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Rachel S. Somerville

Publications and source records attributed to Rachel S. Somerville.

At least 145 records · Page 8Linked to original sources

On the Stellar Populations of Galaxies at z=9-11: The Growth of Metals and Stellar Mass at Early Times

We present a detailed stellar population analysis of 11 bright ($H<26.6$) galaxies at $z=9-11$ (three spectroscopically confirmed) to constrain the chemical enrichment and growth of stellar mass of early galaxies. We use the flexible Bayesian spectral energy distribution (SED) fitting code Prospector with a range of star-formation histories (SFHs), a flexible dust attenuation law and a self-consistent modeling of emission lines. This approach allows us to assess how different priors affect our results, and how well we can break degeneracies between dust attenuation, stellar ages, metallicity and emission lines using data which probe only the rest-frame ultraviolet to optical wavelengths. We measure a median observed ultraviolet spectral slope $β=-1.87_{-0.43}^{+0.35}$ for relatively massive star-forming galaxies ($9<\log(M_{\star}/M_{\odot})<10$), consistent with no change from $z=4$ to $z=9-10$ at these stellar masses, implying rapid enrichment. Our SED-fitting results are consistent with a star-forming main sequence with sub-linear slope ($0.7\pm0.2$) and specific star-formation rates of $3-10~\mathrm{Gyr}^{-1}$. However, the stellar ages and SFHs are less well constrained. Using different SFH priors, we cannot distinguish between median mass-weighted ages of $\sim50-150$ Myr, which corresponds to 50\% formation redshifts of $z_{50}\sim10-12$ at $z\sim9$ and is of the order of the dynamical timescales of these systems. Importantly, the models with different SFH priors are able to fit the data equally well. We conclude that the current observational data cannot tightly constrain the mass-buildup timescales of these $z=9-11$ galaxies, with our results consistent with SFHs implying both a shallow and steep increase of the cosmic SFR density with time at $z>10$.

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LADUMA: Discovery of a luminous OH megamaser at $z > 0.5$

In the local Universe, OH megamasers (OHMs) are detected almost exclusively in infrared-luminous galaxies, with a prevalence that increases with IR luminosity, suggesting that they trace gas-rich galaxy mergers. Given the proximity of the rest frequencies of OH and the hyperfine transition of neutral atomic hydrogen (HI), radio surveys to probe the cosmic evolution of HI in galaxies also offer exciting prospects for exploiting OHMs to probe the cosmic history of gas-rich mergers. Using observations for the Looking At the Distant Universe with the MeerKAT Array (LADUMA) deep HI survey, we report the first untargeted detection of an OHM at $z > 0.5$, LADUMA J033046.20$-$275518.1 (nicknamed "Nkalakatha"). The host system, WISEA J033046.26$-$275518.3, is an infrared-luminous radio galaxy whose optical redshift $z \approx 0.52$ confirms the MeerKAT emission line detection as OH at a redshift $z_{\rm OH} = 0.5225 \pm 0.0001$ rather than HI at lower redshift. The detected spectral line has 18.4$σ$ peak significance, a width of $459 \pm 59\,{\rm km\,s^{-1}}$, and an integrated luminosity of $(6.31 \pm 0.18\,{\rm [statistical]}\,\pm 0.31\,{\rm [systematic]}) \times 10^3\,L_\odot$, placing it among the most luminous OHMs known. The galaxy's far-infrared luminosity $L_{\rm FIR} = (1.576 \pm 0.013) \times 10^{12}\,L_\odot$ marks it as an ultra-luminous infrared galaxy; its ratio of OH and infrared luminosities is similar to those for lower-redshift OHMs. A comparison between optical and OH redshifts offers a slight indication of an OH outflow. This detection represents the first step towards a systematic exploitation of OHMs as a tracer of galaxy growth at high redshifts.

