227 Search Results

This work is part of a series establishing the redshift framework for the $3\times 2\mathrm{pt}$ analysis of the Dark Energy Survey Year 6 (DES Y6). For DES Y6, photometric redshift distributions are estimated using self-organizing maps (SOMs), calibrated with spectroscopic and many-band photometric data. To overcome limitations from color-redshift degeneracies and incomplete spectroscopic coverage, we enhance this approach by incorporating clustering-based redshift constraints (clustering-z, or WZ) from angular cross-correlations with BOSS and eBOSS galaxies and eBOSS quasar samples. We define a WZ likelihood and apply importance sampling to a large ensemble of SOM-derived $n\left(z\right)$ realizations, selecting thosemore » consistent with the clustering measurements to produce a posterior sample for each lens and source bin. The analysis uses angular scales corresponding to 1.5–5 Mpc to optimize signal-to-noise ratio while mitigating modeling uncertainties and marginalizes over redshift-dependent galaxy bias and other systematics informed by the N-body simulation cardinal. While a sparser spectroscopic reference sample limits WZ constraining power at $z>1.1$ , particularly for source bins, we demonstrate that combining SOM with WZ improves redshift accuracy and enhances the overall cosmological constraining power of DES Y6. We estimate an improvement in $S_8$ of approximately 10% for cosmic shear and $3\times 2\mathrm{pt}$ analysis, primarily due to the WZ calibration of the source samples.« less

We present a measurement of the angular baryon acoustic oscillation (BAO) scale from the completed Dark Energy Survey (DES) dataset excluding the area of overlap with the Dark Energy Spectroscopic Instrument (DESI). We follow the same methodology and validation process as in the DES Y6 BAO analysis. We interpret the impact of this measurement in the context of the statistical preference for “ $w_0{w}_a$ cold dark matter (CDM) over $\mathrm{\Lambda }\mathrm{CDM}$ when combined with DES Y5 Type Ia supernovae (SN), Planck CMB, and DESI BAO. Based on our previous work,more » using the full Y6 DES BAO sample, in combination with SN, CMB and DESI data release 1 (DR1) BAO, added $0.3\sigma$ in this preference (from $3.7\sigma$ to $4.0\sigma$ ), but this ignored possible correlations between datasets. Using our new DESI-independent DES BAO likelihood instead, we find a smaller increase in the statistical preference for $w_0{w}_a\mathrm{CDM}$ , from $3.7\sigma$ to $3.8\sigma$ when using DESI DR1 BAO, and from $4.0\sigma$ to $4.1\sigma$ when updating to the more recent DESI data release 2 (DR2) BAO. These significances reduce to $3.1\sigma$ when using the new calibrated DES SN-Dovekie. Alongside this work, we publicly release baofit_wtheta, the BAO fitting code for the angular correlation function used in the DES Y6 BAO analysis.« less

We conduct a search for strong gravitational lenses in the Dark Energy Survey (DES) Year 6 imaging data. We implement a pre-trained Vision Transformer (ViT) for our machine learning (ML) architecture and adopt interactive machine learning to construct a training sample with multiple classes to address common types of false positives. Our ML model reduces ∼236 million DES cutout images to 22,564 targets of interest, including ∼85% of previously reported galaxy–galaxy lens candidates discovered in DES. These targets were visually inspected by citizen scientists, who ruled out ∼90% as false positives. Of the remaining 2618 candidates, 149 were expert-classified asmore » “definite” lenses and 516 as “probable” lenses, for a total of 665 systems, with 147 of these candidates being newly identified. Additionally, we trained a second ViT to find double-source plane lens systems, finding at least one double-source system. Our main ViT excels at identifying galaxy–galaxy lenses, consistently assigning high scores to candidates with high expert assessments. The top 800 ViT-scored images include ∼100 of our “definite” lens candidates. This selection is an order of magnitude higher in purity than previous convolutional neural-network-based lens searches and demonstrates the feasibility of applying our methodology for discovering large samples of lenses in future surveys.« less

