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Risa H. Wechsler

Publications and source records attributed to Risa H. Wechsler.

At least 37 records · Page 2Linked to original sources

EDEN: Exploring Disks Embedded in N-body simulations of Milky-Way-mass halos from Symphony

We investigate the impact of galactic disks on the tidal stripping of cold dark matter subhalos within Milky Way (MW)-mass halos ($M_{\rm vir}\sim 10^{12}\mathrm{M_{\odot}}$) using a new simulation suite, EDEN. By re-simulating 45 MW-mass zoom-in halos from the N-body Symphony compilation with embedded disk potentials, which evolve according to star formation histories predicted by the UniverseMachine model, we self-consistently tie disk growth to halo accretion rate and significantly expand the range of disk masses and formation histories studied. We use the particle-tracking-based subhalo finder Symfind to enhance the robustness of subhalo tracking. We find that disks near the median disk-to-halo mass ratio of our sample ($M_{\ast, \rm Disk}/M_{\rm vir, host} = 2\%$) reduce subhalo peak mass functions within 100 kpc by about $10\%$ for peak masses above $ 10^8\mathrm{M_{\odot}}$. Heavier, MW/M31-like disks ($M_{\ast, \rm Disk}/M_{\rm vir, host} \gtrsim 5\%$) lead to a reduction of more than $40\%$. Subhalo abundance suppression is more pronounced near halo centers, with particularly enhanced stripping for subhalos accreted over 8 Gyr ago on orbits with pericenters < 100 kpc. Suppression is further amplified when disk mass is increased within fixed halo and disk assembly histories. In all cases, the suppression we measure should be interpreted as stripping below the mass resolution limit rather than complete subhalo disruption. This study reshapes our understanding of the MW's impact on its satellites, suggesting it strips subhalos more efficiently than typical MW-mass galaxies due to its larger disk-to-halo mass ratio and earlier disk formation.

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Aemulus $ν$: Precision halo mass functions in w$ν$CDM cosmologies

Precise and accurate predictions of the halo mass function for cluster mass scales in $wν{\rm CDM}$ cosmologies are crucial for extracting robust and unbiased cosmological information from upcoming galaxy cluster surveys. Here, we present a halo mass function emulator for cluster mass scales ($\gtrsim 10^{13}M_\odot /h$) up to redshift $z=2$ with comprehensive support for the parameter space of $wν{\rm CDM}$ cosmologies allowed by current data. Based on the Aemulus $ν$ suite of simulations, the emulator marks a significant improvement in the precision of halo mass function predictions by incorporating both massive neutrinos and non-standard dark energy equation of state models. This allows for accurate modeling of the cosmology dependence in large-scale structure and galaxy cluster studies. We show that the emulator, designed using Gaussian Process Regression, has negligible theoretical uncertainties compared to dominant sources of error in future cluster abundance studies. Our emulator is publicly available, providing the community with a crucial tool for upcoming cosmological surveys such as LSST and Euclid.

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Dark Energy Survey: Modeling strategy for multiprobe cluster cosmology and validation for the Full Six-year Dataset

We introduce an updated To&Krause2021 model for joint analyses of cluster abundances and large-scale two-point correlations of weak lensing and galaxy and cluster clustering (termed CL+3x2pt analysis) and validate that this model meets the systematic accuracy requirements of analyses with the statistical precision of the final Dark Energy Survey (DES) Year 6 (Y6) dataset. The validation program consists of two distinct approaches, (1) identification of modeling and parameterization choices and impact studies using simulated analyses with each possible model misspecification (2) end-to-end validation using mock catalogs from customized Cardinal simulations that incorporate realistic galaxy populations and DES-Y6-specific galaxy and cluster selection and photometric redshift modeling, which are the key observational systematics. In combination, these validation tests indicate that the model presented here meets the accuracy requirements of DES-Y6 for CL+3x2pt based on a large list of tests for known systematics. In addition, we also validate that the model is sufficient for several other data combinations: the CL+GC subset of this data vector (excluding galaxy--galaxy lensing and cosmic shear two-point statistics) and the CL+3x2pt+BAO+SN (combination of CL+3x2pt with the previously published Y6 DES baryonic acoustic oscillation and Y5 supernovae data).

