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DOE OSTI2023

From Images to Dark Matter: End-to-end Inference of Substructure from Hundreds of Strong Gravitational Lenses

Abstract Constraining the distribution of small-scale structure in our universe allows us to probe alternatives to the cold dark matter paradigm. Strong gravitational lensing offers a unique window into small dark matter halos (<10 10 M ⊙ ) because these halos impart a gravitational lensing signal even if they do not host luminous galaxies. We create large data sets of strong lensing images with realistic low-mass halos, Hubble Space Telescope (HST) observational effects, and galaxy light from HST’s COSMOS field. Using a simulation-based inference pipeline, we train a neural posterior estimator of the subhalo mass function (SHMF) and place constraints on populations of lenses generated using a separate set of galaxy sources. We find that by combining our network with a hierarchical inference framework, we can both reliably infer the SHMF across a variety of configurations and scale efficiently to populations with hundreds of lenses. By conducting precise inference on large and complex simulated data sets, our method lays a foundation for extracting dark matter constraints from the next generation of wide-field optical imaging surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

DESI Observations of the Andromeda Galaxy: Revealing the Immigration History of Our Nearest Neighbor

Abstract We present Dark Energy Spectroscopic Instrument (DESI) observations of the inner halo of M31, which reveal the kinematics of a recent merger—a galactic immigration event—in exquisite detail. Of the 11,416 sources studied in 3.75 hr of on-sky exposure time, 7438 are M31 sources with well-measured radial velocities. The observations reveal intricate coherent kinematic structure in the positions and velocities of individual stars: streams, wedges, and chevrons. While hints of coherent structures have been previously detected in M31, this is the first time they have been seen with such detail and clarity in a galaxy beyond the Milky Way. We find clear kinematic evidence for shell structures in the Giant Stellar Stream, the Northeast Shelf, and Western Shelf regions. The kinematics are remarkably similar to the predictions of dynamical models constructed to explain the spatial morphology of the inner halo. The results are consistent with the interpretation that much of the substructure in the inner halo of M31 is produced by a single galactic immigration event 1–2 Gyr ago. Significant numbers of metal-rich stars ([Fe/H] > − 0.5) are present in all of the detected substructures, suggesting that the immigrating galaxy had an extended star formation history. We also investigate the ability of the shells and Giant Stellar Stream to constrain the gravitational potential of M31, and estimate the mass within a projected radius of 125 kpc to be log 10 M NFW ( < 125 kpc ) / M ⊙ = 11.80 − 0.10 + 0.12 . The results herald a new era in our ability to study stars on a galactic scale and the immigration histories of galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Overview of the DESI Milky Way Survey

Abstract We describe the Milky Way Survey (MWS) that will be undertaken with the Dark Energy Spectroscopic Instrument (DESI) on the Mayall 4 m telescope at the Kitt Peak National Observatory. Over the next 5 yr DESI MWS will observe approximately seven million stars at Galactic latitudes ∣ b ∣ > 20°, with an inclusive target selection scheme focused on the thick disk and stellar halo. MWS will also include several high-completeness samples of rare stellar types, including white dwarfs, low-mass stars within 100 pc of the Sun, and horizontal branch stars. We summarize the potential of DESI to advance understanding of the Galactic structure and stellar evolution. We introduce the final definitions of the main MWS target classes and estimate the number of stars in each class that will be observed. We describe our pipelines for deriving radial velocities, atmospheric parameters, and chemical abundances. We use ≃500,000 spectra of unique stellar targets from the DESI Survey Validation program (SV) to demonstrate that our pipelines can measure radial velocities to ≃1 km s −1 and [Fe/H] accurate to ≃0.2 dex for typical stars in our main sample. We find the stellar parameter distributions from ≈100 deg 2 of SV observations with ≳90% completeness on our main sample are in good agreement with expectations from mock catalogs and previous surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Symphony: Cosmological Zoom-in Simulation Suites over Four Decades of Host Halo Mass

