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  1. Abstract

    An unprecedented array of new observational capabilities are starting to yield key constraints on models of the epoch of first light in the Universe. In this Letter we discuss the implications of the UV radiation background at cosmic dawn inferred by recent JWST observations for radio experiments aimed at detecting the redshifted 21 cm hyperfine transition of diffuse neutral hydrogen. Under the basic assumption that the 21 cm signal is activated by the Lyαphoton field produced by metal-poor stellar systems, we show that a detection at the low frequencies of the EDGES and SARAS3 experiments may be expected from a simple extrapolation of the declining UV luminosity density inferred atz≲ 14 from JWST early galaxy data. Accounting for an early radiation excess above the cosmic microwave background suggests a shallower or flat evolution to simultaneously reproduce low- and high-zcurrent UV luminosity density constraints, which cannot be entirely ruled out, given the large uncertainties from cosmic variance and the faint-end slope of the galaxy luminosity function at cosmic dawn. Our findings raise the intriguing possibility that a high star formation efficiency at early times may trigger the onset of intense Lyαemission at redshiftz≲ 20 and produce a cosmic 21 cm absorption signal 200 Myr after the Big Bang.

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  2. Abstract

    Understanding the connections between galaxy stellar mass, star formation rate, and dark matter halo mass represents a key goal of the theory of galaxy formation. Cosmological simulations that include hydrodynamics, physical treatments of star formation, feedback from supernovae, and the radiative transfer of ionizing photons can capture the processes relevant for establishing these connections. The complexity of these physics can prove difficult to disentangle and obfuscate how mass-dependent trends in the galaxy population originate. Here, we train a machine-learning method called Explainable Boosting Machines (EBMs) to infer how the stellar mass and star formation rate of nearly 6 million galaxies simulated by the Cosmic Reionization on Computers project depend on the physical properties of halo mass, the peak circular velocity of the galaxy during its formation historyvpeak, cosmic environment, and redshift. The resulting EBM models reveal the relative importance of these properties in setting galaxy stellar mass and star formation rate, withvpeakproviding the most dominant contribution. Environmental properties provide substantial improvements for modeling the stellar mass and star formation rate in only ≲10% of the simulated galaxies. We also provide alternative formulations of EBM models that enable low-resolution simulations, which cannot track the interior structure of dark matter halos, to predict the stellar mass and star formation rate of galaxies computed by high-resolution simulations with detailed baryonic physics.

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  3. Abstract The density and temperature properties of the intergalactic medium (IGM) reflect the heating and ionization history during cosmological structure formation, and are primarily probed by the Ly α forest of neutral hydrogen absorption features in the observed spectra of background sources. We present the methodology and initial results from the Cholla IGM Photoheating Simulation (CHIPS) suite performed with the graphics process unit–accelerated Cholla code to study the IGM at high, uniform spatial resolution maintained over large volumes. In this first paper, we examine the IGM structure in CHIPS cosmological simulations that include IGM uniform photoheating and photoionization models where hydrogen reionization is completed early or by redshift z ∼ 6. Comparing with observations of the large- and small-scale Ly α transmitted flux power spectra P ( k ) at redshifts 2 ≲ z ≲ 5.5, the relative agreement of the models depends on scale, with the self-consistent Puchwein et al. IGM photoheating and photoionization model in good agreement with the flux P ( k ) at k ≳ 0.01 s km −1 at redshifts 2 ≲ z ≲ 3.5. On larger scales, the P ( k ) measurements increase in amplitude from z ∼ 4.6 to z ∼ 2.2, faster than the models, and lie in between the model predictions at 2.2 ≲ z ≲ 4.6 for k ≈ 0.002–0.01 s km −1 . We argue that the models could improve by changing the He ii photoheating rate associated with active galactic nuclei to reduce the IGM temperature at z ∼ 3. At higher redshifts, z ≳ 4.5, the observed flux P ( k ) amplitude increases at a rate intermediate between the models, and we argue that for models where hydrogen reionization is completed late ( z ∼ 5.5–6), resolving this disagreement will require inhomogeneous or “patchy” reionization. We then use an additional set of simulations to demonstrate that our results have numerically converged and are not strongly affected by varying cosmological parameters. 
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  4. null (Ed.)
    ABSTRACT We perform a consistent comparison of the mass and mass profiles of massive (M⋆ > 1011.4 M⊙) central galaxies at z ∼ 0.4 from deep Hyper Suprime-Cam (HSC) observations and from the Illustris, TNG100, and Ponos simulations. Weak lensing measurements from HSC enable measurements at fixed halo mass and provide constraints on the strength and impact of feedback at different halo mass scales. We compare the stellar mass function (SMF) and the Stellar-to-Halo Mass Relation (SHMR) at various radii and show that the radius at which the comparison is performed is important. In general, Illustris and TNG100 display steeper values of α where $M_{\star } \propto M_{\rm vir}^{\alpha }$. These differences are more pronounced for Illustris than for TNG100 and in the inner rather than outer regions of galaxies. Differences in the inner regions may suggest that TNG100 is too efficient at quenching in situ star formation at Mvir ≃ 1013 M⊙ but not efficient enough at Mvir ≃ 1014 M⊙. The outer stellar masses are in excellent agreement with our observations at Mvir ≃ 1013 M⊙, but both Illustris and TNG100 display excess outer mass as Mvir ≃ 1014 M⊙ (by ∼0.25 and ∼0.12 dex, respectively). We argue that reducing stellar growth at early times in $M_\star \sim 10^{9-10} \, \mathrm{M}_{\odot }$ galaxies would help to prevent excess ex-situ growth at this mass scale. The Ponos simulations do not implement AGN feedback and display an excess mass of ∼0.5 dex at r < 30 kpc compared to HSC which is indicative of overcooling and excess star formation in the central regions. The comparison of the inner profiles of Ponos and HSC suggests that the physical scale over which the central AGN limits star formation is r ≲ 20 kpc. Joint comparisons between weak lensing and galaxy stellar profiles are a direct test of whether simulations build and deposit galaxy mass in the correct dark matter haloes and thereby provide powerful constraints on the physics of feedback and galaxy growth. Our galaxy and weak lensing profiles are publicly available to facilitate comparisons with other simulations. 
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    Using a 1D Lagrangian code specifically designed to assess the impact of multiple, time-resolved supernovae (SNe) from a single-star cluster on the surrounding medium, we test three commonly used feedback recipes: delayed cooling (e.g. used in the gasoline-2 code), momentum-energy injection (a resolution-dependent transition between momentum-dominated feedback and energy-dominated feedback used, e.g. in the fire-2 code), and simultaneous energy injection (e.g. used in the EAGLE simulations). Our work provides an intermediary test for these recipes: we analyse a setting that is more complex than the simplified scenarios for which many were designed, but one more controlled than a full galactic simulation. In particular, we test how well these models reproduce the enhanced momentum efficiency seen for an 11 SN cluster simulated at high resolution (0.6 pc; a factor of 12 enhancement relative to the isolated SN case) when these subgrid recipes are implemented in low resolution (20 pc) runs. We find that: (1) the delayed cooling model performs well – resulting in 9 times the momentum efficiency of the fiducial isolated SN value – when SNe are clustered and 1051 erg are injected per SN, while clearly overpredicting the momentum efficiency in the single SN test case; (2) the momentum-energy model always achieves good results, with a factor of 5 boost in momentum efficiency; and (3) injecting the energy from all SNe simultaneously does little to prevent overcooling and greatly underproduces the momentum deposited by clustered SNe, resulting in a factor of 3 decrease in momentum efficiency on the average.

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