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GD-1 Stellar Stream and Cocoon in the DESI Early Data Release

We present 115 new spectroscopically identified members of the GD-1 tidal stream observed with the 5000-fiber Dark Energy Spectroscopic Instrument (DESI). We confirm the existence of a ``cocoon'' which is a broad (FWHM~2.932 deg ~ 460 pc) and kinematically hot (velocity dispersion, sigma ~ 5-8 km/s) component that surrounds a narrower (FWHM~ 0.353 deg ~ 55) and colder (sigma = 3.09+/-0.76 km/s) thin stream component (based on a median per star velocity precision of 2.7 km/s). The cocoon extends over at least a 30 degree segment of the stream observed by DESI. The thin and cocoon components have similar mean values of [Fe/H]: -2.54+/- 0.04 dex and -2.47+/- 0.06 dex suggestive of a common origin. The data are consistent with the following scenarios for the origin of the cocoon. The progenitor of the GD-1 stream was an accreted globular cluster (GC) and: (a) the cocoon was produced by pre-accretion tidal stripping of the GC while it was still inside its parent dwarf galaxy; (b) the cocoon is debris from the parent dwarf galaxy; (c) an initially thin GC tidal stream was heated by impacts from dark subhalos in the Milky Way; (d) an initially thin GC stream was heated by a massive Sagittarius dwarf galaxy; or a combination of some these. Future DESI spectroscopy and detailed modeling may enable us to distinguish between these possible origins.

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The SAGA Survey. III. A Census of 101 Satellite Systems around Milky Way-mass Galaxies

We present Data Release 3 (DR3) of the Satellites Around Galactic Analogs (SAGA) Survey, a spectroscopic survey characterizing satellite galaxies around Milky Way (MW)-mass galaxies. The SAGA Survey DR3 includes 378 satellites identified across 101 MW-mass systems in the distance range of 25-40.75 Mpc, and an accompanying redshift catalog of background galaxies (including about 46,000 taken by SAGA) in the SAGA footprint of 84.7 sq. deg. The number of confirmed satellites per system ranges from zero to 13, in the stellar mass range of 10^6 to 10^10 solar masses. Based on a detailed completeness model, this sample accounts for 94% of the true satellite population down to a stellar mass of 10^7.5 solar masses. We find that the mass of the most massive satellite in SAGA systems is the strongest predictor of satellite abundance; one-third of the SAGA systems contain LMC-mass satellites, and they tend to have more satellites than the MW. The SAGA satellite radial distribution is less concentrated than the MW's, and the SAGA quenched fraction below 10^8.5 solar masses is lower than the MW's, but in both cases, the MW is within 1 sigma of SAGA system-to-system scatter. SAGA satellites do not exhibit a clear corotating signal as has been suggested in the MW/M31 satellite systems. Although the MW differs in many respects from the typical SAGA system, these differences can be reconciled if the MW is an older, slightly less massive host with a recently accreted LMC/SMC system.

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How the Galaxy-Halo Connection Depends on Large-Scale Environment

