Multiple Spawning with Optimal Basis Set Expansion

TL;DR

This paper introduces an optimized spawning algorithm for the Full Multiple Spawning method, enhancing efficiency in quantum dynamics simulations by maximizing coupling during spawning events, demonstrated on model systems.

Contribution

A novel algorithm for initial conditions in spawning that improves convergence efficiency by maximizing parent-child trajectory coupling.

Findings

Reduced number of spawns needed for convergence

Effective population transfer modeling in quantum dynamics

Validated on model systems with avoided crossing and conical intersection

Abstract

The Full Multiple Spawning (FMS) method is designed to simulate quantum dynamics in the multi-state electronic problem. The FMS nuclear wavefunction is represented in a basis of coupled, frozen Gaussians, and the spawning procedure prescribes a means of adaptively increasing the size of the basis in order to capture population transfer between electronic states. Parent trajectories create children when passing through regions of significant nonadiabatic coupling. In order to converge branching ratios without allowing the basis to reach an impractical size, population transfer at individual spawning events should be made as effective as possible. Herein we detail a new algorithm for specifying the initial conditions of freshly spawned basis functions, one that minimizes the number of spawns needed for convergence by maximizing the efficiency of individual spawning events. Optimization is achieved by maximizing the coupling between parent and child trajectories, as a function of child position and momentum, at the point of spawning. The method is tested with a two-state, one-mode avoided crossing model and a two-state, two-mode conical intersection model.