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Tensor-Train Split-Operator Fourier Transform (TT-SOFT) Method: Multidimensional Nonadiabatic Quantum Dynamics
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DOI：10.1021/acs.jctc.7b00608.png)
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Abstract
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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 S-1/S-2 interconversion dynamics of pyrazine after UV photoexcitation to the S-2 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.
Keywords:
DEPENDENT SCHRODINGER-EQUATION
ULTRAFAST INTERNAL-CONVERSION
COMPLEX MOLECULAR-SYSTEMS
THERMAL RATE CONSTANTS
CONICAL INTERSECTION
PROPAGATING WAVEPACKETS
CHEMICAL-REACTIONS
MATCHING-PURSUIT
SPECTRAL METHOD
HARTREE THEORY
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