We investigate the connection between galaxies, dark matter halos, and their large-scale environments at $z=0$ with Illustris TNG300 hydrodynamic simulation data. We predict stellar masses from subhalo properties to test two types of machine learning (ML) models: Explainable Boosting Machines (EBMs) with simple galaxy environment features and $\mathbb{E}(3)$-invariant graph neural networks (GNNs). The best-performing EBM models leverage spherically averaged overdensity features on $3$ Mpc scales. Interpretations via SHapley Additive exPlanations (SHAP) also suggest that, in the context of the TNG300 galaxy-halo connection, simple spherical overdensity on $\sim 3$ Mpc scales is more important than cosmic web distance features measured using the DisPerSE algorithm. Meanwhile, a GNN with connectivity defined by a fixed linking length, $L$, outperforms the EBM models by a significant margin. As we increase the linking length scale, GNNs learn important environmental contributions up to the largest scales we probe ($L=10$ Mpc). We conclude that $3$ Mpc distance scales are most critical for describing the TNG galaxy-halo connection using the spherical overdensity parameterization but that information on larger scales, which is not captured by simple environmental parameters or cosmic web features, can further augment these models. Our study highlights the benefits of using interpretable ML algorithms to explain models of astrophysical phenomena, and the power of using GNNs to flexibly learn complex relationships directly from data while imposing constraints from physical symmetries.

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SAGAbg II: the Low-Mass Star-Forming Sequence Evolves Significantly Between 0.05<z<0.21

The redshift-dependent relation between galaxy stellar mass and star formation rate (the Star-Forming Sequence, or SFS) is a key observational yardstick for galaxy assembly. We use the SAGAbg-A sample of background galaxies from the Satellites Around Galactic Analogs (SAGA) Survey to model the low-redshift evolution of the low-mass SFS. The sample is comprised of 23258 galaxies with H$α$-based star formation rates (SFRs) spanning $6<\log_{10}(\rm M_\star/[M_\odot])<10$ and $z<0.21$ ($t<2.5$ Gyr). Although it is common to bin or stack galaxies at $z \lesssim 0.2$ for galaxy population studies, the difference in lookback time between $z=0$ and $z=0.21$ is comparable to the time between $z=1$ to $z=2$. We develop a model to account for both the physical evolution of low-mass SFS and the selection function of the SAGA survey, allowing us to disentangle redshift evolution from redshift-dependent selection effects across the SAGAbg-A redshift range. Our findings indicate significant evolution in the SFS over the last 2.5 Gyr, with a rising normalization: $\langle {\rm SFR}({\rm M_\star=10^{8.5} M_\odot)}\rangle(z)=1.24^{+0.25}_{-0.23}\ {\rm z} -1.47^{+0.03}_{-0.03}$. We also identify the redshift limit at which a static SFS is ruled out at the 95% confidence level, which is $z=0.05$ based on the precision of the SAGAbg-A sample. Comparison with cosmological hydrodynamic simulations reveals that some contemporary simulations under-predict the recent evolution of the low-mass SFS. This demonstrates that the recent evolution of the low-mass SFS can provide new constraints on the assembly of the low-mass Universe and highlights the need for improved models in this regime.

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Milky Way-est: Cosmological Zoom-in Simulations with Large Magellanic Cloud and Gaia-Sausage-Enceladus Analogs

We present Milky Way-est, a suite of 20 cosmological cold-dark-matter-only zoom-in simulations of Milky Way (MW)-like host halos. Milky Way-est hosts are selected such that they (i) are consistent with the MW's measured halo mass and concentration, (ii) accrete a Large Magellanic Cloud (LMC)-like ($\approx 10^{11}~M_{\odot}$) subhalo within the last $2~\mathrm{Gyr}$ on a realistic orbit, placing them near $50~\mathrm{kpc}$ from the host center at $z\approx 0$, and (iii) undergo a $>$1:5 sub-to-host halo mass ratio merger with a Gaia-Sausage-Enceladus (GSE)-like system at early times ($0.67<z<3$). Hosts satisfying these LMC and GSE constraints constitute $< 1\%$ of all halos in the MW's mass range, and their total masses grow rapidly at late times due to LMC analog accretion. Compared to hosts of a similar final halo mass that are not selected to include LMC and GSE analogs, Milky Way-est hosts contain $22\%$ more subhalos with present-day virial masses above $10^8~M_{\odot}$ throughout the virial radius, on average. This enhancement reaches $\approx 80\%$ in the inner $100~\mathrm{kpc}$ and is largely, if not entirely, due to LMC-associated subhalos. These systems also induce spatial anisotropy in Milky Way-est subhalo populations, with $\approx 60\%$ of the total subhalo population within $100~\mathrm{kpc}$ found in the current direction of the LMC. Meanwhile, we find that GSE-associated subhalos do not significantly contribute to present-day Milky Way-est subhalo populations. These results provide context for our Galaxy's dark matter structure and subhalo population and will help interpret a range of measurements that are currently only possible in the MW.

