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We construct accurate emulators for the projected and redshift space galaxy correlation functions and excess surface density as measured by galaxy–galaxy lensing, based on halo occupation distribution modeling. Using the complete Mira-Titan suite of 111N-body simulations, our emulators vary over eight cosmological parameters and include the effects of neutrino mass and dynamical dark energy. We demonstrate that our emulators are sufficiently accurate for the analysis of the Baryon Oscillation Spectroscopic Survey DR12 CMASS galaxy sample over the range 0.5 ≤r≤ 50h⁻¹Mpc. Furthermore, we show that our emulators are capable of recovering unbiased cosmological constraints from realistic mock catalogs over the same range. Our mock catalog tests show the efficacy of combining small-scale galaxy–galaxy lensing with redshift space clustering and that we can constrain the growth rate andσ₈to 7% and 4.5%, respectively, for a CMASS-like sample using only the measurements covered by our emulator. With the inclusion of a cosmic microwave background prior onH₀, this reduces to a 2% measurement of the growth rate.

 

Ultra-diffuse galaxies (UDGs) are both extreme products of galaxy evolution and extreme environments in which to test our understanding of star formation. In this work, we contrast the spatially resolved star formation activity of a sample of 22 Hi-selected UDGs and 35 low-mass galaxies from the NASA Sloan Atlas (NSA) catalog within 120 Mpc. We employ a new joint spectral energy distribution fitting method to compute star formation rate and stellar mass surface density maps that leverage the high spatial resolution optical imaging data of the Hyper Suprime-Cam Subaru Strategic Program and the UV coverage of the Galaxy Evolution Explorer, along with Hiradial profiles estimated from a subset of galaxies that have spatially resolved Himaps. We find that UDGs have low star formation efficiencies as a function of their atomic gas down to scales of 500 pc. We additionally find that the stellar mass-weighted sizes of our UDG sample are unremarkable when considered as a function of their Himass—their stellar sizes are comparable to NSA dwarfs at fixed Himass. This is a natural result in the picture where UDGs are forming stars normally, but at low efficiencies. We compare our results to predictions from contemporary models of galaxy formation, and find in particular that our observations are difficult to reproduce in models where UDGs undergo stellar expansion due to vigorous star formation feedback should bursty star formation be required down toz= 0.

 

We compare stellar mass surface density, metallicity, age, and line-of-sight velocity dispersion profiles in massive ($M_*\ge 10^{10.5}\, \mathrm{M_\odot }$) present-day early-type galaxies (ETGs) from the MaNGA survey with simulated galaxies from the TNG100 simulation of the IllustrisTNG suite. We find an excellent agreement between the stellar mass surface density profiles of MaNGA and TNG100 ETGs, both in shape and normalization. Moreover, TNG100 reproduces the shapes of the profiles of stellar metallicity and age, as well as the normalization of velocity dispersion distributions of MaNGA ETGs. We generally also find good agreement when comparing the stellar profiles of central and satellite galaxies between MaNGA and TNG100. An exception is the velocity dispersion profiles of very massive ($M_*\gtrsim 10^{11.5}\, \mathrm{M_\odot }$) central galaxies, which, on average, are significantly higher in TNG100 than in MaNGA ($\approx 50\, \mathrm{km\, s^{-1}}$). We study the radial profiles of in situ and ex situ stars in TNG100 and discuss the extent to which each population contributes to the observed MaNGA profiles. Our analysis lends significant support to the idea that high-mass ($M_*\gtrsim 10^{11}\, \mathrm{M_\odot }$) ETGs in the present-day Universe are the result of a merger-driven evolution marked by major mergers that tend to homogenize the stellar populations of the progenitors in the merger remnant.

 

It is clear that within the class of ultra-diffuse galaxies (UDGs), there is an extreme range in the richness of their associated globular cluster (GC) systems. Here, we report the structural properties of five UDGs in the Perseus cluster based on deep Subaru/Hyper Suprime-Cam imaging. Three appear GC-poor and two appear GC-rich. One of our sample, PUDG_R24, appears to be undergoing quenching and is expected to fade into the UDG regime within the next ∼0.5 Gyr. We target this sample with Keck Cosmic Web Imager (KCWI) spectroscopy to investigate differences in their dark matter haloes, as expected from their differing GC content. Our spectroscopy measures both recessional velocities, confirming Perseus cluster membership, and stellar velocity dispersions, to measure dynamical masses within their half-light radius. We supplement our data with that from the literature to examine trends in galaxy parameters with GC system richness. We do not find the correlation between GC numbers and UDG phase space positioning expected if GC-rich UDGs environmentally quench at high redshift. We do find GC-rich UDGs to have higher velocity dispersions than GC-poor UDGs on average, resulting in greater dynamical mass within the half-light radius. This agrees with the first order expectation that GC-rich UDGs have higher halo masses than GC-poor UDGs.