We present improved cosmological constraints from a re-analysis of the Dark Energy Survey (DES) 5-year sample of Type Ia supernovae (DES-SN5YR). This re-analysis includes an improved photometric cross-calibration, recent white dwarf observations to cross-calibrate between DES and low redshift surveys, retraining the SALT3 light curve model and fixing a numerical approximation in the host galaxy colour law. Our fully recalibrated sample, which we call DES-Dovekie, comprises $$\sim$$1600 likely Type Ia SNe from DES and $$\sim$$200 low-redshift SNe from other surveys. With DES-Dovekie, we obtain $$Ω_{\rm m} = 0.330 \pm 0.015$$ in Flat $$Λ$$CDM which changes $$Ω_{\rm m}$$ by $-0.022$ comparedmore » to DES-SN5YR. Combining DES-Dovekie with CMB data from Planck, ACT and SPT and the DESI DR2 measurements in a Flat $$w_0 w_a$$CDM cosmology, we find $$w_0 = -0.803 \pm 0.054$$, $$w_a = -0.72 \pm 0.21$$. Our results hold a significance of $3.2σ$, reduced from $4.2σ$ for DES-SN5YR, to reject the null hypothesis that the data are compatible with the cosmological constant. This significance is equivalent to a Bayesian model preference odds of approximately 5:1 in favour of the Flat $$w_0 w_a$$CDM model. Using generally accepted thresholds for model preference, our updated data exhibits only a weak preference for evolving dark energy.« less

The properties of Milky Way satellite galaxies have important implications for galaxy formation, reionization, and the fundamental physics of dark matter. However, the population of Milky Way satellites includes the faintest known galaxies, and current observations are incomplete. To understand the impact of observational selection effects on the known satellite population, we perform rigorous, quantitative estimates of the Milky Way satellite galaxy detection efficiency in three wide-field survey datasets: the Dark Energy Survey Year 6, the DECam Local Volume Exploration Data Release 3, and the Pan-STARRS1 Data Release 1. Together, these surveys cover ∼13,600 deg² to g ∼ 24.0 andmore » ∼27,700 deg² to g ∼ 22.5, spanning ∼91% of the high-Galactic-latitude sky (∣b∣ ≥ 15°). We apply multiple detection algorithms over the combined footprint and recover 49 known satellites above a strict census detection threshold. To characterize the sensitivity of our census, we run our detection algorithms on a large set of simulated galaxies injected into the survey data, which allows us to develop models that predict the detectability of satellites as a function of their properties. We then fit an empirical model to our data and infer the luminosity function, radial distribution, and size–luminosity relation of Milky Way satellite galaxies. Our empirical model predicts a total of $$265^{+79}_{-47}$$ satellite galaxies with −20 ≤ M_V ≤ 0, half-light radii of 15 ≤ r_1/2, (pc) ≤ 3000, and galactocentric distances of 10 ≤ D_GC(kpc) ≤ 300. We also identify a mild anisotropy in the angular distribution of the observed galaxies, at a significance of ∼2σ, which can be attributed to the clustering of satellites associated with the LMC.« less

We report the discovery of three Milky Way satellite candidates: Carina IV, Phoenix III, and DELVE 7, in the third data release of the DECam Local Volume Exploration survey (DELVE). The candidate systems were identified by cross-matching results from two independent search algorithms. All three are extremely faint systems composed of old, metal-poor stellar populations (τ ≳ 10 Gyr, [Fe/H] ≲−1.4). Carina IV (M_V = −2.8; r_1/2 = 40 pc) and Phoenix III (M_V = −1.2; r_1/2 = 19 pc) have half-light radii that are consistent with the known population of dwarf galaxies, while DELVE 7 (M_V = 1.2; r_1/2more » = 2 pc) is very compact and seems more likely to be a star cluster, though its nature remains ambiguous without spectroscopic follow-up. The Gaia proper motions of stars in Carina IV ($$M_{\star} = 2250^{+1180}_{-830} M_⊙$$) indicate that it is unlikely to be associated with the LMC, while DECam CaHK photometry confirms that its member stars are metal poor. Phoenix III ($$M_{\star} = 520^{+660}_{-290} M_⊙$$) is the faintest known satellite in the extreme outer stellar halo (D_GC > 100 kpc), while DELVE 7 ($$M_{\star} = 60^{+120}_{-40} M_⊙$$) is the faintest known satellite with D_GC > 20 kpc.« less

