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Simulating the irreversible quantum dynamics of exciton and electron transferproblems poses a nontrivial challenge. Because the irreversibility of thesystem dynamics is a result of quantum thermal activation and dissipationcaused by the surrounding environment, it is necessary to include infiniteenvironmental degrees of freedom in the simulation. Because the capabilities offull quantum dynamics simulations that include the surrounding moleculardegrees of freedom are limited, employing a system-bath model is a practicalapproach. In such a model, the dynamics of excitons or electrons are describedby a system Hamiltonian, while the other degrees of freedom that arise from theenvironmental molecules are described by a harmonic oscillator bath (HOB) andsystem-bath interaction parameters. By extending on a previous study ofmolecular liquids [J. Chem. Theory Comput. 2020, 16, 2099], here we construct asystem-bath model for exciton and electron transfer problems by means of amachine learning approach. We determine both the system and system-bathinteraction parameters, including the spectral distribution of the bath, usingthe electronic excitation energies obtained from a quantum mechanics/molecularmechanics (QM/MM) simulation that is conducted as a function of time. Using theanalytical expressions of optical response functions, we calculate linear andtwo-dimensional electronic (2DES) spectra for indocarbocyanine dimers inmethanol. From these results, we demonstrate the capability of our approach toelucidate the nonequilibrium exciton dynamics of a quantum system in anonintuitive manner.

Modeling and simulating the excited-state dynamics of a system with condensed phases: A machine learning approach