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The Metallicity Distribution Function in Outer Halo Fields of Simulated Elliptical Galaxies Compared to Observations of NGC 5128

Stellar metallicity distribution functions (MDF) have been measured for resolved stellar populations in the outer halos of many galaxies in nearby groups. Among them, the MDF of NGC 5128, the central giant elliptical in the Centaurus group, provides essential constraints for theories of massive galaxy formation and hierarchical assembly. To investigate the formation and chemical evolution history of the outer halo of giant elliptical galaxies, we examine the chemical properties of three zoom-in high resolution cosmological hydrodynamical simulations of an NGC 5128-like giant elliptical galaxy and compare their outer halo MDFs to the observed one of NGC 5128. Even though the simulated galaxies have different merging histories and age distributions, all predicted MDFs are in good qualitative agreement with the observed one. The median metallicity of the simulated galaxies is on average $\rm [M/H]=-0.41 \pm 0.06$ compared to the observed value of $\rm [M/H]=-0.38 \pm 0.02$ for NGC 5128, and the dispersion in metallicity is $\sim 0.77$ dex for both observed and simulated galaxies. We investigate the origin of the stars ending up in the outer halo field of simulated galaxies and show that most have an `accreted' origin, formed in other small galaxies and later accreted in mergers. Only $\sim 15$ percent of the stars are formed `in situ' within the main progenitor of galaxy and radially migrate outwards. We show that the contribution of metal-rich in situ stars is sub-dominant in the outer halos of our simulated galaxies, but can be prominent in the inner regions.

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An empirical representation of a physical model for the ISM [CII], CO, and [CI] emission at redshift $1\leq z\leq9$

Sub-millimeter emission lines produced by the interstellar medium (ISM) are strong tracers of star formation and are some of the main targets of line intensity mapping (LIM) surveys. In this work we present an empirical multi-line emission model that simultaneously covers the mean, scatter, and correlations of [CII], CO J=1-0 to J=5-4, and [CI] lines in redshift range $1\leq z\leq9$. We assume the galaxy ISM line emission luminosity versus halo mass relations can be described by double power laws with redshift-dependent log normal scatter. The model parameters are then derived by fitting to the state of the art semi-analytic simulation results that have successfully reproduced multiple sub-millimeter line observations at $0\leq z\lesssim6$. We cross check the line emission statistics predicted by the semi-analytic simulation and our empirical model, finding that at $z\geq1$ our model reproduces the simulated line intensities with fractional error less than about 10%. The fractional difference is less than 25% for the power spectra. Grounded on physically-motivated and self-consistent galaxy simulations, this computationally efficient model will be helpful in forecasting ISM emission line statistics for upcoming LIM surveys.

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Galaxy Correlation Function and Local Density from Photometric Redshifts Using the Stochastic Order Redshift Technique (SORT)

The stochastic order redshift technique (SORT) is a simple, efficient, and robust method to improve cosmological redshift measurements. The method relies upon having a small ($\sim$10 per cent) reference sample of high-quality redshifts. Within pencil-beam-like sub-volumes surrounding each galaxy, we use the precise dN/d$z$ distribution of the reference sample to recover new redshifts and assign them one-to-one to galaxies such that the original rank order of redshifts is preserved. Preserving the rank order is motivated by the fact that random variables drawn from Gaussian probability density functions with different means but equal standard deviations satisfy stochastic ordering. The process is repeated for sub-volumes surrounding each galaxy in the survey. This results in every galaxy with an uncertain redshift being assigned multiple "recovered" redshifts from which a new redshift estimate can be determined. An earlier paper applied SORT to a mock Sloan Digital Sky Survey at $z \lesssim$ 0.2 and accurately recovered the two-point correlation function on scales $\gtrsim$4 $h^{-1}$Mpc. In this paper, we test the performance of SORT in surveys spanning the redshift range 0.75$<z<$2.25. We used two mock surveys extracted from the Small MultiDark-Planck and Bolshoi-Planck N-body simulations with dark matter haloes that were populated by the Santa Cruz semi-analytic model. We find that SORT is able to improve redshift estimates and recover distinctive large-scale features of the cosmic web. Further, it provides unbiased estimates of the redshift-space two-point correlation function $ξ(s)$ on scales $\gtrsim$2.5 $h^{-1}$Mpc, as well as local densities in regions of average or higher density. This may allow improved understanding of how galaxy properties relate to their local environments.

