Coupled Trajectory Surface Hopping with Sign Consistency

11 July 2024, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

The exact factorization (XF) framework has inspired a series of trajectory-based nonadiabatic dynamics methods based on different approximations which have been widely studied in model and realistic systems. The coupled-trajectory surface hopping (CTSH) method was proposed to combine the advantages of fewest switches surface hopping (FSSH) and the coupled-trajectory mixed quantum-classical (CTMQC) method. However, the inconsistency between trajectory’s wave function and active state might lead to incorrect decoherence process in CTSH. To overcome this problem, we propose a new method, named as sign-consistent coupled-trajectory surface hopping (SC-CTSH) which mainly has two different features: (1) uses a different approach to reconstruct the nuclear density to make the quantum momentum smooth and accurate. (2) takes the consistency between the active state and electronic wave function of each trajectory into account. The performance of SC-CTSH is tested in a series of widely studied one-dimensional two-level systems and compared with other XF-based methods. The results show that incorporating with our novel nuclear density construction algorithm and sign consistent correction, we can obtain accurate quantum momentum and make proper decoherence correction during dynamics, which make the combination between XF and FSSH more consistent and reliable. The results also indicate the consistency between electronic wavefunction and active state in surface hopping scheme significant.

Supplementary materials

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Supporting Information: Coupled Trajectory Surface Hopping with Sign Consistency
Description
Supporting information contains three parts of the content 1. Computational details of the benchmark of different methods on scattering models. 2. A step-by-step outline of the trajectory clustering algorithm. 3. Additional results of other models and computational scaling of different methods.
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