MLatom@XACS team introduced how to use machine learning in chemistry in the CECAM Machine Learning and Quantum Computing for Quantum Molecular Dynamics [MLQCDyn] school. This school aimed at offering state-of-the-art training in quantum molecular dynamics (QMD), machine learning (ML), and quantum computing (QC) to early-stage …

Tutorial on ML in CECAM school MLQCDyn featuring MLatom@XACS Read more »

In the work published in the Journal of Physical Chemistry Letters, we have proposed a one-shot trajectory learning (OSTL) approach that allows an ultrafast prediction of 10-ps-long quantum dynamics of an open quantum system just in 70 milliseconds. OSTL approach takes …

One-Shot Trajectory Learning of Open Quantum Systems Dynamics Read more »

In our work published in the Journal of Physical Chemistry Letters, we investigate the performance of the general-purpose data-driven methods ANI-1ccx and AIQM1 in the calculation of enthalpies of formation. Extensive benchmark tests show that these two methods can achieve …

Toward Chemical Accuracy in Predicting Enthalpies of Formation with General-Purpose Data-Driven Methods Read more »

In the work published in Nature Communications, we have developed a blazingly fast artificial intelligence (AI)-based quantum dynamics (QD) approach with applications to excitation energy transfer in the well-known Fenna–Matthews–Olson (FMO) complex found in green sulfur bacteria.

Our AIQM1 paper is one of the 25 most downloaded Nature Communications articles in chemistry and materials sciences published in 2021! #NCOMTop25 The full list: https://www.nature.com/collections/gagdjjgcgj AIQM1 paper: https://www.nature.com/articles/s41467-021-27340-2 How to use AIQM1 method with MLatom: http://MLatom.com/AIQM1

In the work published in New Journal of Physics, we combine machine learning (ML) with the numerically exact hierarchical equations of motion (HEOM) approach, propagating quantum dynamics of a two-state system (spin-boson model) with only ca. 10% of the HEOM …

Speeding up quantum dissipative dynamics of open systems with kernel methods Read more »

We report global potential energy surfaces (PESs) database VIB5 of 5 molecules of astrophysical interest which was used to produce rovibrational spectra approaching spectroscopic accuracy and contains state-of-the-art, high-level energies and energy gradients. This database can be used to develop …

VIB5 database with accurate ab initio quantum chemical molecular potential energy surfaces Read more »