Preprint
Jul 2026
Nonadiabatic excited-state dynamics with quantum Monte Carlo-trained machine learning: azomethane as a stringent test
QMC-ML is established as a practical route to nonadiabatic photochemical dynamics with accurate wave-function reference data, targeting photochemical processes in which the electronic character changes along the reaction path and a consistent correlated description is required.
Alfonso Annarelli, Emiel Slootman, C. Filippi
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