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    Dark matter halo demographics and assembly histories are a manifestation of cosmological structure formation and have profound implications for the formation and evolution of galaxies. In particular, merger trees provide fundamental input for several modelling techniques, such as semi-analytic models (SAMs), sub-halo abundance matching (SHAM), and decorated halo occupation distribution models. Motivated by the new ultra-high-redshift (z ≳ 10) frontier enabled by JWST, we present a new suite of Gadget at Ultrahigh Redshift with Extra-Fine Timesteps (gureft) dark matter-only cosmological simulations that are carefully designed to capture halo merger histories and structural properties in the ultra-z universe. The simulation suite consists of four 10243-particle simulations with box sizes of 5, 15, 35, and 90 Mpc h−1, each with 170 snapshots stored between 40 ≥ z ≥ 6. With the unprecedented number of available snapshots and strategically chosen dynamic range covered by these boxes, gureft uncovers the emerging dark matter halo populations and their assembly histories in the earliest epochs of cosmic history. In this work, we present the halo mass functions (HMF) between z ∼ 20 and 6 down to log (Mvir/M⊙) ∼ 5, and show that at high redshift, these robust HMFs can differ substantially from commonly used analytic approximations or older fitting functions in the literature. We also present key physical properties of the ultra-high z halo population, such as concentration and spin, as well as their mass growth and merger rates, and again provide updated fitting functions.

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    The physical origin of the seeds of supermassive black holes (SMBHs), with postulated initial masses ranging from ∼105 M⊙ to as low as ∼102 M⊙, is currently unknown. Most existing cosmological hydrodynamic simulations adopt very simple, ad hoc prescriptions for BH seeding and seed at unphysically high masses ∼105–106 M⊙. In this work, we introduce a novel sub-grid BH seeding model for cosmological simulations that is directly calibrated to high-resolution zoom simulations that explicitly resolve ∼103 M⊙ seeds forming within haloes with pristine, dense gas. We trace the BH growth along galaxy merger trees until their descendants reach masses of ∼104 or 105 M⊙. The results are used to build a new stochastic seeding model that directly seeds these descendants in lower resolution versions of our zoom region. Remarkably, we find that by seeding the descendants simply based on total galaxy mass, redshift and an environmental richness parameter, we can reproduce the results of the detailed gas-based seeding model. The baryonic properties of the host galaxies are well reproduced by the mass-based seeding criterion. The redshift-dependence of the mass-based criterion captures the combined influence of halo growth, dense gas formation, and metal enrichment on the formation of ∼103 M⊙ seeds. The environment-based seeding criterion seeds the descendants in rich environments with higher numbers of neighbouring galaxies. This accounts for the impact of unresolved merger dominated growth of BHs, which produces faster growth of descendants in richer environments with more extensive BH merger history. Our new seed model will be useful for representing a variety of low-mass seeding channels within next-generation larger volume uniform cosmological simulations.

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    Extracting information from the total matter power spectrum with the precision needed for upcoming cosmological surveys requires unraveling the complex effects of galaxy formation processes on the distribution of matter. We investigate the impact of baryonic physics on matter clustering at z = 0 using a library of power spectra from the Cosmology and Astrophysics with MachinE Learning Simulations project, containing thousands of $(25\, h^{-1}\, {\rm Mpc})^3$ volume realizations with varying cosmology, initial random field, stellar and active galactic nucleus (AGN) feedback strength and subgrid model implementation methods. We show that baryonic physics affects matter clustering on scales $k \gtrsim 0.4\, h\, \mathrm{Mpc}^{-1}$ and the magnitude of this effect is dependent on the details of the galaxy formation implementation and variations of cosmological and astrophysical parameters. Increasing AGN feedback strength decreases halo baryon fractions and yields stronger suppression of power relative to N-body simulations, while stronger stellar feedback often results in weaker effects by suppressing black hole growth and therefore the impact of AGN feedback. We find a broad correlation between mean baryon fraction of massive haloes (M200c > 1013.5 M⊙) and suppression of matter clustering but with significant scatter compared to previous work owing to wider exploration of feedback parameters and cosmic variance effects. We show that a random forest regressor trained on the baryon content and abundance of haloes across the full mass range 1010 ≤ Mhalo/M⊙<1015 can predict the effect of galaxy formation on the matter power spectrum on scales k = 1.0–20.0 $h\, \mathrm{Mpc}^{-1}$.

