Identifying the most constraining ice observations to infer molecular binding energies

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 (MOPED) compression algorithm to determine which species should be prioritised 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.

arXiv comment10 pages, 4 figures, accepted for publication in MNRAS

References in corpus (34)

• Observations of the Icy Universe
• The UMIST database for astrochemistry 2012
• Karhunen-Loeve eigenvalue problems in cosmology: how should we tackle large data sets?
• Complex Chemistry in Star-Forming Regions: An Expanded Gas-Grain Warm-up Chemical Model
• Formation of methyl formate and other organic species in the warm-up phase of hot molecular cores
• Our astrochemical heritage
• On the Formation of CO2 and Other Interstellar Ices
• Massive Lossless Data Compression and Multiple Parameter Estimation from Galaxy Spectra
• A statistical test for Nested Sampling algorithms
• Binding energies: new values and impact on the efficiency of chemical desorption
• Formation of Complex Molecules in Prestellar Cores: a Multilayer Approach
• H-atom addition and abstraction reactions in mixed CO, H2CO and CH3OH ices: an extended view on complex organic molecule formation
• Collaborative Nested Sampling: Big Data vs. complex physical models
• On the reservoir of sulphur in dark clouds : chemistry and elemental abundance reconciled
• Dust as interstellar catalyst I. Quantifying the chemical desorption process
• Modeling Complex Organic Molecules in dense regions: Eley-Rideal and complex induced reaction
• Rotational spectroscopy, tentative interstellar detection, and chemical modelling of N-methylformamide
• UCLCHEM: A Gas-Grain Chemical Code
• Binding energies of interstellar molecules on crystalline and amorphous models of water ice by ab-initio calculations
• Sensitivity analysis of grain surface chemistry to binding energies of ice species
• Gas-grain chemistry in cold interstellar cloud cores with a microscopic Monte Carlo approach to surface chemistry
• Chemical modelling of complex organic molecules with peptide-like bonds in star-forming regions
• Simultaneous Hydrogenation and UV-photolysis Experiments of NO in CO-rich Interstellar Ice Analogues; linking HNCO, OCN-, NH2CHO and NH2OH
• A new study of an old sink of sulfur in hot molecular cores: the sulfur residue
• Formation of the prebiotic molecule NH${}_2$CHO on astronomical amorphous solid water surfaces: accurate tunneling rate calculations
• An experimental study of the surface formation of methane in interstellar molecular clouds
• Binding Energy of Molecules on Water Ice: Laboratory Measurements and Modeling
• Massive data compression for parameter-dependent covariance matrices
• Infrared spectra of complex organic molecules in astronomically relevant ice matrices. III. Methyl formate and its tentative solid-state detection
• Predicting binding energies of astrochemically relevant molecules via machine learning
• Bayesian Inference of Reaction Rates in Icy Mantles
• Extreme data compression while searching for new physics
• Understanding the Formation and Evolution of Interstellar Ices: A Bayesian Approach
• Exploiting Network Topology for Accelerated Bayesian Inference of Grain Surface Reaction Networks