Accurate and Efficient Strategies for Simulating 2D Electronic Spectroscopy in the Condensed Phase

Explore advanced computational methods for simulating two-dimensional electronic spectroscopy (2DES) in this 29-minute seminar from Cambridge Materials' Lennard-Jones Centre discussion group. Learn how machine learning and quantum dynamics approaches can accurately and efficiently model electronic spectroscopy in condensed phase systems, overcoming the computational challenges of traditional atomistic molecular dynamics simulations. Discover how equivariant transformer-based machine learning architectures, trained with minimal electronic structure calculations, can construct accurate potential energy surfaces for both ground and excited states. Examine the practical application of these methods through the simulation of Nile blue chromophore dynamics in ethanol, where experimental 2DES results are reproduced and explained by decomposing spectroscopic signals to reveal the underlying nuclear motions of chromophores and solvents. Understand how these computational strategies connect spectroscopic observations to their molecular origins, providing insights into electronic energy relaxation processes. Gain knowledge of recent developments in nonadiabatic quantum dynamics approaches, including pure-state Ehrenfest and spin-mapping methods, that enable efficient simulation of 2DES for molecules, proteins, and solid-state materials interacting with their surrounding environments.