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  4. Abstract

    The circumgalactic medium (CGM) plays a pivotal role in regulating gas flows around galaxies and thus shapes their evolution. However, the details of how galaxies and their CGM coevolve remain poorly understood. We present a new time-dependent two-zone model that self-consistently tracks not just mass and metal flows between galaxies and their CGM but also the evolution of the global thermal and turbulent kinetic energy of the CGM. Our model accounts for heating and turbulence driven by both supernova winds and cosmic accretion as well as radiative cooling, turbulence dissipation, and halo outflows due to CGM overpressurization. We demonstrate that, depending on parameters, the CGM can undergo a phase transition (“thermalization”) from a cool, turbulence-supported phase to a virial-temperature, thermally supported phase. This CGM phase transition is largely determined by the ability of radiative cooling to balance heating from supernova winds and turbulence dissipation. We perform an initial calibration of our model to the FIRE-2 cosmological hydrodynamical simulations and show that it can approximately reproduce the baryon cycles of the simulated halos. In particular, we find that, for these parameters, the phase transition occurs at high redshift in ultrafaint progenitors and at low redshift in classicalMvir∼ 1011Mdwarfs, while Milky Way–mass halos undergo the transition atz≈ 0.5. We see a similar transition in the simulations though it is more gradual, likely reflecting radial dependence and multiphase gas not captured by our model. We discuss these and other limitations of the model and possible future extensions.

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    Free, publicly-accessible full text available October 1, 2024

    We analyse a suite of 29 high-resolution zoom-in cosmological hydrodynamic simulations of massive galaxies with stellar masses $M_{\rm star} \gt 10^{10.9} \, \mathrm{M}_\odot$, with the goal of better understanding merger activity among active galactic nuclei (AGN), AGN activity in merging systems, SMBH growth during mergers, and the role of gas content in triggering AGN. Using the radiative transfer code Powderday, we generate HST-WFC3 F160W mock observations of central galaxies at redshift 0.5 < z < 3; convolve each image with a CANDELS-like point spread function; stitch each image into a real CANDELS image; and identify mergers within the synthetic images using commonly adopted non-parametric statistics. We study the connection between mergers and AGN activity in both the simulations and synthetic images and find reasonable agreement with observations from CANDELS. We find that AGN activity is not primarily driven by major mergers (stellar mass ratio > 1:4) except in a select few cases of gas-rich mergers at low redshifts (0.5 < z < 0.9). We also find that major mergers do not significantly grow the central SMBHs, indicating major mergers do not sustain long-term accretion. Moreover, the most luminous AGN in our simulations (Lbol > 1045 erg s−1) are no more likely than inactive galaxies (Lbol < 1043 erg s−1) to be found in merging systems. We conclude that mergers are not the primary drivers of AGN activity in the simulated massive galaxies studied here.

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  6. Abstract

    The inverse problem of extracting the stellar population content of galaxy spectra is analysed here from a basic standpoint based on information theory. By interpreting spectra as probability distribution functions, we find that galaxy spectra have high entropy, thus leading to a rather low effective information content. The highest variation in entropy is unsurprisingly found in regions that have been well studied for decades with the conventional approach. We target a set of six spectral regions that show the highest variation in entropy – the 4000 Å break being the most informative one. As a test case with real data, we measure the entropy of a set of high-quality spectra from the Sloan Digital Sky Survey, and contrast entropy-based results with the traditional method based on line strengths. The data are classified into star-forming (SF), quiescent (Q), and active galactic nucleus (AGN) galaxies, and show – independently of any physical model – that AGN spectra can be interpreted as a transition between SF and Q galaxies, with SF galaxies featuring a more diverse variation in entropy. The high level of entanglement complicates the determination of population parameters in a robust, unbiased way, and affects traditional methods that compare models with observations, as well as machine learning (especially deep learning) algorithms that rely on the statistical properties of the data to assess the variations among spectra. Entropy provides a new avenue to improve population synthesis models so that they give a more faithful representation of real galaxy spectra.

