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September 23, 2025The Journal of Chemical Physics4 citationsOpen Access

Quantum dynamics at conical intersections in solution. I. Multiplicative neural networks and thermofields

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BBBartosz BłasiakDBDominik BreyRMRocco Martinazzo

Key Points

  • Quantum dynamics is significantly influenced by environmental effects on the vibronic dynamics at conical intersections.
  • The study employs a multiplicative neural network (m-NN) approach, tailored to fit the diabatic representation for effective modeling.
  • Thermofield dynamics (TFD) incorporates thermal averaging, facilitating the analysis of interactions between initial vibronic correlations and environmental modes.
  • The model describes the isomerization of protonated Schiff bases in solution, portraying the solvent through an overdamped Brownian-oscillator spectral density.

Abstract

Environmental effects on the vibronic dynamics at a conical intersection can be captured by collective modes, which affect both the topology of the nonadiabatically coupled potential surfaces and the transient dynamics. Here, we show how neural network (NN) potentials can be adapted to a combination of intramolecular coordinates and collective environmental modes. Specifically, we use multiplicative NN (m-NN) potentials, which are fitted to a diabatic representation of regularized diabatic states type. These potentials are readily combined with multiconfigurational wave functions for high-dimensional quantum dynamics. The thermofield dynamics (TFD) approach is employed to include thermal averaging at the wave function level, and we formulate a thermal NN/TFD Hamiltonian that accommodates initial vibronic correlations and collective/residual-mode coupling in the environmental subspace. For a model system describing the isomerization of protonated Schiff bases in solution, the solvent is represented by an overdamped Brownian-oscillator spectral density. In a companion paper B. Błasiak et al., J. Chem. Phys. 163, 124109 (2025), the resulting m-NN/TFD Hamiltonian is employed in real-time quantum dynamical simulations using the multi-layer multiconfiguration time-dependent Hartree method.

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Cite This Study

Błasiak et al. (2025) studied this question.

synapsesocial.com/papers/68d4759031b076d99fa6d671https://doi.org/10.1063/5.0284503
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