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We extensively describe our recently established "divide-and-conquer" semiclassical method [M. Ceotto, G. Di Liberto and R. Conte, Phys. Rev. Lett. 119, 010401 (2017)] and propose a new implementation of it to increase the accuracy of…

Chemical Physics · Physics 2018-01-15 Giovanni Di Liberto , Riccardo Conte , Michele Ceotto

In this paper, we extend a method recently reported [Phys. Rev. E 87, 042921 (2012)] for the calculation of the eigestates of classically highly chaotic systems to cases of mixed dynamics, i.e. those presenting regular and irregular motions…

Quantum Physics · Physics 2017-09-13 F. Revuelta , E. Vergini , R. M. Benito , F. Borondo

The vibrational behavior of molecules serves as a crucial fingerprint of their structure, chemical state, and surrounding environment. Neutron vibrational spectroscopy provides comprehensive measurements of vibrational modes without…

Chemical Physics · Physics 2025-02-19 Bowen Han , Pei Zhang , Kshitij Mehta , Massimiliano Lupo Pasini , Mingda Li , Yongqiang Cheng

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 preservation of the unitary of the reduced dimensionality…

Chemical Physics · Physics 2021-01-12 Michele Gandolfi , Alessandro Rognoni , Chiara Aieta , Riccardo Conte , Michele Ceotto

Accurately simulating molecular vibronic spectra remains computationally challenging due to the exponential scaling of required calculations. Here, we show that employing the linear coupling model within the gaussian boson sampling…

Quantum Physics · Physics 2025-08-07 I. Konyshev , R. Pradip , O. Page , C. Ünlüer , R. T. Nasibullin , V. V. Rybkin , W. Pernice , S. Ferrari

We present an equivariant neural network for predicting vibrational and phonon modes of molecules and periodic crystals, respectively. These predictions are made by evaluating the second derivative Hessian matrices of the learned energy…

Disordered Systems and Neural Networks · Physics 2024-03-19 Shiang Fang , Mario Geiger , Joseph G. Checkelsky , Tess Smidt

We discuss a symmetry-adapted algebraic (or vibron) model for molecular spectroscopy. The model is formulated in terms of tensor operators under the molecular point group. In this way, we have identified interactions that are absent in…

Chemical Physics · Physics 2017-11-02 R. Bijker , A. Frank , R. Lemus , J. M. Arias , F. Perez-Bernal

We present a novel approach to calculate molecular IR spectra based on semiclassical molecular dynamics. The main advance from a previous semiclassical method [M. Micciarelli, R. Conte, J. Suarez, M. Ceotto J. Chem. Phys. 149, 064115…

Chemical Physics · Physics 2019-05-15 Marco Micciarelli , Fabio Gabas , Riccardo Conte , Michele Ceotto

In this work we report a computational study of the vibrational features of four different nucleobases employing the divide-and-conquer semiclassical initial value representation molecular dynamics method. Calculations are performed on…

Chemical Physics · Physics 2019-06-14 Fabio Gabas , Giovanni Di Liberto , Michele Ceotto

We present a methodology for computing vibrationally and time-resolved pump-probe spectra, which takes into account all vibrational degrees of freedom and is based on the combination of the thawed Gaussian approximation with on-the-fly ab…

Chemical Physics · Physics 2019-01-31 Tomislav Begušić , Julien Roulet , Jiří Vaníček

We present and test an approximate method for the semiclassical calculation of vibrational spectra. The approach is based on the mixed time-averaging semiclassical initial value representation method, which is simplified to a form that…

Chemical Physics · Physics 2018-03-22 Max Buchholz , Frank Grossmann , Michele Ceotto

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 have preliminary employed to calculate the densities of the…

Chemical Physics · Physics 2020-12-08 Chiara Aieta , Gianluca Bertaina , Marco Micciarelli , Michele Ceotto

We introduce a novel method for the simulation of the impact scattering in vibrational scanning transmission electron microscopy electron energy loss spectroscopy (STEM-EELS) simulations. The phonon-loss process is modeled by a combination…

Materials Science · Physics 2020-01-22 Paul M. Zeiger , Ján Rusz

On-board processing of hyperspectral data with machine learning models would enable unprecedented amount of autonomy for a wide range of tasks, for example methane detection or mineral identification. This can enable early warning system…

Artificial Intelligence · Computer Science 2025-04-15 Vít Růžička , Andrew Markham

A significant challenge in computational chemistry is developing approximations that accelerate \emph{ab initio} methods while preserving accuracy. Machine learning interatomic potentials (MLIPs) have emerged as a promising solution for…

We study the vibrational spectrum of the protonated water dimer, by means of a divide-and-conquer semiclassical initial value representation of the quantum propagator, as a first step in the study of larger protonated water clusters. We use…

Chemical Physics · Physics 2019-09-23 Gianluca Bertaina , Giovanni Di Liberto , Michele Ceotto

Molecular vibrations in solutions, especially OH stretching and bending in water, drive ultrafast energy relaxation and dephasing in chemical and biological systems. We present a machine learning approach for constructing system-bath models…

Chemical Physics · Physics 2026-03-18 Kwanghee Park , Ju-Yeon Jo , Yoshitaka Tanimura

Employing extensive quantum-chemical calculations at the DFT/B3LYP and MP2 level, a quartic force field of isolated N-methylacetamide is constructed. Taking into account 24 vibrational degrees of freedom, the model is employed to perform…

Chemical Physics · Physics 2015-05-13 Hiroshi Fujisaki , Kiyoshi Yagi , Kimihiko Hirao , John E. Straub , Gerhard Stock

Gaussian wavepackets are a popular tool for semiclassical analyses of classically chaotic systems. We demonstrate that they are extremely powerful in the semiquantal analysis of such systems, too, where their dynamics can be recast in an…

chao-dyn · Physics 2009-10-22 Arjendu K. Pattanayak , William C. Schieve

High-throughput approaches for producing approximate vibrational spectral data for molecules of astrochemistry interest rely on scaled harmonic frequency calculations. However, level of theory and basis set pair recommendations for these…

Chemical Physics · Physics 2023-02-09 Juan C. Zapata Trujillo , Laura K. McKemmish
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