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We analyze measurements of the thermal Sunyaev–Zeldovich (tSZ) effect arising in the circumgalactic medium (CGM) ofL* galaxies, reported by J. N. Bregman et al. (B+22) and S. Das et al. (D+23). In our analysis, we use the Y. Faerman et al. CGM models, a new power-law model (PLM), and the TNG100 simulation. For a givenM_vir, our PLM has four parameters: the fraction,f_hCGM, of the halo baryon mass in hot CGM gas, the ratio,ϕ_T, of the actual gas temperature at the virial radius to the virial temperature, and the power-law indices,a_P,thanda_nfor the thermal electron pressure and the hydrogen nucleon density. The B+22 Compton-yprofile implies steep electron pressure slopes (a_P,th≃ 2). For isothermal conditions, the temperature is at least 1.1 × 10⁶K, with a hot CGM gas mass of up to 3.5 × 10¹¹M_⊙for a virial mass of 2.75 × 10¹²M_⊙. However, if isothermal, the gas must be expanding out of the halos. An isentropic equation of state is favored for which hydrostatic equilibrium is possible. The B+22 and D+23 results are consistent with each other and with recent (0.5–2 keV) CGM X-ray observations of Milky Way mass systems. ForM_vir≃ 3 × 10¹²M_⊙, the scaled Compton pressure integrals,$E{(z)}^{-2/3}{Y}_{500}/M_{\mathrm{vir},12}^{5/3}$, lie in the narrow range, 2.5 × 10⁻⁴–5.0 × 10⁻⁴kpc², for all three sets of observations. TNG100 underpredicts the tSZ parameters by factors ∼0.5 dex for theL* galaxies, suggesting that the feedback strengths and CGM gas losses are overestimated in the simulated halos at these mass scales.

Semianalytic models (SAMs) systematically predict higher-stellar mass scatter at a given halo mass than hydrodynamical simulations and most empirical models. Our goal is to investigate the physical origin of this scatter by exploring modifications to the physics in the SAMDark Sage. We design two black hole formation models that approximate results from theIllustrisTNG 300-1hydrodynamical simulation. In the first model, we assign a fixed black hole mass of 10⁶M_⊙to every halo that reaches 10^10.5M_⊙. In the second model, we disregard any black hole growth as implemented in the standardDark Sagemodel. Instead, we force all black hole masses to follow the medianz= 0 black hole mass–halo mass relation inIllustrisTNG 300-1with an imposed fixed scatter. We find that each model on its own does not significantly reduce the scatter in stellar mass. To explore the effects of active galactic nucleus (AGN) feedback in addition to black hole seeding, we replace the native Dark Sage AGN feedback model with a simple model where we turn off cooling for galaxies with black hole masses above 10⁸M_⊙. With the additional modification in AGN feedback, we find that the supermassive black hole seeding and fixed conditional distribution models create a significant reduction in the scatter in stellar mass at halo masses between 10^11–14M_⊙. These results suggest that AGN feedback in SAMs acts in a qualitatively different way than feedback implemented in cosmological simulations. Either or both may require substantial modification to match the empirically inferred scatter in the stellar mass–halo mass relation.

The presence of dense, neutral hydrogen clouds in the hot, diffuse intragroup and intracluster (IC) medium is an important clue to the physical processes controlling the survival of cold gas and sheds light on cosmological baryon flows in massive halos. Advances in numerical modeling and observational surveys mean that theory and observational comparisons are now possible. In this paper, we use the high-resolution TNG50 cosmological simulation to study the Hidistribution in seven halos with masses similar to the Fornax galaxy cluster. Adopting observational sensitivities similar to the MeerKAT Fornax Survey (MFS), an ongoing Hisurvey that will probe to column densities of 10¹⁸cm⁻², we find that Fornax-like TNG50 halos have an extended distribution of neutral hydrogen clouds. Within 1R_vir, we predict the MFS will observe a total Hicovering fraction of ∼12% (mean value) for 10 kpc pixels and 6% for 2 kpc pixels. If we restrict this to gas more than 10 half-mass radii from galaxies, the mean values only decrease mildly, to 10% (4%) for 10 (2) kpc pixels (albeit with significant halo-to-halo spread). Although there are large amounts of Hioutside of galaxies, the gas seems to be associated with satellites, judging both by the visual inspection of projections and by comparison of the line of sight velocities of galaxies and IC Hi.

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.

Traditional star formation subgrid models implemented in cosmological galaxy formation simulations, such as that of V. Springel & L. Hernquist (hereafter SH03), employ adjustable parameters to satisfy constraints measured in the local Universe. In recent years, however, theory and spatially resolved simulations of the turbulent, multiphase, star-forming interstellar medium (ISM) have begun to produce new first-principles models, which when fully developed can replace traditional subgrid prescriptions. This approach has advantages of being physically motivated and predictive rather than empirically tuned, and allowing for varying environmental conditions rather than being tied to local-Universe conditions. As a prototype of this new approach, by combining calibrations from the TIGRESS numerical framework with the pressure-regulated feedback-modulated (PRFM) theory, simple formulae can be obtained for both the gas depletion time and an effective equation of state. Considering galaxies in TNG50, we compare the “native” simulation outputs with postprocessed predictions from PRFM. At TNG50 resolution, the total midplane pressure is nearly equal to the total ISM weight, indicating that galaxies in TNG50 are close to satisfying vertical equilibrium. The measured gas scale height is also close to theoretical equilibrium predictions. The slopes of the effective equations of states are similar, but with effective velocity dispersion normalization from SH03 slightly larger than that from current TIGRESS simulations. Because of this and the decrease in PRFM feedback yield at high pressure, the PRFM model predicts shorter gas depletion times than the SH03 model at high densities and redshift. Our results represent a first step toward implementing new, numerically calibrated subgrid algorithms in cosmological galaxy formation simulations.

Galaxy formation models within cosmological hydrodynamical simulations contain numerous parameters with nontrivial influences over the resulting properties of simulated cosmic structures and galaxy populations. It is computationally challenging to sample these high dimensional parameter spaces with simulations, in particular for halos in the high-mass end of the mass function. In this work, we develop a novel sampling and reduced variance regression method,CARPoolGP, which leverages built-in correlations between samples in different locations of high dimensional parameter spaces to provide an efficient way to explore parameter space and generate low-variance emulations of summary statistics. We use this method to extend the Cosmology and Astrophysics with machinE Learning Simulations to include a set of 768 zoom-in simulations of halos in the mass range of 10¹³–10^14.5M_⊙h⁻¹that span a 28-dimensional parameter space in the IllustrisTNG model. With these simulations and the CARPoolGP emulation method, we explore parameter trends in the ComptonY–M, black hole mass–halo mass, and metallicity–mass relations, as well as thermodynamic profiles and quenched fractions of satellite galaxies. We use these emulations to provide a physical picture of the complex interplay between supernova and active galactic nuclei feedback. We then use emulations of theY–Mrelation of massive halos to perform Fisher forecasts on astrophysical parameters for future Sunyaev–Zeldovich observations and find a significant improvement in forecasted constraints. We publicly release both the simulation suite and CARPoolGP software package.

We quantify the cosmological spread of baryons relative to their initial neighbouring dark matter distribution using thousands of state-of-the-art simulations from the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project. We show that dark matter particles spread relative to their initial neighbouring distribution owing to chaotic gravitational dynamics on spatial scales comparable to their host dark matter halo. In contrast, gas in hydrodynamic simulations spreads much further from the initial neighbouring dark matter owing to feedback from supernovae (SNe) and active galactic nuclei (AGN). We show that large-scale baryon spread is very sensitive to model implementation details, with the fiducial simba model spreading ∼40 per cent of baryons >1 Mpc away compared to ∼10 per cent for the IllustrisTNG and astrid models. Increasing the efficiency of AGN-driven outflows greatly increases baryon spread while increasing the strength of SNe-driven winds can decrease spreading due to non-linear coupling of stellar and AGN feedback. We compare total matter power spectra between hydrodynamic and paired N-body simulations and demonstrate that the baryonic spread metric broadly captures the global impact of feedback on matter clustering over variations of cosmological and astrophysical parameters, initial conditions, and (to a lesser extent) galaxy formation models. Using symbolic regression, we find a function that reproduces the suppression of power by feedback as a function of wave number (k) and baryonic spread up to $k \sim 10\, h$ Mpc−1 in SIMBA while highlighting the challenge of developing models robust to variations in galaxy formation physics implementation.

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 $h\, \mathrm{Mpc}^{-1}$.

Feedback from active galactic nuclei and stellar processes changes the matter distribution on small scales, leading to significant systematic uncertainty in weak lensing constraints on cosmology. We investigate how the observable properties of group-scale haloes can constrain feedback’s impact on the matter distribution using Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS). Extending the results of previous work to smaller halo masses and higher wavenumber, k, we find that the baryon fraction in haloes contains significant information about the impact of feedback on the matter power spectrum. We explore how the thermal Sunyaev Zel’dovich (tSZ) signal from group-scale haloes contains similar information. Using recent Dark Energy Survey weak lensing and Atacama Cosmology Telescope tSZ cross-correlation measurements and models trained on CAMELS, we obtain 10 per cent constraints on feedback effects on the power spectrum at $k \sim 5\, h\, {\rm Mpc}^{-1}$. We show that with future surveys, it will be possible to constrain baryonic effects on the power spectrum to $\mathcal {O}(\lt 1~{{\ \rm per\ cent}})$ at $k = 1\, h\, {\rm Mpc}^{-1}$ and $\mathcal {O}(3~{{\ \rm per\ cent}})$ at $k = 5\, h\, {\rm Mpc}^{-1}$ using the methods that we introduce here. Finally, we investigate the impact of feedback on the matter bispectrum, finding that tSZ observables are highly informative in this case.