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1. The Galaxy–Halo Connection of DESI Luminous Red Galaxies with Subhalo Abundance Matching

   https://doi.org/10.3847/1538-4357/ace76e  

   Berti, Angela M; Dawson, Kyle S; Dominguez, Wilber (August 2023, The Astrophysical Journal)

   Abstract We use subhalo abundance and age distribution matching to create magnitude-limited mock galaxy catalogs atz∼ 0.43, 0.52, and 0.63 withz-band and 3.4μmW1-band absolute magnitudes andr−zandr−W1 colors. From these magnitude-limited mocks, we select mock luminous red galaxy (LRG) samples according to the (r−z)-based (optical) and (r−W1)-based (infrared) selection criteria for the LRG sample of the Dark Energy Spectroscopic Instrument (DESI) survey. Our models reproduce the number densities, luminosity functions, color distributions, and projected clustering of the DESI Legacy Surveys that are the basis for DESI LRG target selection. We predict the halo occupation statistics of both optical and IR DESI LRGs at fixed cosmology and assess the differences between the two LRG samples. We find that IR-based SHAM modeling represents the differences between the optical and IR LRG populations better than using thezband and that age distribution matching overpredicts the clustering of LRGs, implying that galaxy color is uncorrelated with halo age in the LRG regime. Both the optical and IR DESI LRG target selections exclude some of the most luminous galaxies that would appear to be LRGs based on their position on the red sequence in optical color–magnitude space. Both selections also yield populations with a nontrivial LRG–halo connection that does not reach unity for the most massive halos. We find that the IR selection achieves greater completeness (≳90%) than the optical selection across all redshift bins studied. 

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2. Inferring Cosmological Parameters on SDSS via Domain-generalized Neural Networks and Light-cone Simulations

   https://doi.org/10.3847/1538-4357/ad73d4  

   Lee, Jun-Young; Kim, Ji-hoon; Jung, Minyong; Oh, Boon Kiat; Jo, Yongseok; Park, Songyoun; Lee, Jaehyun; Ting, Yuan-Sen; Hwang, Ho Seong (October 2024, The Astrophysical Journal)

   Abstract We present a proof-of-concept simulation-based inference on Ω_mandσ₈from the Sloan Digital Sky Survey (SDSS) Baryon Oscillation Spectroscopic Survey (BOSS) LOWZ Northern Galactic Cap (NGC) catalog using neural networks and domain generalization techniques without the need of summary statistics. Using rapid light-cone simulations L-picola, mock galaxy catalogs are produced that fully incorporate the observational effects. The collection of galaxies is fed as input to a point cloud-based network,Minkowski-PointNet. We also add relatively more accurate Gadgetmocks to obtain robust and generalizable neural networks. By explicitly learning the representations that reduce the discrepancies between the two different data sets via the semantic alignment loss term, we show that the latent space configuration aligns into a single plane in which the two cosmological parameters form clear axes. Consequently, during inference, the SDSS BOSS LOWZ NGC catalog maps onto the plane, demonstrating effective generalization and improving prediction accuracy compared to non-generalized models. Results from the ensemble of 25 independently trained machines find Ω_m= 0.339 ± 0.056 andσ₈= 0.801 ± 0.061, inferred only from the distribution of galaxies in the light-cone slices without relying on any indirect summary statistics. A single machine that best adapts to the Gadgetmocks yields a tighter prediction of Ω_m= 0.282 ± 0.014 andσ₈= 0.786 ± 0.036. We emphasize that adaptation across multiple domains can enhance the robustness of the neural networks in observational data. 

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3. Toward Accurate Modeling of Galaxy Clustering on Small Scales: Halo Model Extensions and Lingering Tension

   https://doi.org/10.3847/1538-4357/acc576  

   Beltz-Mohrmann, Gillian D.; Szewciw, Adam O.; Berlind, Andreas A.; Sinha, Manodeep (May 2023, The Astrophysical Journal)

