Characterization: 6.0
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