12 citations · 31 across the 9 of their papers we have counts for
4 papers · 1 filter
Disentangling Multiple Emitting Components in Molecular Observations with Non-negative Matrix Factorization
Damien de Mijolla, Jonathan Holdship, Serena Viti +1
Molecular emission from the galactic and extragalactic interstellar medium (ISM) is often used to determine the physical conditions of the dense gas. However, even from spatially r…
Understanding Molecular Abundances in Star-Forming Regions Using Interpretable Machine Learning
Johannes Heyl, Joshua Butterworth, Serena Viti
Astrochemical modelling of the interstellar medium typically makes use of complex computational codes with parameters whose values can be varied. It is not always clear what the ex…
A statistical and machine learning approach to the study of astrochemistry
Johannes Heyl, Serena Viti, Gijs Vermariën
In order to obtain a good understanding of astrochemistry, it is crucial to better understand the key parameters that govern grain-surface chemistry. For many chemical networks, th…
Investigating the impact of reactions of C and CH with molecular hydrogen on a glycine gas-grain network
Johannes Heyl, Thanja Lamberts, Serena Viti +1
The impact of including the reactions of C and CH with molecular hydrogen in a gas-grain network is assessed via a sensitivity analysis. To this end, we vary 3 parameters, namely,…