   Abstract This paper represents an effort to provide robust constraints on the galaxy–halo connection and simultaneously test the Planck ΛCDM cosmology using a fully numerical model of small-scale galaxy clustering. We explore two extensions to the standard Halo Occupation Distribution model: assembly bias, whereby halo occupation depends on both halo mass and the larger environment, and velocity bias, whereby galaxy velocities do not perfectly trace the velocity of the dark matter within the halo. Moreover, we incorporate halo mass corrections to account for the impact of baryonic physics on the halo population. We identify an optimal set of clustering measurements to constrain this “decorated” HOD model for both low- and high-luminosity galaxies in SDSS DR7. We find that, for low-luminosity galaxies, a model with both assembly bias and velocity bias provides the best fit to the clustering measurements, with no tension remaining in the fit. In this model, we find evidence for both central and satellite galaxy assembly bias at the 99% and 95% confidence levels, respectively. In addition, we find evidence for satellite galaxy velocity bias at the 99.9% confidence level. For high-luminosity galaxies, we find no evidence for either assembly bias or velocity bias, but our model exhibits significant tension with SDSS measurements. We find that all of these conclusions still stand when we include the effects of baryonic physics on the halo mass function, suggesting that the tension we find for high-luminosity galaxies may be due to a problem with our assumed cosmological model. 

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4. A Southern Photometric Quasar Catalog from the Dark Energy Survey Data Release 2

   https://doi.org/10.3847/1538-4365/ac9ea8  

   Yang, Qian; Shen, Yue (December 2022, The Astrophysical Journal Supplement Series)

   Abstract We present a catalog of 1.4 million photometrically selected quasar candidates in the southern hemisphere over the ∼5000 deg²Dark Energy Survey (DES) wide survey area. We combine optical photometry from the DES second data release (DR2) with available near-infrared (NIR) and the all-sky unWISE mid-infrared photometry in the selection. We build models of quasars, galaxies, and stars with multivariate skew-tdistributions in the multidimensional space of relative fluxes as functions of redshift (or color for stars) and magnitude. Our selection algorithm assigns probabilities for quasars, galaxies, and stars and simultaneously calculates photometric redshifts (photo-z) for quasar and galaxy candidates. Benchmarking on spectroscopically confirmed objects, we successfully classify (with photometry) 94.7% of quasars, 99.3% of galaxies, and 96.3% of stars when all IR bands (NIRYJHKand WISE W1W2) are available. The classification and photo-zregression success rates decrease when fewer bands are available. Our quasar (galaxy) photo-zquality, defined as the fraction of objects with the difference between the photo-z z_pand the spectroscopic redshiftz_s, ∣Δz∣ ≡ ∣z_s−z_p∣/(1 +z_s) ≤ 0.1, is 92.2% (98.1%) when all IR bands are available, decreasing to 72.2% (90.0%) using optical DES data only. Our photometric quasar catalog achieves an estimated completeness of 89% and purity of 79% atr< 21.5 (0.68 million quasar candidates), with reduced completeness and purity at 21.5 <r≲ 24. Among the 1.4 million quasar candidates, 87,857 have existing spectra, and 84,978 (96.7%) of them are spectroscopically confirmed quasars. Finally, we provide quasar, galaxy, and star probabilities for all (0.69 billion) photometric sources in the DES DR2 coadded photometric catalog. 

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5. Dark Energy Survey Year 3 results: galaxy clustering and systematics treatment for lens galaxy samples

   https://doi.org/10.1093/mnras/stac104  

   Rodríguez-Monroy, M; Weaverdyck, N; Elvin-Poole, J; Crocce, M; Carnero Rosell, A; Andrade-Oliveira, F; Avila, S; Bechtol, K; Bernstein, G M; Blazek, J; et al (February 2022, Monthly Notices of the Royal Astronomical Society)

   ABSTRACT In this work, we present the galaxy clustering measurements of the two DES lens galaxy samples: a magnitude-limited sample optimized for the measurement of cosmological parameters, maglim, and a sample of luminous red galaxies selected with the redmagic algorithm. maglim/redmagic sample contains over 10 million/2.5 million galaxies and is divided into six/five photometric redshift bins spanning the range z ∈ [0.20, 1.05]/z ∈ [0.15, 0.90]. Both samples cover 4143 $$\deg ^2$$ over which we perform our analysis blind, measuring the angular correlation function with an S/N ∼ 63 for both samples. In a companion paper, these measurements of galaxy clustering are combined with the correlation functions of cosmic shear and galaxy–galaxy lensing of each sample to place cosmological constraints with a 3 × 2pt analysis. We conduct a thorough study of the mitigation of systematic effects caused by the spatially varying survey properties and we correct the measurements to remove artificial clustering signals. We employ several decontamination methods with different configurations to ensure the robustness of our corrections and to determine the systematic uncertainty that needs to be considered for the final cosmology analyses. We validate our fiducial methodology using lognormal mocks, showing that our decontamination procedure induces biases no greater than 0.5σ in the (Ωm, b) plane, where b is the galaxy bias. 

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