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Breaking baryon-cosmology degeneracy with the electron density power spectrum

Uncertain feedback processes in galaxies affect the distribution of matter, currently limiting the power of weak lensing surveys. If we can identify cosmological statistics that are robust against these uncertainties, or constrain these effects by other means, then we can enhance the power of current and upcoming observations from weak lensing surveys such as DES, Euclid, the Rubin Observatory, and the Roman Space Telescope. In this work, we investigate the potential of the electron density auto-power spectrum as a robust probe of cosmology and baryonic feedback. We use a suite of (magneto-)hydrodynamic simulations from the CAMELS project and perform an idealized analysis to forecast statistical uncertainties on a limited set of cosmological and physically-motivated astrophysical parameters. We find that the electron number density auto-correlation, measurable through either kinematic Sunyaev-Zel'dovich observations or through Fast Radio Burst dispersion measures, provides tight constraints on $Ω_{m}$ and the mean baryon fraction in intermediate-mass halos, $\bar{f}_{\mathrm{bar}}$. By obtaining an empirical measure for the associated systematic uncertainties, we find these constraints to be largely robust to differences in baryonic feedback models implemented in hydrodynamic simulations. We further discuss the main caveats associated with our analysis, and point out possible directions for future work.

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The CAMELS project: public data release

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 4,233 cosmological simulations, 2,049 N-body and 2,184 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 catalogues, power spectra, bispectra, Lyman-$α$ spectra, probability distribution functions, halo radial profiles, and X-rays photon lists. We also release over one thousand catalogues that contain billions of galaxies from CAMELS-SAM: a large collection of N-body simulations that have been combined with the Santa Cruz Semi-Analytic 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 \url{https://camels.readthedocs.io}.

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A Census of the Bright z=8.5-11 Universe with the Hubble and Spitzer Space Telescopes in the CANDELS Fields

We present the results from a new search for candidate galaxies at z ~ 8.5-11 discovered over the 850 arcmin^2 area probed by the Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey (CANDELS). We use a photometric redshift selection including both Hubble and Spitzer Space Telescope photometry to robustly identify galaxies in this epoch at F160W < 26.6. We use a detailed vetting procedure, including screening for persistence, stellar contamination, inclusion of ground-based imaging, and followup space-based imaging to build a robust sample of 11 candidate galaxies, three presented here for the first time. The inclusion of Spitzer/IRAC photometry in the selection process reduces contamination, and yields more robust redshift estimates than Hubble alone. We constrain the evolution of the rest-frame ultraviolet luminosity function via a new method of calculating the observed number densities without choosing a prior magnitude bin size. We find that the abundance at our brightest probed luminosities (M_UV=-22.3) is consistent with predictions from simulations which assume that galaxies in this epoch have gas depletion times at least as short as those in nearby starburst galaxies. Due to large Poisson and cosmic variance uncertainties we cannot conclusively rule out either a smooth evolution of the luminosity function continued from z=4-8, or an accelerate decline at z > 8. We calculate that the presence of seven galaxies in a single field (EGS) is an outlier at the 2-sigma significance level, implying the discovery of a significant overdensity. These scenarios will be imminently testable to high confidence within the first year of observations of the James Webb Space Telescope.

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Supermassive black holes in cosmological simulations II: the AGN population and predictions for upcoming X-ray missions

In large-scale hydrodynamical cosmological simulations, the fate of massive galaxies is mainly dictated by the modeling of feedback from active galactic nuclei (AGN). The amount of energy released by AGN feedback is proportional to the mass that has been accreted onto the BHs, but the exact sub-grid modeling of AGN feedback differs in all simulations. Whilst modern simulations reliably produce populations of quiescent massive galaxies at z<2, it is also crucial to assess the similarities and differences of the responsible AGN populations. Here, we compare the AGN population of the Illustris, TNG100, TNG300, Horizon-AGN, EAGLE, and SIMBA simulations. The AGN luminosity function (LF) varies significantly between simulations. Although in agreement with current observational constraints at z=0, at higher redshift the agreement of the LFs deteriorates with most simulations producing too many AGN of L_{x, 2-10 keV}~10^43-10^44 erg/s. AGN feedback in some simulations prevents the existence of any bright AGN with L_{x, 2-10 keV}>=10^45 erg/s (although this is sensitive to AGN variability), and leads to smaller fractions of AGN in massive galaxies than in the observations at z<=2. We find that all the simulations fail at producing a number density of AGN in good agreement with observational constraints for both luminous (L_{x, 2-10 keV}~10^43-10^45 erg/s) and fainter (L_{x, 2-10 keV}~10^42-10^43 erg/s) AGN, and at both low and high redshift. These differences can aid us in improving future BH and galaxy subgrid modeling in simulations. Upcoming X-ray missions (e.g., Athena, AXIS, and LynX) will bring faint AGN to light and new powerful constraints. After accounting for AGN obscuration, we find that the predicted number density of detectable AGN in future surveys spans at least one order of magnitude across the simulations, at any redshift.

