PySpawn

PySpawn performs nonadiabatic quantum molecular dynamics simulations using the ab initio multiple spawning (AIMS) method to study nonadiabatic phenomena and photochemical processes.

Key Features:

• Task-based reorganization of AIMS algorithm: Reorganizes the AIMS algorithm into discrete tasks and provides fine-grained restart capabilities for managing simulation state.
• Interfacing with electronic structure software: Interfaces with electronic structure packages such as TeraChem to obtain on-the-fly potential energy surfaces from ab initio calculations.
• Parallelization potential: Decomposes the algorithm into tasks to enable potential parallel execution across computing resources.
• Python analysis module: Includes a Python-based analysis module for post-simulation data analysis.

Scientific Applications:

• CASSCF-based AIMS simulations: Performs complete active space self-consistent field (CASSCF)-based AIMS simulations of complex molecular systems, exemplified by studies of 1,2-dithienyl-1,2-dicyanoethene.
• Photochemistry and nonadiabatic dynamics: Enables investigation of photochemical processes, nonadiabatic dynamics, and molecular photoswitch behavior.

Methodology:

Implements the ab initio multiple spawning (AIMS) method and dynamically generates potential energy surfaces via on-the-fly electronic structure calculations (e.g., interfacing with TeraChem), supporting simulations across arbitrary dimensions.