An efficient statistical method to compute molecular collisional rate coefficients

TL;DR

This paper introduces a fast quantum statistical method for calculating molecular collisional rate coefficients, enabling more efficient data acquisition for astrophysical spectra analysis, especially for reactive species where traditional methods are costly.

Contribution

The paper presents a novel, computationally efficient quantum statistical approach to determine collisional rate coefficients, validated against accurate calculations, and applicable to complex reactive molecules.

Findings

Method is highly accurate for bound complex collisions up to room temperature.

Accuracy decreases with increasing temperature and potential well depth.

Enables calculation of collisional data for reactive species like H3+, H2O+, and H3O+.

Abstract

Our knowledge about the "cold" Universe often relies on molecular spectra. A general property of such spectra is that the energy level populations are rarely at local thermodynamic equilibrium. Solving the radiative transfer thus requires the availability of collisional rate coefficients with the main colliding partners over the temperature range 10-1000 K. These rate coefficients are notoriously difficult to measure and expensive to compute. In particular, very few reliable collisional data exist for collisions involving reactive radicals or ions. Here we explore the use of a fast quantum statistical method to determine molecular collisional excitation rate coefficients. The method is benchmarked against accurate (but costly) close-coupling calculations. For collisions proceeding through the formation of a strongly-bound complex, the method is found to be highly satisfactory up to room temperature. Its accuracy decreases with the potential well depth and with increasing temperature, as expected. This new method opens the way to the determination of accurate inelastic collisional data involving key reactive species such as H3+, H2O+, and H3O+ for which exact quantum calculations are currently not feasible.