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Supermassive black holes in cosmological simulations I: M_BH-M_star relation and black hole mass function

The past decade has seen significant progress in understanding galaxy formation and evolution using large-scale cosmological simulations. While these simulations produce galaxies in overall good agreement with observations, they employ different sub-grid models for galaxies and supermassive black holes (BHs). We investigate the impact of the sub-grid models on the BH mass properties of the Illustris, TNG100, TNG300, Horizon-AGN, EAGLE, and SIMBA simulations, focusing on the M_BH-M_star relation and the BH mass function. All simulations predict tight M_BH-M_star relations, and struggle to produce the lowest (M_BH< 10^7.5 Msun) in galaxies of M_star~10^10.5-10^11.5 Msun. While the time evolution of the mean M_BH-M_star relation is mild (<1 dex in BH mass for 0 10^9 Msun in most of the simulations. The BH mass function is dominated by efficiently accreting BHs (log10 f_Edd >-2$) at high redshifts, and transitions progressively from the high-mass to the low-mass end to be governed by inactive BHs. The transition time and the contribution of active BHs are different among the simulations, and can be used to evaluate models against observations.

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Semi-analytic forecasts for JWST -- V. AGN luminosity functions and helium reionization at z = 2-7

Active galactic nuclei (AGN) forming in the early universe are thought to be the primary source of hard ionizing photons contributing to the reionization of intergalactic helium. However, the number density and spectral properties of high-redshift AGN remain largely unconstrained. In this work, we make use of physically-informed models calibrated with a wide variety of available observations to provide estimates for the role of AGN throughout the Epoch of Reionization. We present AGN luminosity functions in various bands between z = 2 to 7 predicted by the well-established Santa Cruz semi-analytic model, which includes modelling of black hole accretion and AGN feedback. We then combine the predicted AGN populations with a physical spectral model for self-consistent estimates of ionizing photon production rates, which depend on the mass and accretion rate of the accreting supermassive black hole. We then couple the predicted comoving ionizing emissivity with an analytic model to compute the subsequent reionization history of intergalactic helium and hydrogen. This work demonstrates the potential of coupling physically motivated analytic or semi-analytic techniques to capture multi-scale physical processes across a vast range of scales (here, from AGN accretion disks to cosmological scales). Our physical model predicts an intrinsic ionizing photon budget well above many of the estimates in the literature, meaning that helium reionization can comfortably be accomplished even with a relatively low escape fraction. We also make predictions for the AGN populations that are expected to be detected in future \emph{James Webb Space Telescope} surveys.

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Black Hole Growth and Feedback in Isolated Romulus25 Dwarf Galaxies

We investigate the effects of massive black hole growth on the structural evolution of dwarf galaxies within the Romulus25 cosmological hydrodynamical simulation. We study a sample of 228 central, isolated dwarf galaxies with stellar masses $M_{star} < 10^{10} M_\odot$ and a central BH. We find that the local $M_{BH} - M_{star}$ relation exhibits a high degree of scatter below $M_{star} < 10^{10} M_\odot$, which we use to classify BHs as overmassive or undermassive relative to their host $M_{star}$. Overmassive BHs grow through a mixture of BH mergers and relatively high average accretion rates, while undermassive BHs grow slowly through accretion. We find that isolated dwarf galaxies that host overmassive BHs also follow different evolutionary tracks relative to their undermassive BH counterparts, building up their stars and dark matter earlier and experiencing star formation suppression starting around $z=2$. By $z=0.05$, overmassive BH hosts above $M_{star} > 10^{9} M_\odot$ are more likely to exhibit lower central stellar mass density, lower HI gas content, and lower star formation rates than their undermassive BH counterparts. Our results suggest that overmassive BHs in isolated galaxies above $M_{star} > 10^{9} M_\odot$ are capable of driving feedback, in many cases suppressing and even quenching star formation by late times.