The Dark Energy Survey (DES) recently released the final results of its two principal probes of the expansion history: Type Ia supernovae (SNe) and baryonic acoustic oscillations (BAO). In this paper, we explore the cosmological implications of these data in combination with external cosmic microwave background (CMB), big bang nucleosynthesis (BBN), and age-of-the-Universe information. The BAO measurement, which is $\sim 2\sigma$ away from Planck ’s $\mathrm{\Lambda }\mathrm{CDM}$ predictions, pushes for low values of ${\mathrm{\Omega }}_{\mathrm{m}}$ compared to Planck, in contrast to SN which prefers a higher valuemore » than Planck. We identify several tensions among datasets in the $\mathrm{\Lambda }\mathrm{CDM}$ model that cannot be resolved by including either curvature ( $k\mathrm{\Lambda }\mathrm{CDM}$ ) or a constant dark energy equation of state ( $w\mathrm{CDM}$ ). By combining $\mathrm{BAO}+\mathrm{SN}+\mathrm{CMB}$ despite these mild tensions, we obtain ${\mathrm{\Omega }}_k=-{5.5}_{-4.2}^{+4.6}\times {10}^{-3}$ in $k\mathrm{\Lambda }\mathrm{CDM}$ , and $w=-0.948_{-0.027}^{+0.028}$ in $w\mathrm{CDM}$ . In  $w\mathrm{CDM}$ , BAO and SN push again in different directions of parameter space, favoring, respectively, $w<-1$ and $w>-1$ . If we open the parameter space to $w_0{w}_a\mathrm{CDM}$ [where the equation of state of dark energy varies as $w\left(a\right)=w_0+(1-a)w_a$ ], all the datasets are mutually more compatible, and we find concordance in the $[w_0>-1,w_a<0]$ quadrant, with BAO pushing for $w_a<0$ and SN for $[w_0>-1,w_a<0]$ . For DES BAO and SN in combination with Planck -CMB, we find a $3.2\sigma$ deviation from $\mathrm{\Lambda }\mathrm{CDM}$ , with $w_0=-0.673_{-0.097}^{+0.098}$ , $w_a=-1.37_{-0.50}^{+0.51}$ , a Hubble constant of $H_0=67.81_{-0.86}^{+0.96}\mathrm{km}{\mathrm{s}}^{-1}{\mathrm{Mpc}}^{-1}$ , and an abundance of matter of ${\mathrm{\Omega }}_{\mathrm{m}}=0.3109_{-0.0099}^{+0.0086}$ . For the combination of all the background cosmological probes considered (including CMB’s angular acoustic scale ${\theta }_{\star }$ ), we still find a deviation of $2.8\sigma$ from $\mathrm{\Lambda }\mathrm{CDM}$ in the $w_0-w_a$ plane. Assuming a minimal neutrino mass, this work provides tentative evidence for non- $\mathrm{\Lambda }\mathrm{CDM}$ physics, which is consistent with recent claims in support of evolving dark energy, or a source of unknown systematics.« less

