History-independent tracers. Forgetful molecular probes of the physical conditions of the dense interstellar medium

Molecular line emission is a powerful probe of the physical conditions of astrophysical objects but can be complex to model, and it is often unclear which transitions would be the best targets for observers who wish to constrain a given parameter. We therefore produce a list of molecular species for which the gas history can be ignored, removing a major modelling complexity. We then determine the best of these species to observe when attempting to constrain various physical parameters. To achieve this, we use a large set of chemical models with different chemical histories to determine which species have abundances at 1 MYr that are insensitive to the initial conditions. We then use radiative transfer modelling to produce the intensity of every transition of these molecules. We finally compute the mutual information between the physical parameters and all transitions and transition ratios in order to rank their usefulness in determining the value of a given parameter. We find 48 species that are insensitive to the chemical history of the gas, 23 of which have collisional data available. We produce a ranked list of all the transitions and ratios of these species using their mutual information with various gas properties. We show mutual information is an adequate measure of how well a transition can constrain a physical parameter by recovering known probes and demonstrating that random forest regression models become more accurate predictors when high-scoring features are included. Therefore, this list can be used to select target transitions for observations in order to maximize knowledge about those physical parameters

Chemulator: Fast, accurate thermochemistry for dynamical models through emulation

Context. Chemical modelling serves two purposes in dynamical models: accounting for the effect of microphysics on the dynamics and providing observable signatures. Ideally, the former must be done as part of the hydrodynamic simulation but this comes with a prohibitive computational cost that leads to many simplifications being used in practice. / Aims. We aim to produce a statistical emulator that replicates a full chemical model capable of solving the temperature and abundances of a gas through time. This emulator should suffer only a minor loss of accuracy when compared to a full chemical solver and would have a fraction of the computational cost allowing it to be included in a dynamical model. / Methods. The gas-grain chemical code UCLCHEM was updated to include heating and cooling processes, and a large dataset of model outputs from possible starting conditions was produced. A neural network was then trained to map directly from inputs to outputs. / Results. Chemulator replicates the outputs of UCLCHEM with an overall mean squared error (MSE) of 1.7 × 10−4 for a single time step of 1000 yr, and it is shown to be stable over 1000 iterations with an MSE of 3 × 10−3 on the log-scaled temperature after one timzze step and 6 × 10−3 after 1000 time steps. Chemulator was found to be approximately 50 000 times faster than the time-dependent model it emulates but can introduce a significant error to some models

Exploiting Network Topology for Accelerated Bayesian Inference of Grain Surface Reaction Networks

In the study of grain-surface chemistry in the interstellar medium, there exists much uncertainty regarding the reaction mechanisms with few constraints on the abundances of grain-surface molecules. Bayesian inference can be performed to determine the likely reaction rates. In this work, we consider methods for reducing the computational expense of performing Bayesian inference on a reaction network by looking at the geometry of the network. Two methods of exploiting the topology of the reaction network are presented. One involves reducing a reaction network to just the reaction chains with constraints on them. After this, new constraints are added to the reaction network and it is shown that one can separate this new reaction network into subnetworks. The fact that networks can be separated into subnetworks is particularly important for the reaction networks of interstellar complex-organic molecules, whose surface reaction networks may have hundreds of reactions. Both methods allow the maximum-posterior reaction rate to be recovered with minimal bias

Chemical tracers of pre-brown dwarf cores formed through turbulent fragmentation

A gas–grain time-dependent chemical code, UCL_CHEM, has been used to investigate the possibility of using chemical tracers to differentiate between the possible formation mechanisms of brown dwarfs. In this work, we model the formation of a pre-brown dwarf core through turbulent fragmentation by following the depth-dependent chemistry in a molecular cloud through the step change in density associated with an isothermal shock and the subsequent freefall collapse once a bound core is produced. Trends in the fractional abundance of molecules commonly observed in star-forming cores are then explored to find a diagnostic for identifying brown dwarf mass cores formed through turbulence. We find that the cores produced by our models would be bright in CO and NH3 but not in HCO+. This differentiates them from models using purely freefall collapse as such models produce cores that would have detectable transitions from all three molecules

Identifying the most constraining ice observations to infer molecular binding energies

