Identifying the most constraining ice observations to infer molecular binding energies
Monthly Notices of the Royal Astronomical Society, vol. 517, pp. 38–46
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.
Authors 4
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Johannes Heyl corresponding
Affiliation as printed
Department of Physics and Astronomy, University College London , Gower Street, London WC1E 6BT, UK
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Leiden University · Leiden Observatory
Affiliation as printed
Leiden Observatory, Leiden University, Huygens Laboratory , Niels Bohrweg 2, NL-2333 CA Leiden, The Netherlands
Mathematical Institute, Leiden University , Snellius Building, Niels Bohrweg 1, NL-2333 CA Leiden, The Netherlands
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Leiden University · Leiden Observatory · University College London
Affiliation as printed
Department of Physics and Astronomy, University College London , Gower Street, London WC1E 6BT, UK
Leiden Observatory, Leiden University, Huygens Laboratory , Niels Bohrweg 2, NL-2333 CA Leiden, The Netherlands
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Leiden University · Leiden Observatory · University College London
Affiliation as printed
Department of Physics and Astronomy, University College London , Gower Street, London WC1E 6BT, UK
Leiden Observatory, Leiden University, Huygens Laboratory , Niels Bohrweg 2, NL-2333 CA Leiden, The Netherlands
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