Identifying the most constraining ice observations to infer molecular binding energies. Issue 1 (17th September 2022)

• Record Type: Journal Article
• Authors: Heyl, Johannes; Sellentin, Elena; Holdship, Jonathan; Viti, Serena
• Is Part Of: Monthly notices of the Royal Astronomical Society. Volume 517:Issue 1(2022)
• Page Start: 38
• Page End: 46
• Publication Date: 2022-09-17
• Subjects: astrochemistry -- methods: data analysis -- methods: statistical -- ISM: abundances; Astronomy -- Periodicals; Periodicals; 520.5
• DOI: 10.1093/mnras/stac2652
• Languages: English
• ISSNs: 0035-8711

Abstract

ABSTRACT: In order to understand grain-surface chemistry, one must have a good understanding of the reaction rate parameters. For diffusion-based reactions, these parameters are binding energies of the reacting species. However, attempts to estimate these values from grain-surface abundances using Bayesian inference are inhibited by a lack of enough sufficiently constraining data. In this work, we use the Massive Optimised Parameter Estimation and Data compression algorithm to determine which species should be prioritized for future ice observations to better constrain molecular binding energies. Using the results from this algorithm, we make recommendations for which species future observations should focus on.