Computational astrophysic

Lithium Intercalation into the Excitonic Insulator Candidate Ta2NiSe5

A new reduced phase derived from the excitonic insulator candidate Ta2NiSe5 has been synthesized via the intercalation of lithium. LiTa2NiSe5 crystallizes in the orthorhombic space group Pmnb (no. 62) with lattice parameters a = 3.50247(3) Å, b = 13.4053(4) Å, c = 15.7396(2) Å, and Z = 4, with an increase of the unit cell volume by 5.44(1)% compared with Ta2NiSe5. Significant rearrangement of the Ta-Ni-Se layers is observed, in particular a very significant relative displacement of the layers compared to the parent phase, similar to that which occurs under hydrostatic pressure. Neutron powder diffraction experiments and computational analysis confirm that Li occupies a distorted triangular prismatic site formed by Se atoms of adjacent Ta2NiSe5 layers with an average Li-Se bond length of 2.724(2) Å. Li-NMR experiments show a single Li environment at ambient temperature. Intercalation suppresses the distortion to monoclinic symmetry that occurs in Ta2NiSe5 at 328 K and that is believed to be driven by the formation of an excitonic insulating state. Magnetometry data show that the reduced phase has a smaller net diamagnetic susceptibility than Ta2NiSe5 due to the enhancement of the temperature-independent Pauli paramagnetism caused by the increased density of states at the Fermi level evident also from the calculations, consistent with the injection of electrons during intercalation and formation of a metallic phase

Investigating the impact of reactions of C and CH with molecular hydrogen on a glycine gas-grain network

Stars and planetary system

Investigating the Efficiency of Explosion Chemistry as a Source of Complex Organic Molecules in TMC-1

Many species of complex organic molecules (COMs) have been observed in several astrophysical environments but it is not clear how they are produced, particularly in cold, quiescent regions. One process that has been proposed as a means to enhance the chemical complexity of the gas phase in such regions is the explosion of the ice mantles of dust grains. In this process, a build up of chemical energy in the ice is released, sublimating the ices and producing a short lived phase of high density, high temperature gas. The gas–grain chemical code UCLCHEM has been modified to treat these explosions in order to model the observed abundances of COMs toward the TMC1 region. It is found that, based on our current understanding of the explosion mechanism and chemical pathways, the inclusion of explosions in chemical models is not warranted at this time. Explosions are not shown to improve the model’s match to the observed abundances of simple species in TMC-1. Further, neither the inclusion of surface diffusion chemistry, nor explosions, results in the production of COMs with observationally inferred abundances

Nitrogen fractionation in external galaxies

In star-forming regions in our own Galaxy, the 14N/15N ratio is found to vary from ~100 in meteorites, comets, and protoplanetary discs up to ~1000 in pre-stellar and star-forming cores, while in external galaxies the very few single-dish large-scale measurements of this ratio lead to values of 100-450. The extent of the contribution of isotopic fractionation to these variations is, to date, unknown. In this paper, we present a theoretical chemical study of nitrogen fractionation in external galaxies in order to determine the physical conditions that may lead to a spread of the 14N/15N ratio from the solar value of ~440 and hence evaluate the contribution of chemical reactions in the interstellar medium (ISM) to nitrogen fractionation. We find that the main cause of ISM enrichment of nitrogen fractionation is high gas densities, aided by high fluxes of cosmic rays

Bayesian Inference of the Rates of Surface Reactions in Icy Mantles

Grain surface chemistry and its treatment in gas-grain chemical models is an area of large uncertainty. While laboratory experiments are making progress, there is still much that is unknown about grain surface chemistry. Further, the results and parameters produced by experiments are often not easily translated to the rate equation approach most commonly used in astrochemical modeling. It is possible that statistical methods can reduce the uncertainty in grain surface chemical networks. In this work, a simple model of grain surface chemistry in a molecular cloud is developed and a Bayesian inference of the reactions rates is performed through Markov Chain Monte Carlo sampling. Using observational data of the solid state abundances of major chemical species in molecular clouds, the posterior distributions for the rates of seven reactions producing CO, CO2, CH3OH, and H2O are calculated in a form that is suitable for rate equation models. This represents a vital first step in the development of a method to infer reaction rates from observations of chemical abundances in astrophysical environments