Optimal Transport Distances to Characterize Electronic Excitations.

ABSTRACT: Understanding the character of electronic excitations is important in computational and reaction mechanistic studies, but their classification from simulations remains an open problem. Distances based on optimal transport have proven very useful in a plethora of classification problems and, therefore, seem a natural tool to try to tackle this challenge. We propose and investigate a new diagnostic Θ based on the Sinkhorn divergence from optimal transport. We evaluate a k-NN classification algorithm on Θ, the popular Λ diagnostic, and their combination, and assess their performance in labeling excitations, finding that (i) the combination only slightly improves the classification, (ii) Rydberg excitations are not separated well in any setting, and (iii) Θ breaks down for charge transf

SUBMITTER: Lieberherr AZ 

PROVIDER: S-EPMC11238536 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature