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    We investigate how feedback and environment shapes the X-ray scaling relations of early-type galaxies (ETGs), especially at the low-mass end. We select central-ETGs from the TNG100 box of IllustrisTNG that have stellar masses $\log _{10}(M_{\ast }/\mathrm{M_{\odot }})\in [10.7, 11.9]$. We derive mock X-ray luminosity (LX, 500) and spectroscopic-like temperature (Tsl, 500) of hot gas within R500 of the ETG haloes using the MOCK-X pipeline. The scaling between LX, 500 and the total mass within 5 effective radii ($M_{5R_{\rm e}}$) agrees well with observed ETGs from Chandra. IllustrisTNG reproduces the observed increase in scatter of LX, 500 towards lower masses, and we find that ETGs with $\log _{10} (M_{5R_{\rm e}}/\mathrm{M_{\odot }}) \leqslant 11.5$ with above-average LX, 500 experienced systematically lower cumulative kinetic AGN feedback energy historically (vice versa for below-average ETGs). This leads to larger gas mass fractions and younger stellar populations with stronger stellar feedback heating, concertedly resulting in the above-average LX, 500. The LX, 500–Tsl, 500 relation shows a similar slope to the observed ETGs but the simulation systematically underestimates the gas temperature. Three outliers that lie far below the LX–Tsl relation all interacted with larger galaxy clusters recently and demonstrate clear features of environmental heating. We propose that the distinct location of these backsplash ETGs in the LX–Tsl plane could provide a new way of identifying backsplash galaxies in future X-ray surveys.

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  2. Abstract

    We present an in-depth analysis of gas morphologies for a sample of 25 Milky Way–like galaxies from the IllustrisTNG TNG50 simulation. We constrain the morphology of cold, warm, hot gas, and gas particles as a whole using a local shell iterative method and explore its observational implications by computing the hard-to-soft X-ray ratio, which ranges between 10−3and 10−2in the inner ∼50 kpc of the distribution and 10−5–10−4at the outer portion of the hot gas distribution. We group galaxies into three main categories: simple, stretched, and twisted. These categories are based on the radial reorientation of the principal axes of the reduced inertia tensor. We find that a vast majority (77%) of the galaxies in our sample exhibit twisting patterns in their radial profiles. Additionally, we present detailed comparisons between (i) the gaseous distributions belonging to individual temperature regimes, (ii) the cold gas distributions and stellar distributions, and (iii) the gaseous distributions and dark matter (DM) halos. We find a strong correlation between the morphological properties of the cold gas and stellar distributions. Furthermore, we find a correlation between gaseous distributions with a DM halo that increases with gas temperature, implying that we may use the warm–hot gaseous morphology as a tracer to probe the DM morphology. Finally, we show gaseous distributions exhibit significantly more prolate morphologies than the stellar distributions and DM halos, which we hypothesize is due to stellar and active galactic nucleus feedback.

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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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    Using high-resolution cosmological radiation-hydrodynamic (RHD) simulations (thesan-hr), we explore the impact of alternative dark matter (altDM) models on galaxies during the Epoch of Reionization. The simulations adopt the IllustrisTNG galaxy formation model. We focus on altDM models that exhibit small-scale suppression of the matter power spectrum, namely warm dark matter (WDM), fuzzy dark matter (FDM), and interacting dark matter (IDM) with strong dark acoustic oscillations (sDAO). In altDM scenarios, both the halo mass functions and the ultraviolet luminosity functions at z ≳ 6 are suppressed at the low-mass/faint end, leading to delayed global star formation and reionization histories. However, strong non-linear effects enable altDM models to ‘catch up’ with cold dark matter (CDM) in terms of star formation and reionization. The specific star formation rates are enhanced in halos below the half-power mass in altDM models. This enhancement coincides with increased gas abundance, reduced gas depletion times, more compact galaxy sizes, and steeper metallicity gradients at the outskirts of the galaxies. These changes in galaxy properties can help disentangle altDM signatures from a range of astrophysical uncertainties. Meanwhile, it is the first time that altDM models have been studied in RHD simulations of galaxy formation. We uncover significant systematic uncertainties in reionization assumptions on the faint-end luminosity function. This underscores the necessity of accurately modeling the small-scale morphology of reionization in making predictions for the low-mass galaxy population. Upcoming James Webb Space Telescope imaging surveys of deep lensed fields hold potential for uncovering the faint low-mass galaxy population, which could provide constraints on altDM models.

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    The feedback loop between the galaxies producing the background radiation field for reionization and their growth is crucial, particularly for low-mass haloes. Despite this, the vast majority of galaxy formation studies employ a spatially uniform, time-varying reionizing background, with the majority of reionization studies employing galaxy formation models only required to work at high redshift. This paper uses the well-studied TNG galaxy formation model, calibrated at low redshift, coupled to the arepo-rt code, to self-consistently solve the coupled problems of galaxy evolution and reionization, evaluating the impact of patchy (and slow) reionization on early galaxies. thesan-hr is an extension of the thesan project to higher resolution (a factor of 50 increase, with a baryonic mass of mb ≈ 104 M⊙), to additionally enable the study of ‘mini-haloes’ with virial temperatures Tvir < 104 K. Comparing the self-consistent model to a uniform UV background, we show that galaxies in thesan-hr are predicted to be larger in physical extent (by a factor ∼2), less metal enriched (by ∼0.2 dex), and less abundant (by a factor ∼10 at M1500 =   − 10) by z = 5. We show that differences in star formation and enrichment patterns lead to significantly different predictions for star formation in low mass haloes, low-metallicity star formation, and even the occupation fraction of haloes. We posit that cosmological galaxy formation simulations aiming to study early galaxy formation (z ≳ 3) must employ a spatially inhomogeneous UV background to accurately reproduce galaxy properties.