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The SAGA Survey. IV. The Star Formation Properties of 101 Satellite Systems around Milky Way-mass Galaxies

We present the star-forming properties of 378 satellite galaxies around 101 Milky Way analogs in the Satellites Around Galactic Analogs (SAGA) Survey, focusing on the environmental processes that suppress or quench star formation. In the SAGA stellar mass range of 10^6 to 10^10 solar masses, we present quenched fractions, star-forming rates, gas-phase metallicities, and gas content. The fraction of SAGA satellites that are quenched increases with decreasing stellar mass and shows significant system-to-system scatter. SAGA satellite quenched fractions are highest in the central 100 kpc of their hosts and decline out to the virial radius. Splitting by specific star formation rate (sSFR), the least star-forming satellite quartile follows the radial trend of the quenched population. The median sSFR of star-forming satellites increases with decreasing stellar mass and is roughly constant with projected radius. Star-forming SAGA satellites are consistent with the star formation rate--stellar mass relationship determined in the Local Volume, while the median gas-phase metallicity is higher and median HI gas mass is lower at all stellar masses. We investigate the dependence of the satellite quenched fraction on host properties. Quenched fractions are higher in systems with larger host halo mass, but this trend is only seen in the inner 100 kpc; we do not see significant trends with host color or star formation rate. Our results suggest that lower mass satellites and satellites inside 100 kpc are more efficiently quenched in a Milky Way-like environment, with these processes acting sufficiently slowly to preserve a population of star-forming satellites at all stellar masses and projected radii.

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Forecasts for Galaxy Formation and Dark Matter Constraints from Dwarf Galaxy Surveys

The abundance of faint dwarf galaxies is determined by the underlying population of low-mass dark matter (DM) halos and the efficiency of galaxy formation in these systems. Here, we quantify potential galaxy formation and DM constraints from future dwarf satellite galaxy surveys. We generate satellite populations using a suite of Milky Way (MW)--mass cosmological zoom-in simulations and an empirical galaxy--halo connection model, and assess sensitivity to galaxy formation and DM signals when marginalizing over galaxy--halo connection uncertainties. We find that a survey of all satellites around one MW-mass host can constrain a galaxy formation cutoff at peak virial masses of $M_{50}=10^8~M_{\mathrm{\odot}}$ at the $1σ$ level; however, a tail toward low $M_{50}$ prevents a $2σ$ measurement. In this scenario, combining hosts with differing bright satellite abundances significantly reduces uncertainties on $M_{50}$ at the $1σ$ level, but the $2σ$ tail toward low $M_{50}$ persists. We project that observations of one (two) complete satellite populations can constrain warm DM models with $m_{\mathrm{WDM}}\approx 10~\mathrm{keV}$ ($20~\mathrm{keV}$). Subhalo mass function (SHMF) suppression can be constrained to $\approx 70\%$, $60\%$, and $50\%$ that in cold dark matter (CDM) at peak virial masses of $10^8$, $10^9$, and $10^{10}~M_{\mathrm{\odot}}$, respectively; SHMF enhancement constraints are weaker ($\approx 20$, $4$, and $2$ times that in CDM, respectively) due to galaxy--halo connection degeneracies. These results motivate searches for faint dwarf galaxies beyond the MW and indicate that ongoing missions like Euclid and upcoming facilities including the Vera C. Rubin Observatory and Nancy Grace Roman Space Telescope will probe new galaxy formation and DM physics.

