Sensitivity analysis of aromatic chemistry to gas-phase kinetics in a dark molecular cloud model

The increasingly large number of complex organic molecules detected in the interstellar medium necessitates robust kinetic models that can be relied upon for investigating the involved chemical processes. Such models require rate coefficients for each of the thousands of reactions; the values of these are often estimated or extrapolated, leading to large uncertainties that are rarely quantified. We have performed a global Monte Carlo and a more local one-at-a-time sensitivity analysis on the gas-phase rate coefficients in a 3-phase dark cloud model. Time-dependent sensitivities have been calculated using four metrics to determine key reactions for the overall network as well as for the cyanonaphthalene molecule in particular, an important interstellar species that is severely under-produced by current models. All four metrics find that reactions involving small, reactive species that initiate hydrocarbon growth have large effects on the overall network. Cyanonaphthalene is most sensitive to a number of these reactions as well as ring-formation of the phenyl cation (C6H5+) and aromatic growth from benzene to naphthalene. Future efforts should prioritize constraining rate coefficients of key reactions and expanding the network surrounding these processes. These results highlight the strength of sensitivity analysis techniques to identify critical processes in complex chemical networks, such as those often used in astrochemical modeling.

Tracing the chemical footprint of shocks in AGN-host and starburst galaxies with ALMA multi-line molecular studies

Multi-line molecular observations are an ideal tool for a systematic study of the physico-chemical processes in the Interstellar Medium (ISM), given the wide range of critical densities associated with different molecules and their transitions, and the dependencies of chemical reactions on the energy budget of the system. Recently high spatial resolution of typical shock tracers - SiO, HNCO, and CH3OH - have been studied in the potentially shocked regions in two nearby galaxies: NGC 1068 (an AGN-host galaxy) (Huang et al., Astron. Astrophys., 2022, 666, A102; Huang et al., in prep.) and NGC 253 (a starburst galaxy) (K.-Y. Huang et al., arXiv, 2023, preprint, arXiv:2303.12685, DOI: 10.48550/arXiv.2303.12685). This paper is dedicated to the comparative study of these two distinctively different galaxies, with the aim of determining the differences in their energetics and understanding large-scale shocks in different types of galaxies.

A statistical and machine learning approach to the study of astrochemistry

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, these crucial parameters are the binding energies of the species. However, there exists much disagreement regarding these values in the literature. In this work, a Bayesian inference approach is taken to estimate these values. It is found that this is difficult to do in the absence of enough data. The Massive Optimised Parameter Estimation and Data (MOPED) compression algorithm is then used to help determine which species should be prioritised for future detections in order to better constrain the values of binding energies. Finally, an interpretable machine learning approach is taken in order to better understand the non-linear relationship between binding energies and the final abundances of specific species of interest.

The emergence of interstellar molecular complexity explained by interacting networks

Recent years have witnessed the detection of an increasing number of complex organic molecules in interstellar space, some of them being of prebiotic interest. Disentangling the origin of interstellar prebiotic chemistry and its connection to biochemistry and ultimately, to biology is an enormously challenging scientific goal where the application of complexity theory and network science has not been fully exploited. Encouraged by this idea, we present a theoretical and computational framework to model the evolution of simple networked structures toward complexity. In our environment, complex networks represent simplified chemical compounds and interact optimizing the dynamical importance of their nodes. We describe the emergence of a transition from simple networks toward complexity when the parameter representing the environment reaches a critical value. Notably, although our system does not attempt to model the rules of real chemistry nor is dependent on external input data, the results describe the emergence of complexity in the evolution of chemical diversity in the interstellar medium. Furthermore, they reveal an as yet unknown relationship between the abundances of molecules in dark clouds and the potential number of chemical reactions that yield them as products, supporting the ability of the conceptual framework presented here to shed light on real scenarios. Our work reinforces the notion that some of the properties that condition the extremely complex journey from the chemistry in space to prebiotic chemistry and finally, to life could show relatively simple and universal patterns.

Isotopic ratios and fractionation in the local Universe

The knowledge of isotopic abundances is important in galaxy evolution studies because isotopes provide diagnostics for the chemical enrichment in galaxies over time. While measurements of isotopes in large sample of stars would be ideal to determine the fossil record of the enrichment history, in practice this is hampered by the need of very high resolution, high signal-to-noise spectroscopic data. A complementary, or alternative, method is to measure isotopic ratios from observations of gas-phase interstellar medium (ISM) isotopic abundances. In this proceedings I shall review the observations of the most abundant fractionated species in nearby galaxies and recent modeling efforts aimed at investigating the physical and chemical conditions that can lead to a large spread of isotopic ratios in external local galaxies.

ALCHEMI: Results from the ALMA Comprehensive High-resolution Extragalactic Molecular Inventory of NGC253

The star formation process in galaxies drives their evolution. The physical conditions which drive the star formation process in galaxies are studied using measurements of atomic and molecular species found in the dense has from which stars form in galaxies. Molecular emission measurements at millimeter/submillimeter wavelengths have revealed the molecular complexity of the star formation regions in galaxies. In a recent study of the nearby starburst galaxy NGC253 using the Atacama Large Millimeter/submillimeter Array (ALMA), the ALMA Comprehensive High-resolution Extragalactic Molecular Inventory (ALCHEMI) large program imaged the continuum and spectral line emission from the central molecular zone (CMZ) of this starburst galaxy. In this article we summarize the current results derived from the ALCHEMI large program. Many of these studies have focused on clarifying the state of dense gas heating processes in the NGC253 CMZ.

Astrochemistry: overview and challenges

This paper provides a brief overview of the journey of molecules through the Cosmos, from local diffuse interstellar clouds and PDRs to distant galaxies, and from cold dark clouds to hot star-forming cores, protoplanetary disks, planetesimals and exoplanets. Recent developments in each area are sketched and the importance of connecting astronomy with chemistry and other disciplines is emphasized. Fourteen challenges for the field of Astrochemistry in the coming decades are formulated.