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Title: Tensor-Train Split-Operator Fourier Transform (TT-SOFT) Method: Multidimensional Nonadiabatic Quantum Dynamics

Abstract

We introduce the “tensor-train split-operator Fourier transform” (TT-SOFT) method for simulations of multidimensional nonadiabatic quantum dynamics. TT-SOFT is essentially the grid-based SOFT method implemented in dynamically adaptive tensor-train representations. In the same spirit of all matrix product states, the tensor-train format enables the representation, propagation, and computation of observables of multidimensional wave functions in terms of the grid-based wavepacket tensor components, bypassing the need of actually computing the wave function in its full-rank tensor product grid space. We demonstrate the accuracy and efficiency of the TT-SOFT method as applied to propagation of 24-dimensional wave packets, describing the S1/S2 interconversion dynamics of pyrazine after UV photoexcitation to the S2 state. Our results show that the TT-SOFT method is a powerful computational approach for simulations of quantum dynamics of polyatomic systems since it avoids the exponential scaling problem of full-rank grid-based representations.

Authors:
 [1]; ORCiD logo [1]
  1. Department of Chemistry, Yale University, P.O. Box 208107, New Haven, Connecticut 06520-8107, United States; Energy Sciences Institute, Yale University, P.O. Box 27394, West Haven, Connecticut 06516-7394, United States
Publication Date:
Research Org.:
Lawrence Berkeley National Laboratory-National Energy Research Scientific Computing Center
Sponsoring Org.:
USDOE; National Science Foundation (NSF)
OSTI Identifier:
1480241
Resource Type:
Journal Article
Journal Name:
Journal of Chemical Theory and Computation
Additional Journal Information:
Journal Volume: 13; Journal Issue: 9; Journal ID: ISSN 1549-9618
Country of Publication:
United States
Language:
English

Citation Formats

Greene, Samuel M., and Batista, Victor S. Tensor-Train Split-Operator Fourier Transform (TT-SOFT) Method: Multidimensional Nonadiabatic Quantum Dynamics. United States: N. p., 2017. Web. doi:10.1021/acs.jctc.7b00608.
Greene, Samuel M., & Batista, Victor S. Tensor-Train Split-Operator Fourier Transform (TT-SOFT) Method: Multidimensional Nonadiabatic Quantum Dynamics. United States. doi:10.1021/acs.jctc.7b00608.
Greene, Samuel M., and Batista, Victor S. Fri . "Tensor-Train Split-Operator Fourier Transform (TT-SOFT) Method: Multidimensional Nonadiabatic Quantum Dynamics". United States. doi:10.1021/acs.jctc.7b00608.
@article{osti_1480241,
title = {Tensor-Train Split-Operator Fourier Transform (TT-SOFT) Method: Multidimensional Nonadiabatic Quantum Dynamics},
author = {Greene, Samuel M. and Batista, Victor S.},
abstractNote = {We introduce the “tensor-train split-operator Fourier transform” (TT-SOFT) method for simulations of multidimensional nonadiabatic quantum dynamics. TT-SOFT is essentially the grid-based SOFT method implemented in dynamically adaptive tensor-train representations. In the same spirit of all matrix product states, the tensor-train format enables the representation, propagation, and computation of observables of multidimensional wave functions in terms of the grid-based wavepacket tensor components, bypassing the need of actually computing the wave function in its full-rank tensor product grid space. We demonstrate the accuracy and efficiency of the TT-SOFT method as applied to propagation of 24-dimensional wave packets, describing the S1/S2 interconversion dynamics of pyrazine after UV photoexcitation to the S2 state. Our results show that the TT-SOFT method is a powerful computational approach for simulations of quantum dynamics of polyatomic systems since it avoids the exponential scaling problem of full-rank grid-based representations.},
doi = {10.1021/acs.jctc.7b00608},
journal = {Journal of Chemical Theory and Computation},
issn = {1549-9618},
number = 9,
volume = 13,
place = {United States},
year = {2017},
month = {8}
}