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A Strong Gravitational Lens Is Worth a Thousand Dark Matter Halos: Inference on Small-Scale Structure Using Sequential Methods

Strong gravitational lenses are a singular probe of the universe's small-scale structure $\unicode{x2013}$ they are sensitive to the gravitational effects of low-mass $(<10^{10} M_\odot)$ halos even without a luminous counterpart. Recent strong-lensing analyses of dark matter structure rely on simulation-based inference (SBI). Modern SBI methods, which leverage neural networks as density estimators, have shown promise in extracting the halo-population signal. However, it is unclear whether the constraining power of these models has been limited by the methodology or the information content of the data. In this study, we introduce an accelerator-optimized simulation pipeline that can generate lens images with realistic subhalo populations in a matter of milliseconds. Leveraging this simulator, we identify the main methodological limitation of our fiducial SBI analysis: training set size. We then adopt a sequential neural posterior estimation (SNPE) approach, allowing us to iteratively refine the distribution of simulated training images to better align with the observed data. Using only one-fifth as many mock Hubble Space Telescope (HST) images, SNPE matches the constraints on the low-mass halo population produced by our best non-sequential model. Our experiments suggest that an over three order-of-magnitude increase in training set size and GPU hours would be required to achieve an equivalent result without sequential methods. While the full potential of the existing strong lens sample remains to be explored, the notable improvement in constraining power enabled by our sequential approach highlights that the current constraints are limited primarily by methodology and not the data itself. Moreover, our results emphasize the need to treat training set generation and model optimization as interconnected stages of any cosmological analysis using simulation-based inference techniques.

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The Aemulus Project VI: Emulation of beyond-standard galaxy clustering statistics to improve cosmological constraints

There is untapped cosmological information in galaxy redshift surveys in the non-linear regime. In this work, we use the AEMULUS suite of cosmological $N$-body simulations to construct Gaussian process emulators of galaxy clustering statistics at small scales ($0.1-50 \: h^{-1}\,\mathrm{Mpc}$) in order to constrain cosmological and galaxy bias parameters. In addition to standard statistics -- the projected correlation function $w_\mathrm{p}(r_\mathrm{p})$, the redshift-space monopole of the correlation function $ξ_0(s)$, and the quadrupole $ξ_2(s)$ -- we emulate statistics that include information about the local environment, namely the underdensity probability function $P_\mathrm{U}(s)$ and the density-marked correlation function $M(s)$. This extends the model of AEMULUS III for redshift-space distortions by including new statistics sensitive to galaxy assembly bias. In recovery tests, we find that the beyond-standard statistics significantly increase the constraining power on cosmological parameters of interest: including $P_\mathrm{U}(s)$ and $M(s)$ improves the precision of our constraints on $Ω_m$ by 27%, $σ_8$ by 19%, and the growth of structure parameter, $f σ_8$, by 12% compared to standard statistics. We additionally find that scales below $\sim6 \: h^{-1}\,\mathrm{Mpc}$ contain as much information as larger scales. The density-sensitive statistics also contribute to constraining halo occupation distribution parameters and a flexible environment-dependent assembly bias model, which is important for extracting the small-scale cosmological information as well as understanding the galaxy-halo connection. This analysis demonstrates the potential of emulating beyond-standard clustering statistics at small scales to constrain the growth of structure as a test of cosmic acceleration.