Abstract We present Symphony, a compilation of 262 cosmological, cold-dark-matter-only zoom-in simulations spanning four decades of host halo mass, from 10 11 –10 15 M ⊙ . This compilation includes three existing simulation suites at the cluster and Milky Way–mass scales, and two new suites: 39 Large Magellanic Cloud-mass (10 11 M ⊙ ) and 49 strong-lens-analog (10 13 M ⊙ ) group-mass hosts. Across the entire host halo mass range, the highest-resolution regions in these simulations are resolved with a dark matter particle mass of ≈3 × 10 −7 times the host virial mass and a Plummer-equivalent gravitational softening length of ≈9 × 10 −4 times the host virial radius, on average. We measure correlations between subhalo abundance and host concentration, formation time, and maximum subhalo mass, all of which peak at the Milky Way host halo mass scale. Subhalo abundances are ≈50% higher in clusters than in lower-mass hosts at fixed sub-to-host halo mass ratios. Subhalo radial distributions are approximately self-similar as a function of host mass and are less concentrated than hosts’ underlying dark matter distributions. We compare our results to the semianalytic model Galacticus , which predicts subhalo mass functions with a higher normalization at the low-mass end and radial distributions that are slightly more concentrated than Symphony. We use UniverseMachine to model halo and subhalo star formation histories in Symphony, and we demonstrate that these predictions resolve the formation histories of the halos that host nearly all currently observable satellite galaxies in the universe. To promote open use of Symphony, data products are publicly available at http://web.stanford.edu/group/gfc/symphony .

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

The Aemulus Project. V. Cosmological Constraint from Small-scale Clustering of BOSS Galaxies

We analyze clustering measurements of BOSS galaxies using a simulation-based emulator of two-point statistics. We focus on the monopole and quadrupole of the redshift-space correlation function, and the projected correlation function, at scales of 0.1 ~ 60 h -1 Mpc. Although our simulations are based on wCDM with general relativity (GR), we include a scaling parameter of the halo velocity field, γ f , defined as the amplitude of the halo velocity field relative to the GR prediction. We divide the BOSS data into three redshift bins. After marginalizing over other cosmological parameters, galaxy bias parameters, and the velocity scaling parameter, we find fσ 8 (z = 0.25) = 0.413 ± 0.031, fσ 8 (z = 0.4) = 0.470 ± 0.026, and fσ 8 (z = 0.55) = 0.396 ± 0.022. Compared with Planck observations using a flat Lambda cold dark matter model, our results are lower by 1.9σ, 0.3σ, and 3.4σ, respectively. These results are consistent with other recent simulation-based results at nonlinear scales, including weak lensing measurements of BOSS LOWZ galaxies, two-point clustering of eBOSS LRGs, and an independent clustering analysis of BOSS LOWZ. All these results are generally consistent with a combination of ${\gamma }_{f}^{1/2}{\sigma }_{8}\approx 0.75$. We note, however, that the BOSS data is well fit assuming GR, i.e., γf = 1. We cannot rule out an unknown systematic error in the galaxy bias model at nonlinear scales, but near-future data and modeling will enhance our understanding of the galaxy–halo connection, and provide a strong test of new physics beyond the standard model.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Target Selection and Sample Characterization for the DESI LOW-Z Secondary Target Program

Abstract We introduce the DESI LOW- Z Secondary Target Survey, which combines the wide-area capabilities of the Dark Energy Spectroscopic Instrument (DESI) with an efficient, low-redshift target selection method. Our selection consists of a set of color and surface brightness cuts, combined with modern machine-learning methods, to target low-redshift dwarf galaxies ( z < 0.03) between 19 < r < 21 with high completeness. We employ a convolutional neural network (CNN) to select high-priority targets. The LOW- Z survey has already obtained over 22,000 redshifts of dwarf galaxies ( M * < 10 9 M ⊙ ), comparable to the number of dwarf galaxies discovered in the Sloan Digital Sky Survey DR8 and GAMA. As a spare fiber survey, LOW- Z currently receives fiber allocation for just ∼50% of its targets. However, we estimate that our selection is highly complete: for galaxies at z < 0.03 within our magnitude limits, we achieve better than 95% completeness with ∼1% efficiency using catalog-level photometric cuts. We also demonstrate that our CNN selections z < 0.03 galaxies from the photometric cuts subsample at least 10 times more efficiently while maintaining high completeness. The full 5 yr DESI program will expand the LOW- Z sample, densely mapping the low-redshift Universe, providing an unprecedented sample of dwarf galaxies, and providing critical information about how to pursue effective and efficient low-redshift surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

