Bulletin of the American Physical Society
APS March Meeting 2023
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session A01: Predicting Nonlinear and Complex Systems with Machine Learning
8:00 AM–10:48 AM,
Monday, March 6, 2023
Room: Room 124
Sponsoring
Units:
GSNP DSOFT
Chair: Yuhai Tu, IBM T. J. Watson Research Center
Abstract: A01.00010 : Decomposing Long-Time Behavior of Dynamical Systems through Linear Regression*
9:48 AM–10:00 AM
Presenter:
Sam Quinn
(Georgia Institute of Technology)
Authors:
Sam Quinn
(Georgia Institute of Technology)
Joshua L. Pughe-Sanford
(Georgia Institute of Technology)
Roman O Grigoriev
(Georgia Tech)
Periodic Orbit Theory (POT) provides exact expressions for the same predictions but requires careful theoretical analysis and computational effort specific to the system under consideration. Worse, it suffers from truncation error when only finitely many periodic orbits are known. We compare the performance of our method against leading alternatives in the Lorenz system. When tuned properly, our scheme is more precise than POT and other schemes when provided with the same trajectories as input.
*This work was supported in part by the Letson Summer Internship Award.
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