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Title: Efficient construction of generalized master equation memory kernels for multi-state systems from nonadiabatic quantum-classical dynamics

Abstract

Techniques derived from the generalized quantum master equation (GQME) framework have provided the basis for elucidating energy and charge transfer in systems ranging from molecular solids to photosynthetic complexes. Recently, the nonperturbative combination of the GQME with quantum-classical methods has resulted in approaches whose accuracy and efficiency exceed those of the original quantumclassical schemes while offering significant accuracy improvements over perturbative expansions of the GQME. In this work, we show that, while the non-Markovian memory kernel required to propagate the GQME scales quartically with the number of subsystem states, the number of trajectories required scales at most quadratically when using quantum-classical methods to construct the kernel. We then present an algorithm that allows further acceleration of the quantum-classical GQME by offering a way to selectively sample the kernel matrix elements that are most important to the process of interest. We demonstrate the utility of these advances by applying the combination of Ehrenfest mean field theory with the GQME (MF-GQME) to models of the Fenna-Matthews-Olson (FMO) complex and the light harvesting complex II (LHCII), with 7 and 14 states, respectively. This allows us to show that the MF-GQME is able to accurately capture all the relevant dynamical time scales in LHCII:more » the initial nonequilibrium population transfer on the femtosecond time scale, the steady state-type trapping on the picosecond time scale, and the long time population relaxation. Remarkably, all of these physical effects spanning tens of picoseconds can be encoded in a memory kernel that decays only after ~65 fs.« less

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3]; ORCiD logo [2]
+ Show Author Affiliations
  1. Stanford Univ., CA (United States); Chatham University, Pittsburgh, PA (United States)
  2. Stanford Univ., CA (United States)
  3. Dalhousie Univ., Halifax, NS (Canada)
Publication Date:
Research Org.:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Univ. of California, Oakland, CA (United States); Univ. of California, Merced, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
OSTI Identifier:
1577593
Alternate Identifier(s):
OSTI ID: 1529414
Grant/Contract Number:  
AC02-05CH11231; SC0014437
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Chemical Physics
Additional Journal Information:
Journal Volume: 150; Journal Issue: 24; Journal ID: ISSN 0021-9606
Publisher:
American Institute of Physics (AIP)
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; Quantum chemical dynamics; Mean field theory; Light harvesting complexes; Non-adiabatic molecular dynamics; Energy transfer

Citation Formats

Pfalzgraff, William C., Montoya-Castillo, Andrés, Kelly, Aaron, and Markland, Thomas E. Efficient construction of generalized master equation memory kernels for multi-state systems from nonadiabatic quantum-classical dynamics. United States: N. p., 2019. Web. doi:10.1063/1.5095715.
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Pfalzgraff, William C., Montoya-Castillo, Andrés, Kelly, Aaron, & Markland, Thomas E. Efficient construction of generalized master equation memory kernels for multi-state systems from nonadiabatic quantum-classical dynamics. United States. https://doi.org/10.1063/1.5095715
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Pfalzgraff, William C., Montoya-Castillo, Andrés, Kelly, Aaron, and Markland, Thomas E. Tue . "Efficient construction of generalized master equation memory kernels for multi-state systems from nonadiabatic quantum-classical dynamics". United States. https://doi.org/10.1063/1.5095715. https://www.osti.gov/servlets/purl/1577593.
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@article{osti_1577593,
title = {Efficient construction of generalized master equation memory kernels for multi-state systems from nonadiabatic quantum-classical dynamics},
author = {Pfalzgraff, William C. and Montoya-Castillo, Andrés and Kelly, Aaron and Markland, Thomas E.},
abstractNote = {Techniques derived from the generalized quantum master equation (GQME) framework have provided the basis for elucidating energy and charge transfer in systems ranging from molecular solids to photosynthetic complexes. Recently, the nonperturbative combination of the GQME with quantum-classical methods has resulted in approaches whose accuracy and efficiency exceed those of the original quantumclassical schemes while offering significant accuracy improvements over perturbative expansions of the GQME. In this work, we show that, while the non-Markovian memory kernel required to propagate the GQME scales quartically with the number of subsystem states, the number of trajectories required scales at most quadratically when using quantum-classical methods to construct the kernel. We then present an algorithm that allows further acceleration of the quantum-classical GQME by offering a way to selectively sample the kernel matrix elements that are most important to the process of interest. We demonstrate the utility of these advances by applying the combination of Ehrenfest mean field theory with the GQME (MF-GQME) to models of the Fenna-Matthews-Olson (FMO) complex and the light harvesting complex II (LHCII), with 7 and 14 states, respectively. This allows us to show that the MF-GQME is able to accurately capture all the relevant dynamical time scales in LHCII: the initial nonequilibrium population transfer on the femtosecond time scale, the steady state-type trapping on the picosecond time scale, and the long time population relaxation. Remarkably, all of these physical effects spanning tens of picoseconds can be encoded in a memory kernel that decays only after ~65 fs.},
doi = {10.1063/1.5095715},
journal = {Journal of Chemical Physics},
number = 24,
volume = 150,
place = {United States},
year = {Tue Jun 25 00:00:00 EDT 2019},
month = {Tue Jun 25 00:00:00 EDT 2019}
}
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Journal Article:
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https://doi.org/10.1063/1.5095715
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Cited by: 28 works
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Figures / Tables:

FIG. 1 FIG. 1: Overview of an iterative approach to identifying and selectively converging the memory kernel given an initial state or states of interest.
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    Special topic on dynamics of open quantum systems
    journal, January 2020

    • Berkelbach, Timothy C.; Thoss, Michael
    • The Journal of Chemical Physics, Vol. 152, Issue 2
    • DOI: 10.1063/1.5142731
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