Alec Owens

The ExoMol database: Molecular line lists for exoplanet and other hot atmospheres

The ExoMol database (www.exomol.com) provides extensive line lists of molecular transitions which are valid over extended temperature ranges. The status of the current release of the database is reviewed and a new data structure is specified. This structure augments the provision of energy levels (and hence transition frequencies) and Einstein A coefficients with other key properties, including lifetimes of individual states, temperature-dependent cooling functions, Lande g-factors, partition functions, cross sections, k-coefficients and transition dipoles with phase relations. Particular attention is paid to the treatment of pressure broadening parameters. The new data structure includes a definition file which provides the necessary information for utilities accessing ExoMol through its application programming interface (API). Prospects for the inclusion of new species into the database are discussed.

Accurate ab initio vibrational energies of methyl chloride

Two new nine-dimensional potential energy surfaces (PESs) have been generated using high-level ab initio theory for the two main isotopologues of methyl chloride, CH3 (35)Cl and CH3 (37)Cl. The respective PESs, CBS-35( HL), and CBS-37( HL), are based on explicitly correlated coupled cluster calculations with extrapolation to the complete basis set (CBS) limit, and incorporate a range of higher-level (HL) additive energy corrections to account for core-valence electron correlation, higher-order coupled cluster terms, scalar relativistic effects, and diagonal Born-Oppenheimer corrections. Variational calculations of the vibrational energy levels were performed using the computer program TROVE, whose functionality has been extended to handle molecules of the form XY 3Z. Fully converged energies were obtained by means of a complete vibrational basis set extrapolation. The CBS-35( HL) and CBS-37( HL) PESs reproduce the fundamental term values with root-mean-square errors of 0.75 and 1.00 cm(-1), respectively. An analysis of the combined effect of the HL corrections and CBS extrapolation on the vibrational wavenumbers indicates that both are needed to compute accurate theoretical results for methyl chloride. We believe that it would be extremely challenging to go beyond the accuracy currently achieved for CH3Cl without empirical refinement of the respective PESs.

A global potential energy surface and dipole moment surface for silane

A new nine-dimensional potential energy surface (PES) and dipole moment surface (DMS) for silane have been generated using high-level ab initio theory. The PES, CBS-F12(HL), reproduces all four fundamental term values for (28)SiH4 with sub-wavenumber accuracy, resulting in an overall root-mean-square error of 0.63 cm(-1). The PES is based on explicitly correlated coupled cluster calculations with extrapolation to the complete basis set limit, and incorporates a range of higher-level additive energy corrections to account for core-valence electron correlation, higher-order coupled cluster terms, and scalar relativistic effects. Systematic errors in computed intra-band rotational energy levels are reduced by empirically refining the equilibrium geometry. The resultant Si-H bond length is in excellent agreement with previous experimental and theoretical values. Vibrational transition moments, absolute line intensities of the ν3 band, and the infrared spectrum for (28)SiH4 including states up to J = 20 and vibrational band origins up to 5000 cm(-1) are calculated and compared with available experimental results. The DMS tends to marginally overestimate the strength of line intensities. Despite this, band shape and structure across the spectrum are well reproduced and show good agreement with experiment. We thus recommend the PES and DMS for future use.

A highly accurate ab initio potential energy surface for methane.

A new nine-dimensional potential energy surface (PES) for methane has been generated using state-of-the-art ab initio theory. The PES is based on explicitly correlated coupled cluster calculations with extrapolation to the complete basis set limit and incorporates a range of higher-level additive energy corrections. These include core-valence electron correlation, higher-order coupled cluster terms beyond perturbative triples, scalar relativistic effects, and the diagonal Born-Oppenheimer correction. Sub-wavenumber accuracy is achieved for the majority of experimentally known vibrational energy levels with the four fundamentals of (12)CH4 reproduced with a root-mean-square error of 0.70 cm(-1). The computed ab initio equilibrium C-H bond length is in excellent agreement with previous values despite pure rotational energies displaying minor systematic errors as J (rotational excitation) increases. It is shown that these errors can be significantly reduced by adjusting the equilibrium geometry. The PES represents the most accurate ab initio surface to date and will serve as a good starting point for empirical refinement.

Structure-based sampling and self-correcting machine learning for accurate calculations of potential energy surfaces and vibrational levels

We present an efficient approach for generating highly accurate molecular potential energy surfaces (PESs) using self-correcting, kernel ridge regression (KRR) based machine learning (ML). We introduce structure-based sampling to automatically assign nuclear configurations from a pre-defined grid to the training and prediction sets, respectively. Accurate high-level ab initio energies are required only for the points in the training set, while the energies for the remaining points are provided by the ML model with negligible computational cost. The proposed sampling procedure is shown to be superior to random sampling and also eliminates the need for training several ML models. Self-correcting machine learning has been implemented such that each additional layer corrects errors from the previous layer. The performance of our approach is demonstrated in a case study on a published high-level ab initio PES of methyl chloride with 44 819 points. The ML model is trained on sets of different sizes and then used to predict the energies for tens of thousands of nuclear configurations within seconds. The resulting datasets are utilized in variational calculations of the vibrational energy levels of CH3Cl. By using both structure-based sampling and self-correction, the size of the training set can be kept small (e.g., 10% of the points) without any significant loss of accuracy. In ab initio rovibrational spectroscopy, it is thus possible to reduce the number of computationally costly electronic structure calculations through structure-based sampling and self-correcting KRR-based machine learning by up to 90%.

Accurate prediction of H3O+ and D3O+ sensitivity coefficients to probe a variable proton-to-electron mass ratio

The mass sensitivity of the vibration-rotation-inversion transitions of H

Enhanced sensitivity to a possible variation of the proton-to-electron mass ratio in ammonia

_3{}^{16}

Anomalous phosphine sensitivity coefficients as probes for a possible variation of the proton-to-electron mass ratio

O

Simulating electric field interactions with polar molecules using spectroscopic databases

^+

The rotation–vibration spectrum of methyl fluoride from first principles

, H