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SAGAbg I: A Near-Unity Mass Loading Factor in Low-Mass Galaxies via their Low-Redshift Evolution in Stellar Mass, Oxygen Abundance, and Star Formation Rate

Measuring the relation between star formation and galactic winds is observationally difficult. In this work we make an indirect measurement of the mass loading factor (the ratio between mass outflow rate and star formation rate) in low-mass galaxies using a differential approach to modeling the low-redshift evolution of the star-forming main sequence and mass-metallicity relation. We use the SAGA (Satellites Around Galactic Analogs) background galaxies, those spectra observed by the SAGA survey that are not associated with the main SAGA host galaxies, to construct a sample of 11925 spectroscopically confirmed low-mass galaxies from $0.01\lesssim z \leq 0.21$ and measure a auroral line metallicity for 120 galaxies. The crux of the method is to use the lowest redshift galaxies as the boundary condition of our model, and to infer a mass-loading factor for the sample by comparing the expected evolution of the low redshift reference sample in stellar mass, gas-phase metallicity, and star formation rate against the observed properties of the sample at higher redshift. We infer a mass-loading factor of $η_{\rm m}=0.92^{+1.76}_{-0.74}$, which is in line with direct measurements of the mass-loading factor from the literature despite the drastically different set of assumptions needed for each approach. While our estimate of the mass-loading factor is in good agreement with recent galaxy simulations that focus on resolving the dynamics of the interstellar medium, it is smaller by over an order of magnitude than the mass-loading factor produced by many contemporary cosmological simulations.

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Dynamical friction in self-interacting ultralight dark matter

We explore how dynamical friction in an ultralight dark matter (ULDM) background is affected by dark matter self-interactions. We calculate the force of dynamical friction on a point mass moving through a uniform ULDM background with self-interactions, finding that the force of dynamical friction vanishes for sufficiently strong repulsive self-interactions. Using the pseudospectral solver $\texttt{UltraDark.jl}$, we show with simulations that reasonable values of the ULDM self-interaction strength and particle mass cause $\mathcal{O}(1)$ differences in the acceleration of an object like a supermassive black hole (SMBH) traveling near the center of a soliton, relative to the case with no self-interactions. For example, repulsive self-interactions with $λ= 10^{-90}$ yield a deceleration due to dynamical friction $\approx70\%$ smaller than a model with no self-interactions. We discuss the observational implications of our results for SMBHs near soliton centers and for massive satellite galaxies falling into ultralight axion halos and show that outcomes are dependent on whether a self-interaction is present or not.

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The mass profiles of dwarf galaxies from Dark Energy Survey lensing

We present a novel approach to extracting dwarf galaxies from photometric data to measure their average halo mass profile with weak lensing. We characterise their stellar mass and redshift distributions with a spectroscopic calibration sample. Using the ${\sim}5000\mathrm{deg}^2$ multi-band photometry from Dark Energy Survey and redshifts from the Satellites Around Galactic Analogs (SAGA) survey with an unsupervised machine learning method, we select a low-mass galaxy sample spanning redshifts $z{<}0.3$ and divide it into three mass bins. From low to high median mass, the bins contain [146 420, 330 146, 275 028] galaxies and have median stellar masses of $\log_{10}(M_*/M_{\odot})= [8.52^{+0.57}_{-0.76}, 9.02^{+0.50}_ {-0.64}, 9.49^{+0.50}_{-0.58}]$. We measure the stacked excess surface mass density profiles, $ΔΣ(R)$, of these galaxies using galaxy--galaxy lensing with a signal-to-noise of [14, 23, 28]. Through a simulation-based forward-modelling approach, we fit the measurements to constrain the stellar-to-halo mass relation and find the median halo mass of these samples to be $\log_{10}(M_{\rm halo}/M_{\odot})$ = [$10.67\substack{+0.2\\-0.4}$, $11.01\substack{+0.14 \\ -0.27}$,$11.40\substack{+0.08\\-0.15}$]. The CDM profiles are consistent with NFW profiles over scales ${\lesssim}0.15 \rm{h}^{-1}$Mpc. We find that ${\sim}20$ per cent of the dwarf galaxy sample are satellites. This is the first measurement of the halo profiles and masses of such a comprehensive, low-mass galaxy sample. The techniques presented here pave the way for extracting and analysing even lower-mass dwarf galaxies and for more finely splitting galaxies by their properties with future photometric and spectroscopic survey data.