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    We present the to-date largest parameter space exploration of binaries in circumbinary discs (CBDs), deriving orbital evolution prescriptions for eccentric, unequal mass binaries from our suite of hydrodynamic simulations. In all cases, binary eccentricities evolve towards steady state values that increase with mass ratio, and saturate at an equilibrium eccentricity eb,eq ∼ 0.5 in the large mass ratio regime, in line with resonant theory. For binaries accreting at their combined Eddington limit, a steady state eccentricity can be achieved within a few megayears. Once at their steady state eccentricities, binaries with qb ≳ 0.3 evolve towards coalescence, while lower mass ratio systems expand due to CBD torques. We discuss implications for population studies of massive black hole binaries, protostars in binary systems, and post-common envelope binaries observed by ground-based gravitational wave detectors.

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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

    Elongated bar-like features are ubiquitous in galaxies, occurring at the centers of approximately two-thirds of spiral disks in the nearby Universe. Due to gravitational interactions between the bar and the other components of galaxies, it is expected that angular momentum and matter will redistribute over long (Gyr) timescales in barred galaxies. Previous work ignoring the gas phase of galaxies has conclusively demonstrated that bars should slow their rotation over time due to their interaction with dark matter halos. We have performed a simulation of a Milky Way–like galactic disk hosting a strong bar, including a state-of-the-art model of the interstellar medium and a live dark matter halo. In this simulation, the bar pattern does not slow down over time, and instead it remains at a stable, constant rate of rotation. This behavior has been observed in previous simulations using more simplified models for the interstellar gas, but the apparent lack of secular evolution has remained unexplained. We find that the presence of the gas phase arrests the process by which the dark matter halo slows down a bar, a phenomenon we term bar locking. This locking is responsible for stabilizing the bar pattern speed. We find that, in a Milky Way–like disk, a gas fraction of only about 5% is necessary for this mechanism to operate. Our result naturally explains why nearly all observed bars rotate rapidly and is especially relevant for our understanding of how the Milky Way arrived at its present state.

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  9. Abstract

    We present CAMELS-ASTRID, the third suite of hydrodynamical simulations in the Cosmology and Astrophysics with MachinE Learning (CAMELS) project, along with new simulation sets that extend the model parameter space based on the previous frameworks of CAMELS-TNG and CAMELS-SIMBA, to provide broader training sets and testing grounds for machine-learning algorithms designed for cosmological studies. CAMELS-ASTRID employs the galaxy formation model following the ASTRID simulation and contains 2124 hydrodynamic simulation runs that vary three cosmological parameters (Ωm,σ8, Ωb) and four parameters controlling stellar and active galactic nucleus (AGN) feedback. Compared to the existing TNG and SIMBA simulation suites in CAMELS, the fiducial model of ASTRID features the mildest AGN feedback and predicts the least baryonic effect on the matter power spectrum. The training set of ASTRID covers a broader variation in the galaxy populations and the baryonic impact on the matter power spectrum compared to its TNG and SIMBA counterparts, which can make machine-learning models trained on the ASTRID suite exhibit better extrapolation performance when tested on other hydrodynamic simulation sets. We also introduce extension simulation sets in CAMELS that widely explore 28 parameters in the TNG and SIMBA models, demonstrating the enormity of the overall galaxy formation model parameter space and the complex nonlinear interplay between cosmology and astrophysical processes. With the new simulation suites, we show that building robust machine-learning models favors training and testing on the largest possible diversity of galaxy formation models. We also demonstrate that it is possible to train accurate neural networks to infer cosmological parameters using the high-dimensional TNG-SB28 simulation set.

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    Upcoming large galaxy surveys will subject the standard cosmological model, Lambda Cold Dark Matter, to new precision tests. These can be tightened considerably if theoretical models of galaxy formation are available that can predict galaxy clustering and galaxy–galaxy lensing on the full range of measurable scales, throughout volumes as large as those of the surveys, and with sufficient flexibility that uncertain aspects of the underlying astrophysics can be marginalized over. This, in particular, requires mock galaxy catalogues in large cosmological volumes that can be directly compared to observation, and can be optimized empirically by Monte Carlo Markov Chains or other similar schemes, thus eliminating or estimating parameters related to galaxy formation when constraining cosmology. Semi-analytic galaxy formation methods implemented on top of cosmological dark matter simulations offer a computationally efficient approach to construct physically based and flexibly parametrized galaxy formation models, and as such they are more potent than still faster, but purely empirical models. Here, we introduce an updated methodology for the semi-analytic L-Galaxies code, allowing it to be applied to simulations of the new MillenniumTNG project, producing galaxies directly on fully continuous past lightcones, potentially over the full sky, out to high redshift, and for all galaxies more massive than $\sim 10^8\, {\rm M}_\odot$. We investigate the numerical convergence of the resulting predictions, and study the projected galaxy clustering signals of different samples. The new methodology can be viewed as an important step towards more faithful forward-modelling of observational data, helping to reduce systematic distortions in the comparison of theory to observations.

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