We describe the photometric dataset assembled from the full 6 yr of observations by the Dark Energy Survey (DES) in support of static-sky cosmology analyses. DES Y6 Gold is a curated dataset derived from DES Data Release 2 (DR2) that incorporates improved measurement, photometric calibration, object classification and value-added information. Y6 Gold comprises nearly 5000 deg$$^{2}$$ of grizY imaging in the south Galactic cap and includes 669 million objects with a depth of i$$_{AB}$$ ∼ 23.4 mag at a signal-to-noise ratio ∼ 10 for extended objects and a top-of-the-atmosphere photometric uniformity <2 mmag. Y6 Gold augments DES DR2 with simultaneous fits to multiepochmore » photometry for more robust galaxy shapes, colors, and photometric redshift estimates. Y6 Gold features improved morphological star–galaxy classification with an efficiency of 98.6% and a contamination of 0.8% for galaxies with 17.5 < i$$_{AB}$$ < 22.5. Additionally, it includes per-object quality information, and accompanying maps of the footprint coverage, masked regions, imaging depth, survey conditions, and astrophysical foregrounds that are used for cosmology analyses. After quality selections, benchmark samples contain 448 million galaxies and 120 million stars. This publication is complemented by data access and documentation.« less

We present cosmological constraints from Dark Energy Survey Year 3 (DES Y3) weak lensing data using persistent homology, a topological data analysis technique that tracks how features like clusters and voids evolve across density thresholds. For the first time, we apply spherical persistent homology to galaxy survey data through the algorithm TopoS2, which is optimized for curved-sky analyses and HEALPix compatibility. Employing a simulation-based inference framework with the Gower Street simulation suite, specifically designed to mimic DES Y3 data properties, we extract topological summary statistics from convergence maps across multiple smoothing scales and redshift bins. After neural network compression ofmore » these statistics, we estimate the likelihood function and validate our analysis against baryonic feedback effects, finding minimal biases (under $0.3σ$) in the $$Ω_\mathrm{m}-S_8$$ plane. Assuming the $$w$$CDM model, our combined Betti numbers and second moments analysis yields $$S_8 = 0.821 \pm 0.018$$ and $$Ω_\mathrm{m} = 0.304\pm0.037$$-constraints 70% tighter than those from cosmic shear two-point statistics in the same parameter plane. Our results demonstrate that topological methods provide a powerful and robust framework for extracting cosmological information, with our spherical methodology readily applicable to upcoming Stage IV wide-field galaxy surveys.« less

Galaxy clusters provide a unique probe of the late-time cosmic structure and serve as a powerful independent test of the Λ⁢CDM model. This work presents the first set of cosmological constraints derived with ∼16,000 optically selected redMaPPer clusters across nearly 5000 deg² using DES year 3 datasets. Our analysis leverages a consistent modeling framework for galaxy cluster cosmology and DES-Y3 joint analyses of galaxy clustering and weak lensing (3 × 2⁢pt), ensuring direct comparability with the DES-Y3 3 × 2⁢pt analysis. Here, we obtain constraints of 𝑆₈ = 0.864 ± 0.035 and Ω_m = $$0.26⁢5^{+0.019}_{−0.031}$$ from the cluster-based data vector.more » We find that cluster constraints and 3 × 2⁢pt constraints are consistent under the Λ⁢CDM model with a posterior predictive distribution (PPD) value of 0.53. The consistency between clusters and 3 × 2⁢pt provides a stringent test of Λ⁢CDM across different mass and spatial scales. Jointly analyzing clusters with 3 × 2⁢pt further improves cosmological constraints, yielding 𝑆₈ = $$0.81⁢1^{+0.022}_{−0.020}$$ and Ω_m = $$0.29⁢4^{+0.022}_{−0.033}$$, a 24% improvement in the Ω_m − 𝑆₈ figure of merit over 3 × 2⁢pt alone. Moreover, we find no significant deviation from the Planck CMB constraints with a probability to exceed (PTE) value of 0.6, significantly reducing previous 𝑆₈ tension claims. Finally, combining DES 3 × 2⁢pt, DES clusters, and Planck CMB places an upper limit on the sum of neutrino masses of ∑𝑚_𝜈 < 0.26 eV at 95% confidence under the Λ⁢CDM model. These results establish optically selected clusters as a key cosmological probe and pave the way for cluster-based analyses in upcoming stage-IV surveys such as LSST, Euclid, and Roman.« less