The Aemulus Project. VI. Emulation of Beyond-standard Galaxy Clustering Statistics to Improve Cosmological Constraints

Abstract There is untapped cosmological information in galaxy redshift surveys in the nonlinear 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 Mpc) in order to constrain cosmological and galaxy bias parameters. In addition to standard statistics—the projected correlation function w p ( r 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 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 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 ∼6 h −1 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.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Buzzard to Cardinal: Improved Mock Catalogs for Large Galaxy Surveys

Abstract We present the Cardinal mock galaxy catalogs, a new version of the Buzzard simulation that has been updated to support ongoing and future cosmological surveys, including the Dark Energy Survey (DES), DESI, and LSST. These catalogs are based on a one-quarter sky simulation populated with galaxies out to a redshift of z = 2.35 to a depth of m r = 27. Compared to the Buzzard mocks, the Cardinal mocks include an updated subhalo abundance matching model that considers orphan galaxies and includes mass-dependent scatter between galaxy luminosity and halo properties. This model can simultaneously fit galaxy clustering and group–galaxy cross-correlations measured in three different luminosity threshold samples. The Cardinal mocks also feature a new color assignment model that can simultaneously fit color-dependent galaxy clustering in three different luminosity bins. We have developed an algorithm that uses photometric data to further improve the color assignment model and have also developed a novel method to improve small-scale lensing below the ray-tracing resolution. These improvements enable the Cardinal mocks to accurately reproduce the abundance of galaxy clusters and the properties of lens galaxies in the DES data. As such, these simulations will be a valuable tool for future cosmological analyses based on large sky surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

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 2021 April to May, 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. PRObabilistic Value-Added BGS (PROVABGS) Bayesian spectral energy distribution 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 × 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.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

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 the 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 Satellites Around Galactic Analogs (SAGA) background galaxies, i.e., spectra observed by the SAGA Survey that are not associated with the main SAGA host galaxies, to construct a sample of 11,925 spectroscopically confirmed low-mass galaxies from 0.01 ≲ z ≤ 0.21 and measure auroral line metallicities 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 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 sets 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.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

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

Abstract 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 ⊙ at the 1 σ level; however, a tail toward low M 50 prevents a 2 σ measurement. In this scenario, combining hosts with differing bright satellite abundances significantly reduces uncertainties on M 50 at the 1 σ level, but the 2 σ tail toward low M 50 persists. We project that observations of one (two) complete satellite populations can constrain warm DM models with m WDM ≈ 10 keV (20 keV). Subhalo mass function (SHMF) suppression can be constrained to ≈70%, 60%, and 50% that in cold dark matter (CDM) at peak virial masses of 10 8 , 10 9 , and 10 10 M ⊙ , respectively; SHMF enhancement constraints are weaker (≈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.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

symfind : Addressing the Fragility of Subhalo Finders and Revealing the Durability of Subhalos

Abstract A major question in ΛCDM is what this theory actually predicts for the properties of subhalo populations. Subhalos are difficult to accurately simulate and to find within simulations, and this propagates into uncertainty in theoretical predictions for satellite galaxies. We present Symfind , a new particle-tracking-based subhalo finder, and demonstrate that it can track subhalos to orders-of-magnitude lower masses than commonly used halo-finding tools, with a focus on Rockstar and consistent-trees . These longer survival times mean that at a fixed peak subhalo mass, we find ≈ 15%–40% more subhalos within the virial radius, R vir , and ≈35%–120% more subhalos within R vir /4 in the Symphony dark-matter-only simulation suite. More subhalos are found as the resolution is increased, in contrast to the Rockstar halo finder, which appears to be converged at smaller subhalo counts. We perform extensive numerical testing. In agreement with idealized simulations, we show that the v max , the maximum circular velocity, is systematically biased low until high resolutions ( n peak ≳ 3 × 10 4 ) are achieved, but that mass loss itself can be resolved at much more modest resolutions ( n peak ≳ 4 × 10 3 ). We show that Rockstar converges to false solutions for the mass function, radial distribution, and disruption masses of subhalos. We argue that our new method can trace resolved subhalos until the point of typical galaxy disruption without invoking post hoc orphan modeling. We outline a concrete set of steps for determining whether other subhalo finders meet the same criteria. We publicly release Symfind catalogs and particle data for the Symphony simulation suite at http://web.stanford.edu/group/gfc/symphony .