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Unraveling emission line galaxy conformity at z~1 with DESI early data

Emission line galaxies (ELGs) are now the preeminent tracers of large-scale structure at z>0.8 due to their high density and strong emission lines, which enable accurate redshift measurements. However, relatively little is known about ELG evolution and the ELG-halo connection, exposing us to potential modeling systematics in cosmology inference using these sources. In this paper, we propose a physical picture of ELGs and improve ELG-halo connection modeling using a variety of observations and simulated galaxy models. We investigate DESI-selected ELGs in COSMOS data, and infer that ELGs are rapidly star-forming galaxies with a large fraction exhibiting disturbed morphology, implying that many of them are likely to be merger-driven starbursts. We further postulate that the tidal interactions from mergers lead to correlated star formation in central-satellite ELG pairs, a phenomenon dubbed "conformity." We argue for the need to include conformity in the ELG-halo connection using galaxy models such as IllustrisTNG, and by combining observations such as the DESI ELG auto-correlation, ELG cross-correlation with Luminous Red Galaxies (LRGs), and ELG-cluster cross-correlation. We also explore the origin of conformity using the UniverseMachine model and elucidate the difference between conformity and the well-known galaxy assembly bias effect.

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Robust cosmological inference from non-linear scales with k-th nearest neighbor statistics

We present the methodology for deriving accurate and reliable cosmological constraints from non-linear scales (<50Mpc/h) with k-th nearest neighbor (kNN) statistics. We detail our methods for choosing robust minimum scale cuts and validating galaxy-halo connection models. Using cross-validation, we identify the galaxy-halo model that ensures both good fits and unbiased predictions across diverse summary statistics. We demonstrate that we can model kNNs effectively down to transverse scales of rp ~ 3Mpc/h and achieve precise and unbiased constraints on the matter density and clustering amplitude, leading to a 2% constraint on sigma_8. Our simulation-based model pipeline is resilient to varied model systematics, spanning simulation codes, halo finding, and cosmology priors. We demonstrate the effectiveness of this approach through an application to the Beyond-2p mock challenge. We propose further explorations to test more complex galaxy-halo connection models and tackle potential observational systematics.

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PROVABGS: The Probabilistic Stellar Mass Function of the BGS One-Percent Survey

We present the probabilistic stellar mass function (pSMF) of galaxies in the DESI Bright Galaxy Survey (BGS), observed during the One-Percent Survey. The One-Percent Survey was one of DESI's survey validation programs conducted from April to May 2021, before the start of the main survey. It used the same target selection and similar observing strategy as the main survey and successfully observed the spectra and redshifts of 143,017 galaxies in the $r < 19.5$ magnitude-limited BGS Bright sample and 95,499 galaxies in the fainter surface brightness and color selected BGS Faint sample over $z < 0.6$. We derive pSMFs from posteriors of stellar mass, $M_*$, inferred from DESI photometry and spectroscopy using the Hahn et al. (2022a; arXiv:2202.01809) PRObabilistic Value-Added BGS (PROVABGS) Bayesian SED modeling framework. We use a hierarchical population inference framework that statistically and rigorously propagates the $M_*$ uncertainties. Furthermore, we include correction weights that account for the selection effects and incompleteness of the BGS observations. We present the redshift evolution of the pSMF in BGS as well as the pSMFs of star-forming and quiescent galaxies classified using average specific star formation rates from PROVABGS. Overall, the pSMFs show good agreement with previous stellar mass function measurements in the literature. Our pSMFs showcase the potential and statistical power of BGS, which in its main survey will observe >100$\times$ more galaxies. Moreover, we present the statistical framework for subsequent population statistics measurements using BGS, which will characterize the global galaxy population and scaling relations at low redshifts with unprecedented precision.

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