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The CAMELS Multifield Dataset: Learning the Universe's Fundamental Parameters with Artificial Intelligence

We present the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) Multifield Dataset, CMD, a collection of hundreds of thousands of 2D maps and 3D grids containing many different properties of cosmic gas, dark matter, and stars from 2,000 distinct simulated universes at several cosmic times. The 2D maps and 3D grids represent cosmic regions that span $\sim$100 million light years and have been generated from thousands of state-of-the-art hydrodynamic and gravity-only N-body simulations from the CAMELS project. Designed to train machine learning models, CMD is the largest dataset of its kind containing more than 70 Terabytes of data. In this paper we describe CMD in detail and outline a few of its applications. We focus our attention on one such task, parameter inference, formulating the problems we face as a challenge to the community. We release all data and provide further technical details at https://camels-multifield-dataset.readthedocs.io.

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Characterizing mass, momentum, energy and metal outflow rates of multi-phase galactic winds in the FIRE-2 cosmological simulations

We characterize mass, momentum, energy and metal outflow rates of multi-phase galactic winds in a suite of FIRE-2 cosmological "zoom-in" simulations from the Feedback in Realistic Environments (FIRE) project. We analyze simulations of low-mass dwarfs, intermediate-mass dwarfs, Milky Way-mass halos, and high-redshift massive halos. Consistent with previous work, we find that dwarfs eject about 100 times more gas from their interstellar medium (ISM) than they form in stars, while this mass "loading factor" drops below one in massive galaxies. Most of the mass is carried by the hot phase ($>10^5$ K) in massive halos and the warm phase ($10^3-10^5$ K) in dwarfs; cold outflows ($<10^3$ K) are negligible except in high-redshift dwarfs. Energy, momentum and metal loading factors from the ISM are of order unity in dwarfs and significantly lower in more massive halos. Hot outflows have $2-5\times$ higher specific energy than needed to escape from the gravitational potential of dwarf halos; indeed, in dwarfs, the mass, momentum, and metal outflow rates increase with radius whereas energy is roughly conserved, indicating swept up halo gas. Burst-averaged mass loading factors tend to be larger during more powerful star formation episodes and when the inner halo is not virialized, but we see effectively no trend with the dense ISM gas fraction. We discuss how our results can guide future controlled numerical experiments that aim to elucidate the key parameters governing galactic winds and the resulting associated preventative feedback.

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Efficient early stellar feedback can suppress galactic outflows by reducing supernova clustering

We present a novel set of stellar feedback models, implemented in the moving-mesh code Arepo, designed for galaxy formation simulations with near-parsec (or better) resolution. These include explicit sampling of stars from the IMF, allowing feedback to be linked to individual massive stars, an improved method for the modelling of H II regions, photoelectric heating from a spatially varying FUV field and supernova feedback. We perform a suite of 32 simulations of isolated $M_\mathrm{vir} = 10^{10}\,\mathrm{M_\odot}$ galaxies with a baryonic mass resolution of $20\,\mathrm{M_\odot}$ in order to study the non-linear coupling of the different feedback channels. We find that photoionization and supernova feedback are both independently capable of regulating star formation to the same level, while photoelectric heating is inefficient. Photoionization produces a considerably smoother star formation history than supernovae. When all feedback channels are combined, the additional suppression of star formation rates is minor. However, outflow rates are substantially reduced relative to the supernova only simulations. We show that this is directly caused by a suppression of supernova clustering by the photoionization feedback, disrupting star forming clouds prior to the first supernovae. We demonstrate that our results are robust to variations of our star formation prescription, feedback models and the gas fraction of the disk. Our results also imply that the burstiness of star formation and the mass loading of outflows may be overestimated if the adopted star particle mass is considerably larger than the mass of individual stars because this imposes a minimum cluster size.