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

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

Abstract 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 (≈10 11 M ⊙ ) subhalo within the last 2 Gyr on a realistic orbit, placing them near 50 kpc from the host center at z ≈ 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 ⊙ throughout the virial radius, on average. This enhancement reaches ≈80% in the inner 100 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 ≈60% of the total subhalo population within 100 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.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

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 6−10 M ⊙ , 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 H i 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.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

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 deg 2 . The number of confirmed satellites per system ranges from zero to 13, in the stellar mass range of 10 6−10 M ⊙ . Based on a detailed completeness model, this sample accounts for 94% of the true satellite population down to M ⋆ = 10 7.5 M ⊙ . 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 M ⊙ is lower than the MW's, but in both cases, the MW is within 1σ 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.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

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—they are sensitive to the gravitational effects of low-mass (<10 10 M ⊙ ) 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 constraints from these models are limited by the methodology or the data. In this study, we introduce an accelerator-optimized simulation pipeline that can generate lens images with realistic subhalo populations in milliseconds. Leveraging this simulator, we identify the main limitation of our fiducial SBI analysis: training set size. We then adopt a sequential neural posterior estimation (SNPE) approach, allowing us to refine the training distribution to align with the observed data. Using only one-fifth as many mock Hubble Space Telescope images, SNPE matches the constraints on the low-mass halo population produced by our best nonsequential model. Our experiments suggest that an over 3 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 lens sample remains to be explored, the notable improvement in constraining power enabled by our sequential approach highlights that 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 SBI.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

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 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 also suggest that in the context of the TNG300 galaxy–halo connection, simple spherical overdensity on ∼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.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

The SAGA Survey. V. Modeling Satellite Systems around Milky Way–Mass Galaxies with Updated UniverseMachine

Abstract Environment plays a critical role in shaping the assembly of low-mass galaxies. Here, we use the U niverse M achine (UM) galaxy–halo connection framework and Data Release 3 of the Satellites Around Galactic Analogs (SAGA) Survey to place dwarf galaxy star formation and quenching into a cosmological context. UM is a data-driven forward model that flexibly parameterizes galaxy star formation rates (SFRs) using only halo mass and assembly history. We add a new quenching model to UM, tailored for galaxies with m ⋆ ≲ 10 9 M ⊙ , and constrain the model down to m ⋆ ≳ 10 7 M ⊙ using new SAGA observations of 101 satellite systems around Milky Way (MW)–mass hosts and a sample of isolated field galaxies in a similar mass range from the Sloan Digital Sky Survey. The new best-fit model, “UM-SAGA,” reproduces the satellite stellar mass functions, average SFRs, and quenched fractions in SAGA satellites while keeping isolated dwarfs mostly star-forming. The enhanced quenching in satellites relative to isolated field galaxies leads the model to maximally rely on halo assembly to explain the observed environmental quenching. Extrapolating the model down to m ⋆ ∼ 10 6.5 M ⊙ yields a quenched fraction of ≳30% for isolated field galaxies and ≳80% for satellites of MW-mass hosts at this stellar mass. Spectroscopic surveys can soon test this specific prediction to reveal the relative importance of internal feedback, cessation of mass and gas accretion, satellite-specific gas processes, and reionization for the evolution of faint low-mass galaxies.

Wang, Yunchong (ORCID:000000018913626X)↗