Radiative cooling rates, ion fractions, molecule abundances and line emissivities including self-shielding and both local and metagalactic radiation fields

TL;DR

This paper presents comprehensive tables generated with Cloudy that detail the physical properties of gas across a wide range of conditions, accounting for various radiation fields, self-shielding, and dust effects, useful for simulations.

Contribution

The authors provide extensive, publicly available tables of gas properties including ionization, molecule fractions, and line emissivities, incorporating self-shielding and multiple radiation sources, for use in hydrodynamical simulations.

Findings

Tables cover redshift 0-9, temperature 1-9.5, metallicity -4 to +0.5, density -8 to +6.

Self-shielding and radiation fields significantly affect ionization and cooling.

Tools include C routines and Python GUI for data exploration.

Abstract

We use the spectral synthesis code Cloudy to tabulate the properties of gas for an extensive range in redshift (z=0 to 9), temperature (log T [K] = 1 to 9.5), metallicity (log Z/$\mathrm{Z}_{\odot}$ = -4 to +0.5, Z=0), and density (log $n_{\mathrm{H}}$ [$\mathrm{cm}^{-3}$] = -8 to +6). This therefore includes gas with properties characteristic of the interstellar, circumgalactic and intergalactic media. The gas is exposed to a redshift-dependent UV/X-ray background, while for the self-shielded lower-temperature gas (i.e. ISM gas) an interstellar radiation field and cosmic rays are added. The radiation field is attenuated by a density- and temperature-dependent column of gas and dust. Motivated by the observed star formation law, this gas column density also determines the intensity of the interstellar radiation field and the cosmic ray density. The ionization balance, molecule fractions, cooling rates, line emissivities, and equilibrium temperatures are calculated self-consistently. We include dust, cosmic rays, and the interstellar radiation field step-by-step to study their relative impact. These publicly available tables are ideal for hydrodynamical simulations. They can be used stand alone or coupled to a non-equilibrium network for a subset of elements. The release includes a C routine to read in and interpolate the tables, as well as an easy to use python graphical user interface to explore the tables.