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Abstract In the current era of high-zgalaxy discovery with JWST and the Atacama Large Millimeter/submillimeter Array, our ability to study the stellar populations and interstellar medium conditions in a diverse range of galaxies at Cosmic Dawn has rapidly improved. At the same time, the need to understand the current limitations in modeling galaxy formation processes and physical properties in order to interpret these observations is critical. Here, we study the challenges in modeling galaxy dust temperatures, both in the context of forward modeling galaxy spectral properties from a hydrodynamical simulation and via backwards modeling galaxy physical properties from mock observations of far-infrared dust emission. Using thesimbamodel for galaxy formation combined withpowderdayradiative transfer, we can accurately predict the evolution of dust at high redshift, though several aspects of the model are essentially free parameters (dust composition, subresolution dust in star-forming regions) that dull the predictive power of the model dust temperature distributions. We also highlight the uncertainties in the backwards modeling methods, where we find the commonly used models and assumptions to fit far-infrared spectral energy distributions and infer dust temperatures (e.g., single temperature, optically thin modified blackbody) largely fail to capture the complexity of high-zdusty galaxies. We caution that conclusions inferred from both simulations—limited by resolution and post-processing techniques—and observations—limited by sparse data and simplistic model parameterizations—are susceptible to unique and nuanced uncertainties that can limit the usefulness of current high-zdust measurements. 

We present a new methodology for simulating mid-infrared emission from polycyclic aromatic hydrocarbons (PAHs) in galaxy evolution simulations. To do this, we combine theoretical models of PAH emission features as they respond to varying interstellar radiation fields, grain-size distributions, and ionization states with a new model for dust evolution in galaxy simulations. We apply these models to three idealized arepo galaxy evolution simulations within the smuggle physics framework. We use these simulations to develop numerical experiments investigating the buildup of PAH masses and luminosities in galaxies in idealized analogs of the Milky Way, a dwarf galaxy, and a starburst disk. Our main results are as follows. Galaxies with high specific star formation rates have increased feedback energy per unit mass, and are able to shatter grains efficiently, driving up the fraction of ultrasmall grains. At the same time, in our model large radiation fields per unit gas density convert aliphatic grains into aromatics. The fraction of dust grains in the form of PAHs (q_PAH) can be understood as a consequence of these processes, and in our model PAHs form primarily from interstellar processing (shattering) of larger grains rather than from the growth of smaller grains. We find that the hardness of the radiation field plays a larger role than variations in the grain-size distribution in setting the total integrated PAH luminosities, though cosmological simulations are necessary to investigate fully the complex interplay of processes that drive PAH band luminosities in galaxies. 

Abstract One of the most common methods for inferring galaxy attenuation curves is via spectral energy distribution (SED) modeling, where the dust attenuation properties are modeled simultaneously with other galaxy physical properties. In this paper, we assess the ability of SED modeling to infer these dust attenuation curves from broadband photometry, and suggest a new flexible model that greatly improves the accuracy of attenuation curve derivations. To do this, we fit mock SEDs generated from the simba cosmological simulation with the prospector SED fitting code. We consider the impact of the commonly assumed uniform screen model and introduce a new nonuniform screen model parameterized by the fraction of unobscured stellar light. This nonuniform screen model allows for a nonzero fraction of stellar light to remain unattenuated, resulting in a more flexible attenuation curve shape by decoupling the shape of the UV attenuation curve from the optical attenuation curve. The ability to constrain the dust attenuation curve is significantly improved with the use of a nonuniform screen model, with the median offset in UV attenuation decreasing from −0.30 dex with a uniform screen model to −0.17 dex with the nonuniform screen model. With this increase in dust attenuation modeling accuracy, we also improve the star formation rates (SFRs) inferred with the nonuniform screen model, decreasing the SFR offset on average by 0.12 dex. We discuss the efficacy of this new model, focusing on caveats with modeling star-dust geometries and the constraining power of available SED observations. 

