A non-Markovian neural quantum propagator and its application in the simulation of ultrafast nonlinear spectra
Year: 2024
Type: article
Abstract: The accurate solution of dissipative quantum dynamics plays an important role in the simulation of open quantum systems. Here, we propose a machine learning-based universal solver for the hierarchical equations of motion, one of the most widely used approaches which takes into account non-Markovian effects and nonperturbative system-environment interactions in a numerically exact manner. We develop a neural quantum propagator model by utilizing the neural network architecture, which avoids time-consuming iterations and can be used to evolve any initial quantum state for arbitrarily long times. To demonstrate the efficacy of our model, we apply it to the simulation of population dynamics and linear and two-dimensional spectra of the Fenna-Matthews-Olson complex.
DOI: 10.1039/d4cp03736g
Authors: Jiaji Zhang, Lipeng Chen
Institution: Zhejiang Lab
Language: English
Subfield: Atomic and Molecular Physics, and Optics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4404696964