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  7. Abstract

    We explore the role of galactic feedback on the low-redshift Lyα(Lyα) forest (z≲ 2) statistics and its potential to alter the thermal state of the intergalactic medium. Using the Cosmology and Astrophysics with Machine Learning Simulations (CAMELS) suite, we explore variations of the AGN and stellar feedback models in the IllustrisTNG and Simba subgrid models. We find that both AGN and stellar feedback in Simba play a role in setting the Lyαforest column density distribution function (CDD) and the Doppler width (b-value) distribution. The Simba AGN jet feedback mode is able to efficiently transport energy out to the diffuse IGM, causing changes in the shape and normalization of the CDD and a broadening of theb-value distribution. We find that stellar feedback plays a prominent role in regulating supermassive black hole growth and feedback, highlighting the importance of constraining stellar and AGN feedback simultaneously. In IllustrisTNG, the AGN feedback variations explored in CAMELS do not affect the Lyαforest, but varying the stellar feedback model does produce subtle changes. Our results imply that the low-zLyαforest can be sensitive to changes in the ultraviolet background, stellar and black hole feedback, and that AGN jet feedback in particular can have a strong effect on the thermal state of the IGM.

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  8. Abstract

    Galactic outflows driven by supernovae (SNe) are thought to be a powerful regulator of a galaxy’s star-forming efficiency. Mass, energy, and metal outflows (ηM,ηE, andηZ, here normalized by the star formation rate, the SNe energy, and metal production rates, respectively) shape galaxy properties by both ejecting gas and metals out of the galaxy and by heating the circumgalactic medium (CGM), preventing future accretion. Traditionally, models have assumed that galaxies self-regulate by ejecting a large fraction of the gas, which enters the interstellar medium (ISM), although whether such high mass loadings agree with observations is still unclear. To better understand how the relative importance of ejective (i.e., high mass loading) versus preventative (i.e., high energy loading) feedback affects the present-day properties of galaxies, we develop a simple gas-regulator model of galaxy evolution, where the stellar mass, ISM, and CGM are modeled as distinct reservoirs which exchange mass, metals, and energy at different rates within a growing halo. Focusing on the halo mass range from 1010to 1012M, we demonstrate that, with reasonable parameter choices, we can reproduce the stellar-to-halo mass relation and the ISM-to-stellar mass relation with low-mass-loaded (ηM∼ 0.1–10) but high-energy-loaded (ηE∼ 0.1–1) winds, with self-regulation occurring primarily through heating and cooling of the CGM. We show that the model predictions are robust against changes to the mass loading of outflows but are quite sensitive to our choice of the energy loading, preferringηE∼ 1 for the lowest-mass halos and ∼0.1 for Milky Way–like halos.

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  9. Abstract

    The selection of high-redshift galaxies often involves spectral energy distribution (SED) fitting to photometric data, an expectation for contamination levels, and measurement of sample completeness—all vetted through comparison to spectroscopic redshift measurements of a sub-sample. The first JWST data are now being taken over several extragalactic fields to different depths and across various areas, which will be ideal for the discovery and classification of galaxies out to distances previously uncharted. As spectroscopic redshift measurements for sources in this epoch will not be initially available to compare with the first photometric measurements ofz> 8 galaxies, robust photometric redshifts are of the utmost importance. Galaxies atz> 8 are expected to have bluer rest-frame ultraviolet (UV) colors than typically used model SED templates, which could lead to catastrophic photometric redshift failures. We use a combination of BPASS andCloudymodels to create a supporting set of templates that match the predicted rest-UV colors ofz> 8 simulated galaxies. We test these new templates by fitting simulated galaxies in a mock catalog, Yung et al., which mimic expected field depths and areas of the JWST Cosmic Evolution Early Release Science Survey (m5σ∼ 28.6 over ∼100 arcmin2). We use EAZY to highlight the improvements in redshift recovery with the inclusion of our new template set and suggest criteria for selecting galaxies at 8 <z< 10 with the JWST, providing an important test case for observers venturing into this new era of astronomy.

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  10. 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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