Leveraging Dynamical Symmetries in Two-Dimensional Electronic Spectra to Extract Population Transfer Pathways

We present a method to deterministically isolate population transfer kinetics from two-dimensional electronic spectroscopic signals. Central to this analysis is the characterization of how all possible subensembles of excited state systems evolve through the population time. When these dynamics are diagrammatically mapped by using double-sided Feynman pathways where population time dynamics are included, a useful symmetry emerges between excited state absorption and ground state bleach recovery dynamics of diagonal and below diagonal cross-peak signals. This symmetry allows removal of pathways from the spectra to isolate signals that evolve according to energy transfer kinetics. We describe a regression procedure to fit to energy transfer time constants and characterize the accuracy of the method in a variety of complex excited state systems using simulated two-dimensional spectra. Our results show that the method is robust for extracting ultrafast energy transfer in multistate excitonic systems, systems containing dark states that affect the signal kinetics, and systems with interfering vibrational relaxation pathways. This procedure can be used to accurately extract energy transfer kinetics from a wide variety of condensed phase systems.