36 citations · 60 across the 3 of their papers we have counts for
3 papers
Machine Learning for Vibrational Spectroscopy via Divide-and-Conquer Semiclassical Initial Value Representation Molecular Dynamics with Application to N-Methylacetamide
Michele Gandolfi, Alessandro Rognoni, Chiara Aieta +2
A machine learning algorithm for partitioning the nuclear vibrational space into subspaces is introduced. The subdivision criterion is based on Liouville's theorem, i.e. best prese…
Representing Molecular Ground and Excited Vibrational Eigenstates with Nuclear Densities obtained from Semiclassical Initial Value Representation Molecular Dynamics
Chiara Aieta, Gianluca Bertaina, Marco Micciarelli +1
We present in detail and validate an effective Monte Carlo approach for the calculation of the nuclear vibrational densities via integration of molecular eigenfunctions that we hav…
Improved semiclassical dynamics through adiabatic switching trajectory sampling
Riccardo Conte, Lorenzo Parma, Chiara Aieta +2
We introduce an improved semiclassical dynamics approach to quantum vibrational spectroscopy. In this method, a harmonic-based phase space sampling is preliminarily driven toward n…