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The Journal of Chemical Physics

Quantum dynamics in multistate harmonic models using tensor-train thermofield dynamics and semiclassical mapping dynamics

Hao Zeng, Xiang Sun

Published Jul 10, 2025• 6 citations
Publisher

Abstract

We present quantum dynamics of the multi-state harmonic (MSH) model using numerically exact tensor-train (TT)-based calculations. The MSH model provides a general framework for mapping a realistic system onto an effective model Hamiltonian, which is defined in extended spatial dimensions, ensuring consistent reorganization energies between all state pairs. Its analytic structure allows efficient propagation of wavepackets via a rank-adaptive TT-KSL scheme and rigorous finite-temperature dynamics via TT-thermofield dynamics. These exact results are used to benchmark various approximate semiclassical and mixed quantum-classical dynamics, including the linearized semiclassical (LSC), symmetrical quasiclassical, classical mapping models (CMMs), mean-field Ehrenfest, and fewest-switches surface hopping dynamics. We systematically explore the parameter space of the MSH model by changing electronic coupling, reorganization energy, reaction free energy, and the nuclear characteristic frequency. In the adiabatic-inverted regime, strong electronic coupling and low reorganization energy lead all approximate methods to converge with the exact TT results. In contrast, discrepancies emerge in the nonadiabatic or normal regimes, where resolution-of-identity LSC and CMMs provide the reliable predictions. This study establishes the MSH model as a powerful tool for validating nonadiabatic dynamics methods in complex condensed-phase systems.

DOI
10.1063/5.0276946

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We present quantum dynamics of the multi-state harmonic (MSH) model using numerically exact tensor-train (TT)-based calculations. The MSH model provides a general framework for mapping a realistic system onto an effective model Hamiltonian, which is defined in extended spatial dimensions, ensuring consistent reorganization energies between all state pairs. Its analytic structure allows efficient propagation of wavepackets via a rank-adaptive TT-KSL scheme and rigorous finite-temperature dynamics via TT-thermofield dynamics. These exact results are used to benchmark various approximate semiclassical and mixed quantum-classical dynamics, including the linearized semiclassical (LSC), symmetrical quasiclassical, classical mapping models (CMMs), mean-field Ehrenfest, and fewest-switches surface hopping dynamics. We systematically explore the parameter space of the MSH model by changing electronic coupling, reorganization energy, reaction free energy, and the nuclear characteristic frequency. In the adiabatic-inverted regime, strong electronic coupling and low reorganization energy lead all approximate methods to converge with the exact TT results. In contrast, discrepancies emerge in the nonadiabatic or normal regimes, where resolution-of-identity LSC and CMMs provide the reliable predictions. This study establishes the MSH model as a powerful tool for validating nonadiabatic dynamics methods in complex condensed-phase systems.
Accurate quantum dynamics simulations of nonadiabatic processes are important for studies of electron transfer, energy transfer, and photochemical reactions in complex systems. In this comparative study, we benchmark various approximate nonadiabatic dynamics methods with mapping variables against numerically exact calculations based on the tensor-train (TT) representation of high-dimensional arrays, including TT-KSL for zero-temperature dynamics and TT-thermofield dynamics for finite-temperature dynamics. The approximate nonadiabatic dynamics methods investigated include mixed quantum-classical Ehrenfest mean-field and fewest-switches surface hopping, linearized semiclassical mapping dynamics, symmetrized quasiclassical dynamics, the spin-mapping method, and extended classical mapping models. Different model systems were evaluated, including the spin-boson model for nonadiabatic dynamics in the condensed phase, the linear vibronic coupling model for electronic transition through conical intersections, the photoisomerization model of retinal, and Tully's one-dimensional scattering models. Our calculations show that the optimal choice of approximate dynamical method is system-specific, and the accuracy is sensitively dependent on the zero-point-energy parameter and the initial sampling strategy for the mapping variables.
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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.
Addressing needs of contemporary nonlinear femtosecond optical spectroscopy, we have developed a fully quantum, numerically accurate wave function-based approach for the calculation of third-order spectroscopic signals of polyatomic molecules and molecular aggregates at finite temperature. The systems are described by multimode nonadiabatic vibronic-coupling Hamiltonians, in which diagonal terms are treated in harmonic approximation, while off-diagonal interstate couplings are assumed to be coordinate independent. The approach is based on the Thermo Field Dynamics (TFD) representation of quantum mechanics and tensor-train (TT) machinery for efficient numerical simulation of quantum evolution of systems with many degrees of freedom. The developed TFD-TT approach is applied to the calculation of time- and frequency-resolved fluorescence spectra of the Fenna-Matthews-Olson (FMO) antenna complex at room temperature taking into account finite time-frequency resolution in fluorescence detection, orientational averaging, and static disorder.
We present a streamlined implementation of a computational framework for constructing and analyzing reduced dynamical maps for complex system--bath models at finite temperature. The methodology is based on three established ingredients of quantum dynamics: the Choi--Jamiołkowski isomorphism for the representation of quantum channels, thermofield (TFD) purification of thermal environments, and tensor-train (TT) propagation of the resulting enlarged pure state. The reduced map is obtained from a single unitary propagation in a thermofield-doubled Hilbert space and represented in matrix form through the Choi--Jamiołkowski isomorphism. The TFD evolution is implemented in the TT representation, enabling efficient propagation of high-dimensional purified thermal states. We illustrate the methodology for exciton transfer in the Fenna--Matthews--Olson complex with site-dependent structured spectral densities represented by discretized bosonic environments. The resulting maps are used to analyze decoherence, relaxation, and finite-memory effects, and to assess the crossover to an effectively time-local description. The proposed approach provides a route to compute reduced propagators and to post-process them into memory kernels, transfer tensors, and effective kinetic rate descriptions for complex molecular systems.
Abstract This review provides the fundamental theoretical tools for the development of a complete wave‐function formalism for the study of time‐evolution of chemico‐physical systems at finite temperature. The methodology is based on the non‐equilibrium thermo‐field dynamics (NE‐TFD) representation of quantum mechanics, which is alternative to the commonly used density matrix representation. TFD concepts are extended and integrated with the tensor‐train (TT) numerical tools leading to a novel and powerful theoretical and computational framework for the study of complex quantum dynamical problems. In addition, NE‐TFD techniques are extended to enable the study of dissipative open systems via a new formulation of the hierarchical equations of motion (HEOM) fully integrated with TT methodologies. We demonstrate that the combination of the TFD machinery with computational advantages of TTs results in a powerful theoretical and computational framework for scrutinizing dynamics of complex multidimensional electron‐vibrational systems. We illustrate the validity and the computational advantages of the developed methodologies by applying them to the study of quantum coherence effects in the energy‐transfer processes in antenna systems, to the analysis of fingerprints of vibrational modes in electron‐transfer and charge‐transfer processes in various model and realistic multidimensional molecular systems, as well as to simulation of other fundamental models of physical chemistry. This article is categorized under: Theoretical and Physical Chemistry > Reaction Dynamics and Kinetics Theoretical and Physical Chemistry > Statistical Mechanics