Abstract Observations of local star-forming galaxies (SFGs) show a tight correlation between their singly ionized carbon line luminosity ($$L_{\rm [C\, \small {II}]}$$) and star formation rate (SFR), suggesting that $$L_{\rm [C\, \small {II}]}$$ may be a useful SFR tracer for galaxies. Some other galaxy populations, however, are found to have lower $$L_{\rm [C\, \small {II}]}{}/{}\rm SFR$$ than local SFGs, including the infrared-luminous, starburst galaxies at low and high redshifts as well as some moderately star-forming galaxies at the epoch of re-ionization (EoR). The origins of this ‘$$\rm [C\, \small {II}]$$ deficit’ is unclear. In this work, we study the $$L_{\rm [C\, \small {II}]}$$-SFR relation of galaxies using a sample of z = 0 − 8 galaxies with M* ≈ 107 − 5 × 1011 M⊙ extracted from cosmological volume and zoom-in simulations from the Feedback in Realistic Environments (fire) project. We find a simple analytic expression for $$L_{\rm [C\, \small {II}]}$$/SFR of galaxies in terms of the following parameters: mass fraction of $$\rm [C\, \small {II}]$$-emitting gas ($$f_{\rm [C\, \small {II}]}$$), gas metallicity (Zgas), gas density (ngas) and gas depletion time ($$t_{\rm dep}{}={}M_{\rm gas}{}/{}\rm SFR$$). We find two distinct physical regimes: $$\rm H_2$$-rich galaxies where tdep is the main driver of the $$\rm [C\, \small {II}]$$ deficit and $$\rm H_2$$-poor galaxies where Zgas is the main driver. The observed $$\rm [C\, \small {II}]$$ deficit of IR-luminous galaxies and early EoR galaxies, corresponding to the two different regimes, is due to short gas depletion time and low gas metallicity, respectively. Our result indicates that the $$\rm [C\, \small {II}]$$ deficit is a common phenomenon of galaxies, and caution needs to be taken when applying a constant $$L_{\rm [C\, \small {II}]}$$-to-SFR conversion factor derived from local SFGs to estimate cosmic SFR density at high redshifts and interpret data from upcoming $$\rm [C\, \small {II}]$$ line intensity mapping experiments. 

Abstract We present the first spatially resolved maps of gas-phase metallicity for two dust-obscured star-forming galaxies atz∼ 4, from the JWST TEMPLATES Early Release Science program, derived from NIRSpec integral field unit spectroscopy of the Hαand [Nii] emission lines. Empirical optical line calibrations are used to determine that the sources are globally enriched to near-solar levels. While one source shows elevated [N ii]/Hαratios and broad Hαemission consistent with the presence of an active galactic nucleus in a ≳1 kpc region, we argue that both systems have already undergone significant metal enrichment as a result of their extremely high star formation rates. Utilizing Atacama Large Millimeter/submillimeter Array rest-frame 380μm continuum and [Ci](³P₂–³P₁) line maps we compare the spatial variation of the metallicity and gas-to-dust ratio in the two galaxies, finding the two properties to be anticorrelated on highly resolved spatial scales, consistent with various literature studies ofz∼ 0 galaxies. The data are indicative of the enormous potential of JWST to probe the enrichment of the interstellar medium on ∼kpc scales in extremely dust-obscured systems atz∼ 4 and beyond. 

Abstract Understanding the halo–galaxy connection is fundamental in order to improve our knowledge on the nature and properties of dark matter. In this work, we build a model that infers the mass of a halo given the positions, velocities, stellar masses, and radii of the galaxies it hosts. In order to capture information from correlations among galaxy properties and their phase space, we use Graph Neural Networks (GNNs), which are designed to work with irregular and sparse data. We train our models on galaxies from more than 2000 state-of-the-art simulations from the Cosmology and Astrophysics with MachinE Learning Simulations project. Our model, which accounts for cosmological and astrophysical uncertainties, is able to constrain the masses of the halos with a ∼0.2 dex accuracy. Furthermore, a GNN trained on a suite of simulations is able to preserve part of its accuracy when tested on simulations run with a different code that utilizes a distinct subgrid physics model, showing the robustness of our method. The PyTorch Geometric implementation of the GNN is publicly available on GitHub ( https://github.com/PabloVD/HaloGraphNet ).