Abstract

Linear spectroscopies, ranging from electronic to Raman and infra-red, are the workhorse methods used to interrogate nuclear and electronic time and energy scales of chemical systems. However, in disordered condensed phase systems the presence of many overlapping features makes decoding the information present to obtain the individual processes and states present, the timescales of their interconversion, and the molecular motions they arise from extremely challenging. In this talk, I will discuss how one can harness theory and simulations that include both nuclear and electronic quantum effects and machine learning to provide molecular-level insights into multidimensional spectroscopies. In particular, two-dimensional electronic spectroscopy (2DES) provides rich information about how the electronic states of molecules, proteins, and solid-state materials interact with each other and their surrounding environment that can be interpreted with the aid of simulations. I will discuss how one can leverage and develop methods from electronic structure theory, machine learning, and electronically nonadiabatic quantum dynamics to develop practical approaches to simulate and understand 2DES with atomistic detail, to uncover how nuclear motions mediate electronic energy relaxation and how these processes manifest in electronic spectroscopies.