Bulletin of the American Physical Society
2023 APS March Meeting
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session K59: First-Principles Simulations of Excited-State Phenomena: Electron-phonon Interactions II
3:00 PM–5:36 PM,
Tuesday, March 7, 2023
Room: Room 301
Sponsoring
Unit:
DCOMP
Chair: Yuan Ping, University of California, Santa Cruz
Abstract: K59.00008 : Data-driven solution of the real-time Boltzmann transport equation: speeding up and finding patterns in first-principles calculations of nonequilibrium dynamics*
4:48 PM–5:00 PM
Presenter:
Ivan Maliyov
(Caltech)
Authors:
Ivan Maliyov
(Caltech)
Jia Yin
(Lawrence Berkeley National Laboratory)
Chao Yang
(Lawrence Berkeley National Laboratory)
Marco Bernardi
(Caltech)
In this talk, we present a data-driven approach based on dynamic mode decomposition (DMD) to accelerate the solution of the electronic rt-BTE. This approach enables calculations of nonequilibrium electron populations and steady-state solution in external fields with order-of-magnitude reduction in computational cost while fully preserving the accuracy. Analysis of the leading modes extracted from DMD sheds light on the dominant scattering and relaxation mechanisms. We show illustrative examples of such data-driven electron dynamics calculations and discuss their implementation in the Perturbo code. We conclude by discussing extensions for data-driven nonequilibrium phonon dynamics.
[1] I. Maliyov, J. Park, M. Bernardi, Phys. Rev. B 104, L100303 (2021)
[2] X. Tong, M. Bernardi, Phys. Rev. Research, 3 (2021)
*We acknowledge the support by the Liquid Sunlight Alliance, which is supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Award Number DE-SC0021266. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility located at Lawrence Berkeley National Laboratory, operated under Contract No. DE-AC02-05CH11231. This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research and Office of Basic Energy Sciences, Scientific Discovery through Advanced Computing (SciDAC) program under Award Number DE-SC0022088, which supported method development.
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