Welcome
Simulation approaches to spectroscopy (UV-visible, IR, Raman, sum frequency generation spectroscopy, 2D UV, 3D IR-UV,…) are extremely valuable to help interpret experimental spectra, assign bands and rationalize observed shifts. Typically, one tries to simulate the experimentally measured spectrum, and then analyses the simulation to bring additional molecular insight.
For electronic spectroscopy, one needs at the same time to use quantum methods to obtain an accurate description of the ground and excited states energies, and to properly sample the geometries in both states.
For vibrational spectroscopy, advanced polarizable force fields (e.g. AMOEBA) are used to obtain the dipole and polarizability fluctuations required for spectra calculations. Polarizable forces fields are used for biomolecular simulations [7], but also for the study of infrared spectra [8], solid states [9], charge transfer states, transitions states [10]. An alternative is offered by frequency maps, that are trained on quantum data, and allow to compute spectra from simulations using standard non polarizable force fields [11]. Very recently, several Machine Learning-enhanced approaches have been suggested [12-14].