 

Extended, old, and round stellar halos appear to be ubiquitous around high-mass dwarf galaxies (10^8.5<M_⋆/M_⊙< 10^9.6) in the observed universe. However, it is unlikely that these dwarfs have undergone a sufficient number of minor mergers to form stellar halos that are composed of predominantly accreted stars. Here, we demonstrate that FIRE-2 (Feedback in Realistic Environments) cosmological zoom-in simulations are capable of producing dwarf galaxies with realistic structures, including both a thick disk and round stellar halo. Crucially, these stellar halos are formed in situ, largely via the outward migration of disk stars. However, there also exists a large population of “nondisky” dwarfs in FIRE-2 that lack a well-defined disk/halo and do not resemble the observed dwarf population. These nondisky dwarfs tend to be either more gas-poor or to have burstier recent star formation histories than the disky dwarfs, suggesting that star formation feedback may be preventing disk formation. Both classes of dwarfs underscore the power of a galaxy’s intrinsic shape—which is a direct quantification of the distribution of the galaxy’s stellar content—to interrogate the feedback implementation in simulated galaxies.

 

ABSTRACT We perform a consistent comparison of the mass and mass profiles of massive (M⋆ > 1011.4 M⊙) central galaxies at z ∼ 0.4 from deep Hyper Suprime-Cam (HSC) observations and from the Illustris, TNG100, and Ponos simulations. Weak lensing measurements from HSC enable measurements at fixed halo mass and provide constraints on the strength and impact of feedback at different halo mass scales. We compare the stellar mass function (SMF) and the Stellar-to-Halo Mass Relation (SHMR) at various radii and show that the radius at which the comparison is performed is important. In general, Illustris and TNG100 display steeper values of α where $M_{\star } \propto M_{\rm vir}^{\alpha }$. These differences are more pronounced for Illustris than for TNG100 and in the inner rather than outer regions of galaxies. Differences in the inner regions may suggest that TNG100 is too efficient at quenching in situ star formation at Mvir ≃ 1013 M⊙ but not efficient enough at Mvir ≃ 1014 M⊙. The outer stellar masses are in excellent agreement with our observations at Mvir ≃ 1013 M⊙, but both Illustris and TNG100 display excess outer mass as Mvir ≃ 1014 M⊙ (by ∼0.25 and ∼0.12 dex, respectively). We argue that reducing stellar growth at early times in $M_\star \sim 10^{9-10} \, \mathrm{M}_{\odot }$ galaxies would help to prevent excess ex-situ growth at this mass scale. The Ponos simulations do not implement AGN feedback and display an excess mass of ∼0.5 dex at r < 30 kpc compared to HSC which is indicative of overcooling and excess star formation in the central regions. The comparison of the inner profiles of Ponos and HSC suggests that the physical scale over which the central AGN limits star formation is r ≲ 20 kpc. Joint comparisons between weak lensing and galaxy stellar profiles are a direct test of whether simulations build and deposit galaxy mass in the correct dark matter haloes and thereby provide powerful constraints on the physics of feedback and galaxy growth. Our galaxy and weak lensing profiles are publicly available to facilitate comparisons with other simulations. 

ABSTRACT Using deep images from the Hyper Suprime-Cam (HSC) survey and taking advantage of its unprecedented weak lensing capabilities, we reveal a remarkably tight connection between the stellar mass distribution of massive central galaxies and their host dark matter halo mass. Massive galaxies with more extended stellar mass distributions tend to live in more massive dark matter haloes. We explain this connection with a phenomenological model that assumes, (1) a tight relation between the halo mass and the total stellar content in the halo, (2) that the fraction of in situ and ex situ mass at r <10 kpc depends on halo mass. This model provides an excellent description of the stellar mass functions (SMFs) of total stellar mass ($M_{\star }^{\mathrm{max}}$) and stellar mass within inner 10 kpc ($M_{\star }^{10}$) and also reproduces the HSC weak lensing signals of massive galaxies with different stellar mass distributions. The best-fitting model shows that halo mass varies significantly at fixed total stellar mass (as much as 0.4 dex) with a clear dependence on $M_{\star }^{10}$. Our two-parameter $M_{\star }^{\mathrm{max}}$–$M_{\star }^{10}$ description provides a more accurate picture of the galaxy–halo connection at the high-mass end than the simple stellar–halo mass relation (SHMR) and opens a new window to connect the assembly history of haloes with those of central galaxies. The model also predicts that the ex situ component dominates the mass profiles of galaxies at r < 10 kpc for log M⋆ ≥ 11.7. The code used for this paper is available online https://github.com/dr-guangtou/asap