Pathway-resolved analysis of internal conversion enabled by Gaussian boson sampling
Gaussian Boson Sampling (GBS) has provided strong evidence of quantum advantage, motivating the search for real-world applications. Such applications rely on mapping physical problems to the native GBS output: photon-number patterns sampled from a highly non-trivial probability distribution. Here we derive a GBS-compatible mapping for the rate constant $k_\mathrm{IC}$ of internal conversion (IC), incorporating two important physical effects -- Duschinsky rotations and Herzberg--Teller contribution. We validate this framework using sampling \textit{simulations} of dibenzoterrylene, reproducing reported values of $k_\mathrm{IC}$. Beyond $k_\mathrm{IC}$ reconstruction, we show that the photon-number patterns of GBS encode the vibrational mode combinations responsible for the IC process, which we refer to as non-radiative pathways. This pathway-resolved data can then be grouped in different ways to extract multiple physically motivated observables. In particular, it enables $k_\mathrm{IC}$ analysis at several levels, from individual modes and mode family contributions to recurring vibrational configurations shared by multiple pathways. We find that Duschinsky rotations increase the fraction of $k_\mathrm{IC}$ associated with correlated vibrational pathways from 46% to 86%, and identify the mode combinations with the largest rate contributions. These pathway-resolved insights can guide targeted molecular modifications, including selective deuteration and bond substitution, to control non-radiative decay.