Using the Prospector spectral energy distribution (SED) fitting code, we analyze the properties of 19 Extreme Emission Line Galaxies (EELGs) identified in the bluest composite SED in the zfourge survey at 2.5 ≤ z ≤ 4. P rospector includes a physical model for nebular emission and returns probability distributions for stellar mass, stellar metallicity, dust attenuation, and nonparametric star formation history (SFH). The EELGs show evidence for a starburst in the most recent 50 Myr, with the median EELG having a specific star formation rate (sSFR) of 4.6 Gyr −1 and forming 15% of its mass in this short time. For a sample of more typical star-forming galaxies (SFGs) at the same redshifts, the median SFG has a sSFR of 1.1 Gyr −1 and forms only 4% of its mass in the last 50 Myr. We find that virtually all of our EELGs have rising SFHs, while most of our SFGs do not. From our analysis, we hypothesize that many, if not most, star-forming galaxies at z ≥ 2.5 undergo an extreme Hβ+[Oiii] emission line phase early in their lifetimes. In a companion paper, we obtain spectroscopic confirmation of the EELGs as part of our MOSEL survey. In the future, explorations of uncertainties in modeling the UV slope for galaxies at z > 2 are needed to better constrain their properties, e.g. stellar metallicities.

Active galactic nuclei (AGNs) feedback models are generally calibrated to reproduce galaxy observables such as the stellar mass function and the bimodality in galaxy colors. We use variations of the AGN feedback implementations in the IllustrisTNG (TNG) and Simba cosmological hydrodynamic simulations to show that the low-redshift Lyα forest can provide constraints on the impact of AGN feedback. We show that TNG overpredicts the number density of absorbers at column densities N HI < 1014 cm−2 compared to data from the Cosmic Origins Spectrograph (in agreement with previous work), and we demonstrate explicitly that its kinetic feedback mode, which is primarily responsible for galaxy quenching, has a negligible impact on the column density distribution (CDD) of absorbers. In contrast, we show that the fiducial Simba model, which includes AGN jet feedback, is the preferred fit to the observed CDD of the z = 0.1 Lyα forest across 5 orders of magnitude in column density. We show that the Simba results with jets produce a quantitatively better fit to the observational data than the Simba results without jets, even when the ultraviolet background is left as a free parameter. AGN jets in Simba are high speed, collimated, weakly interacting with the interstellar medium (via brief hydrodynamic decoupling), and heated to the halo virial temperature. Collectively these properties result in stronger long-range impacts on the intergalactic medium when compared to TNG’s kinetic feedback mode, which drives isotropic winds with lower velocities at the galactic radius. Our results suggest that the low-redshift Lyα forest provides plausible evidence for long-range AGN jet feedback.

We study the sensitivity of the z = 0.1 Lyα forest observables, such as the column density distribution function (CDD), flux PDF, flux power spectrum, and line-width distribution, to subgrid models of active galactic nucleus (AGN) feedback using the Illustris and IllustrisTNG (TNG) cosmological simulations. The two simulations share an identical ultraviolet background (UVB) prescription and similar cosmological parameters, but TNG features an entirely reworked AGN feedback model. Due to changes in the AGN radio-mode model, the original Illustris simulations have a factor of 2–3 fewer Lyα absorbers than TNG at column densities N H i < 1015.5 cm−2. We compare the simulated forest statistics to UV data from the Cosmic Origins Spectrograph (COS) and find that neither simulation can reproduce the slope of the absorber distribution. Both Illustris and TNG also produce significantly smaller line-width distributions than observed in the COS data. We show that TNG is in much better agreement with the observed z = 0.1 flux power spectrum than Illustris. We explore which statistics can disentangle the effects of AGN feedback from alternative UVB models by rescaling the UVB of Illustris to produce a CDD match to TNG. While this UVB rescaling is degenerate with the effect of AGN feedback on the CDD, the amplitude and shape of the flux PDF and 1D flux power spectrum change in a way distinct from the scaling of the UVB. Our study suggests that the z = 0.1 Lyα forest observables can be used as a diagnostic of AGN feedback models.

The Cosmology and Astrophysics with Machine Learning Simulations (CAMELS) project was developed to combine cosmology with astrophysics through thousands of cosmological hydrodynamic simulations and machine learning. CAMELS contains 4233 cosmological simulations, 2049 N-body simulations, and 2184 state-of-the-art hydrodynamic simulations that sample a vast volume in parameter space. In this paper, we present the CAMELS public data release, describing the characteristics of the CAMELS simulations and a variety of data products generated from them, including halo, subhalo, galaxy, and void catalogs, power spectra, bispectra, Lyα spectra, probability distribution functions, halo radial profiles, and X-rays photon lists. We also release over 1000 catalogs that contain billions of galaxies from CAMELS-SAM: a large collection of N-body simulations that have been combined with the Santa Cruz semianalytic model. We release all the data, comprising more than 350 terabytes and containing 143,922 snapshots, millions of halos, galaxies, and summary statistics. We provide further technical details on how to access, download, read, and process the data at https://camels.readthedocs.io.