2 papers
physics.chem-ph2026
Nonadiabatic excited-state dynamics with quantum Monte Carlo-trained machine learning: azomethane as a stringent test
Alfonso Annarelli, Emiel Slootman, Claudia Filippi
We introduce quantum Monte Carlo (QMC)-trained multi-state machine-learned (ML) force fields for nonadiabatic excited-state dynamics, targeting photochemical processes in which the…
cond-mat.mtrl-sci2024
A brief introduction to the diffusion Monte Carlo method and the fixed-node approximation
Alfonso Annarelli, Dario Alfè, Andrea Zen
Quantum Monte Carlo (QMC) methods represent a powerful family of computational techniques for tackling complex quantum many-body problems and performing calculations of stationary…