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In recent years, cosmological hydrodynamical simulations have proven their utility as key interpretative tools in the study of galaxy formation and evolution. In this work, we present a comparative analysis of the baryon cycle in three publicly available, leading cosmological simulation suites: EAGLE, IllustrisTNG, and SIMBA. While these simulations broadly agree in terms of their predictions for the stellar mass content and star formation rates of galaxies at $z\approx 0$, they achieve this result for markedly different reasons. In EAGLE and SIMBA, we demonstrate that at low halo masses ($M_{\rm 200c}\lesssim 10^{11.5}\, \mathrm{M}_{\odot }$), stellar feedback (SF)-driven outflows can reach far beyond the scale of the halo, extending up to $2\!-\!3\times R_{\rm 200c}$. In contrast, in TNG, SF-driven outflows, while stronger at the scale of the interstellar medium, recycle within the circumgalactic medium (within $R_{\rm 200c}$). We find that active galactic nucleus (AGN)-driven outflows in SIMBA are notably potent, reaching several times $R_{\rm 200c}$ even at halo masses up to $M_{\rm 200c}\approx 10^{13.5}\, \mathrm{M}_{\odot }$. In both TNG and EAGLE, AGN feedback can eject gas beyond $R_{\rm 200c}$ at this mass scale, but seldom beyond $2\!-\!3\times R_{\rm 200c}$. We find that the scale of feedback-driven outflows can be directly linked with the prevention of cosmological inflow, as well as the total baryon fraction of haloes within $R_{\rm 200c}$. This work lays the foundation to develop targeted observational tests that can discriminate between feedback scenarios, and inform subgrid feedback models in the next generation of simulations.

We present a new suite of numerical simulations of the star-forming interstellar medium (ISM) in galactic disks using the TIGRESS-NCR framework. Distinctive aspects of our simulation suite are (1) sophisticated and comprehensive numerical treatments of essential physical processes including magnetohydrodynamics, self-gravity, and galactic differential rotation, as well as photochemistry, cooling, and heating coupled with direct ray-tracing UV radiation transfer and resolved supernova feedback and (2) wide parameter coverage including the variation in metallicity over$Z\prime \equiv Z/Z_{\odot }\sim 0.1-3$, gas surface density Σ_gas∼ 5–150M_⊙pc⁻², and stellar surface density Σ_star∼ 1–50M_⊙pc⁻². The range of emergent star formation rate surface density is Σ_SFR∼ 10⁻⁴–0.5M_⊙kpc⁻²yr⁻¹, and ISM total midplane pressure isP_tot/k_B= 10³–10⁶cm⁻³K, withP_totequal to the ISM weight$\mathcal{W}$. For given Σ_gasand Σ_star, we find${\mathrm{\Sigma }}_{\mathrm{SFR}}\propto Z{\prime }^{0.3}$. We provide an interpretation based on the pressure-regulated feedback-modulated (PRFM) star formation theory. The total midplane pressure consists of thermal, turbulent, and magnetic stresses. We characterize feedback modulation in terms of the yield ϒ, defined as the ratio of each stress to Σ_SFR. The thermal feedback yield varies sensitively with both weight and metallicity as${\mathrm{\Upsilon }}_{\mathrm{th}}\propto {\mathcal{W}}^{-0.46}Z{\prime }^{-0.53}$, while the combined turbulent and magnetic feedback yield shows weaker dependence${\mathrm{\Upsilon }}_{\mathrm{turb}+\mathrm{mag}}\propto {\mathcal{W}}^{-0.22}Z{\prime }^{-0.18}$. The reduction in Σ_SFRat low metallicity is due mainly to enhanced thermal feedback yield, resulting from reduced attenuation of UV radiation. With the metallicity-dependent calibrations we provide, PRFM theory can be used for a new subgrid star formation prescription in cosmological simulations where the ISM is unresolved.

The observed rest-UV luminosity function at cosmic dawn (z∼ 8–14) measured by JWST revealed an excess of UV-luminous galaxies relative to many prelaunch theoretical predictions. A high star formation efficiency (SFE) and a top-heavy initial mass function (IMF) are among the mechanisms proposed for explaining this excess. Although a top-heavy IMF has been proposed for its ability to increase the light-to-mass ratio (Ψ_UV), the resulting enhanced radiative pressure from young stars could decrease the SFE, potentially driving galaxy luminosities back down. In this Letter, we use idealized radiation hydrodynamic simulations of star cluster formation to explore the effects of a top-heavy IMF on the SFE of clouds typical of the high-pressure conditions found at these redshifts. We find that the SFE in star clusters with solar-neighborhood-like dust abundance decreases with increasingly top-heavy IMFs—by ∼20% for an increase of a factor of 4 in Ψ_UVand by 50% for a factor of ∼10 in Ψ_UV. However, we find that an expected decrease in the dust-to-gas ratio (∼0.01 × solar) at these redshifts can completely compensate for the enhanced light output. This leads to a (cloud-scale; ∼10 pc) SFE that is ≳70% even for a factor of 10 increase in Ψ_UV, implying that highly efficient star formation is unavoidable for high surface density and low-metallicity conditions. Our results suggest that a top-heavy IMF, if present, likely coexists with efficient star formation in these galaxies.

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.

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.

‘Runaway stars’ might play a role in driving galactic outflows and enriching the circumgalactic medium with metals. To study this effect, we carry out high-resolution dwarf galaxy simulations that include velocity ‘kicks’ to massive stars above eigth solar masses. We consider two scenarios, one that adopts a power law velocity distribution for kick velocities, resulting in more stars with high-velocity kicks, and a more moderate scenario with a Maxwellian velocity distribution. We explicitly resolve the multiphase interstellar medium (ISM) and include non-equilibrium cooling and chemistry. We sample individual massive stars from an IMF and follow their radiation input and SN feedback (core-collapse) channel at the end of their lifetime. In the simulations with runaway stars, we add additional (natal) velocity kicks that mimic two- and three-body interactions that cannot be fully resolved in our simulations. We find that including runaway or ‘walkaway’ star scenarios impacts mass, metal, momentum, and energy outflows as well as the corresponding loading factors. The effect on the mass loading factor is small, but we find an increase in the metal loading by a factor of 1.5 to 2. The momentum loading increases by a factor of 1.5–2. The energy loading increases by roughly a factor of 5 when runaway stars are included. Additionally, we find that the overall level of star formation is increased in the models that include runaway stars. We conclude that the inclusion of runaway stars could have an impact on the global star formation and subsequent outflow properties of dwarf galaxies.

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 classicalM_vir∼ 10¹¹M_⊙dwarfs, 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.

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.

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.

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 (η_M,η_E, andη_Z, 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 (η_M∼ 0.1–10) but high-energy-loaded (η_E∼ 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, preferringη_E∼ 1 for the lowest-mass halos and ∼0.1 for Milky Way–like halos.