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The CAMELS project: Cosmology and Astrophysics with MachinE Learning Simulations

We present the Cosmology and Astrophysics with MachinE Learning Simulations --CAMELS-- project. CAMELS is a suite of 4,233 cosmological simulations of $(25~h^{-1}{\rm Mpc})^3$ volume each: 2,184 state-of-the-art (magneto-)hydrodynamic simulations run with the AREPO and GIZMO codes, employing the same baryonic subgrid physics as the IllustrisTNG and SIMBA simulations, and 2,049 N-body simulations. The goal of the CAMELS project is to provide theory predictions for different observables as a function of cosmology and astrophysics, and it is the largest suite of cosmological (magneto-)hydrodynamic simulations designed to train machine learning algorithms. CAMELS contains thousands of different cosmological and astrophysical models by way of varying $Ω_m$, $σ_8$, and four parameters controlling stellar and AGN feedback, following the evolution of more than 100 billion particles and fluid elements over a combined volume of $(400~h^{-1}{\rm Mpc})^3$. We describe the simulations in detail and characterize the large range of conditions represented in terms of the matter power spectrum, cosmic star formation rate density, galaxy stellar mass function, halo baryon fractions, and several galaxy scaling relations. We show that the IllustrisTNG and SIMBA suites produce roughly similar distributions of galaxy properties over the full parameter space but significantly different halo baryon fractions and baryonic effects on the matter power spectrum. This emphasizes the need for marginalizing over baryonic effects to extract the maximum amount of information from cosmological surveys. We illustrate the unique potential of CAMELS using several machine learning applications, including non-linear interpolation, parameter estimation, symbolic regression, data generation with Generative Adversarial Networks (GANs), dimensionality reduction, and anomaly detection.

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Galaxy assembly bias and large-scale distribution: a comparison between IllustrisTNG and a semi-analytic model

In this work, we compare large scale structure observables for stellar mass selected samples at $z=0$, as predicted by two galaxy models, the hydrodynamical simulation IllustrisTNG and the Santa-Cruz semi-analytic model (SC-SAM). Although both models have been independently calibrated to match observations, rather than each other, we find good agreement between the two models for two-point clustering and galaxy assembly bias signatures. The models also show a qualitatively similar response of occupancy and clustering to secondary halo paramaters other than mass, such as formation history and concentration, although with some quantitative differences. Thus, our results demonstrate that the galaxy-halo relationships in SC-SAM and TNG are quite similar to first order. However, we also find areas in which the models differ. For example, we note a strong correlation between halo gas content and environment in TNG, which is lacking in the SC-SAM, as well as differences in the occupancy predictions for low-mass haloes. Moreover, we show that higher-order statistics, such as cumulants of the density field, help to accurately describe the galaxy distribution and discriminate between models that show degenerate behavior for two-point statistics. Our results suggest that SAMs are a promising cost-effective and intuitive method for generating mock catalogues for next generation cosmological surveys.

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Exploring the Milky Way Circumgalactic Medium in a Cosmological Context with a Semi-Analytic Model

We combine the Santa-Cruz Semi-Analytic Model (SAM) for galaxy formation and evolution with the circumgalactic medium (CGM) model presented in Faerman et al. (2020) to explore the CGM properties of $L^{*}$ galaxies. We use the SAM to generate a sample of galaxies with halo masses similar to the Milky Way (MW) halo, $M_{\rm vir} \approx 10^{12}~{\rm M_{sun}}$, and find that the CGM mass and mean metallicity in the sample are correlated. We use the CGM masses and metallicities of the SAM galaxies as inputs for the FSM20 model, and vary the amount of non-thermal support. The density profiles in our models can be approximated by power-law functions with slopes in the range of $0.75 < a_n < 1.25$, with higher non-thermal pressure resulting in flatter distributions. We explore how the gas pressure, dispersion measure, OVI-OVIII column densities, and cooling rates behave with the gas distribution and total mass. We show that for CGM masses below $\sim 3 \times 10^{10}~{\rm M_{sun}}$, photoionization has a significant effect on the column densities of OVI and OVIII. The combination of different MW CGM observations favors models with similar fractions in thermal pressure, magnetic fields/cosmic rays, and turbulent support, and with $M_{\rm gas} \sim 3-10 \times 10^{10}~{\rm M_{sun}}$. The MW OVI column requires $t_{\rm cool}/t_{\rm dyn} \sim 4$, independent of the gas distribution. The AGN jet-driven heating rates in the SAM are enough to offset the CGM cooling, although exact balance is not required in star-forming galaxies. We provide predictions for the columns densities of additional metal ions - NV, NeVIII, and MgX.

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