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Full dimensional potential energy surfaces (PESs) based on machine learning (ML) techniques provide means for accurate and efficient molecular simulations in the gas- and condensed-phase for various experimental observables ranging from…
We explore the performance of a statistical learning technique based on Gaussian Process (GP) regression as an efficient non-parametric method for constructing multi-dimensional potential energy surfaces (PES) for polyatomic molecules.…
Gaussian process regression has recently emerged as a powerful, system-agnostic tool for building global potential energy surfaces (PES) of polyatomic molecules. While the accuracy of GP models of PES increases with the number of potential…
Hydrogen atom transfer (HAT) reactions are essential in many biological processes, such as radical migration in damaged proteins, but their mechanistic pathways remain incompletely understood. Simulating HAT is challenging due to the need…
We train an equivariant machine learning model to predict energies and forces for a real-world study of hydrogen combustion under conditions of finite temperature and pressure. This challenging case for reactive chemistry illustrates that…
A detailed characterization of the interaction between the most abundant molecules in air is important for the understanding of a variety of phenomena in atmospherical science. A completely {\em ab initio} global potential energy surface…
The predictive simulation of molecular liquids requires models that are not only accurate, but computationally efficient enough to handle the large systems and long time scales required for reliable prediction of macroscopic properties. We…
The reaction dynamics for the H + HeH$^+$ $\rightarrow$ He + H$_2^+$ reaction in its electronic ground state is investigated using two different representations of the potential energy surface (PES). The first uses a combined kernel and…
Accurate, global Potential Energy Surfaces (PES) expressed in sum-of-products (SOP) form are a prerequisite for efficient high-dimensional quantum dynamics simulations using the MCTDH method. This work introduces a methodology for…
Energy functions for pure and heterogenous systems are one of the backbones for molecular simulation of condensed phase systems. With the advent of machine learned potential energy surfaces (ML-PESs) a new era has started. Statistical…
A detailed interpretation of the detected emission lines of environments in which propyne (or methyl acetylene, CH$_3$CCH) is observed requires a knowledge of its collisional rate coefficients with the most abundant species in the…
We propose a method that exploits sparse representation of potential energy surfaces (PES) on a polynomial basis set selected by compressed sensing. The method is useful for studies involving large numbers of PES evaluations, such as the…
Reaction probabilities as a function of total angular momentum and the resulting reaction cross-sections for the collision of open shell S($^1$D) atoms with para-hydrogen have been calculated in the kinetic energy range 0.09--10 meV (1--120…
Machine-learned potential energy surfaces (PESs) for molecules with more than 10 atoms are typically forced to use lower-level electronic structure methods such as density functional theory and second-order Moller-Plesset perturbation…
Collisional excitation of light hydrides is important to fully understand the complex chemical and physical processes of atmospheric and astrophysical environments. Here, we focus on the NH(X3{\Sigma}-)-Ar van der Waals system. First, we…
The correlation energy of the homogeneous electron gas is evaluated by solving the Bethe-Salpeter equation (BSE) beyond the Tamm-Dancoff approximation for the electronic polarisation propagator. The BSE is expected to improve upon the…
We present a 3D isotropic ab initio three-body (para-H$_2$)$_3$ interaction potential energy surface (PES). The electronic structure calculations are carried out at the correlated coupled-cluster theory level, with single, double, and…
Potential Energy Surface for the ($\mathrm{\bar{p}} - \mathrm{He}^{2+} - \mathrm{He}$) system is calculated in the framework of the restricted (singlet spin state) Hartree-Fock method with subsequent account of the electronic correlations…
We present the first quantum-centric simulations of noncovalent interactions using a supramolecular approach. We simulate the potential energy surfaces (PES) of the water and methane dimers, featuring hydrophilic and hydrophobic…
The Bethe-Salpeter equation (BSE) is the key equation in many-body perturbation theory based on Green's functions to access response properties. Within the $GW$ approximation to the exchange-correlation kernel, the BSE has been successfully…