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A. Ferté

Publications and source records attributed to A. Ferté.

At least 37 records · Page 2Linked to original sources

Dark Energy Survey Year 3 Results: Cosmological constraints from second and third-order shear statistics

We present a cosmological analysis of the third-order aperture mass statistic using Dark Energy Survey Year 3 (DES Y3) data. We perform a complete tomographic measurement of the three-point correlation function of the Y3 weak lensing shape catalog with the four fiducial source redshift bins. Building upon our companion methodology paper, we apply a pipeline that combines the two-point function $ξ_{\pm}$ with the mass aperture skewness statistic $\langle M_{\rm ap}^3\rangle$, which is an efficient compression of the full shear three-point function. We use a suite of simulated shear maps to obtain a joint covariance matrix. By jointly analyzing $ξ_\pm$ and $\langle M_{\rm ap}^3\rangle$ measured from DES Y3 data with a $Λ$CDM model, we find $S_8=0.780\pm0.015$ and $Ω_{\rm m}=0.266^{+0.039}_{-0.040}$, yielding 111% of figure-of-merit improvement in $Ω_m$-$S_8$ plane relative to $ξ_{\pm}$ alone, consistent with expectations from simulated likelihood analyses. With a $w$CDM model, we find $S_8=0.749^{+0.027}_{-0.026}$ and $w_0=-1.39\pm 0.31$, which gives an improvement of $22\%$ on the joint $S_8$-$w_0$ constraint. Our results are consistent with $w_0=-1$. Our new constraints are compared to CMB data from the Planck satellite, and we find that with the inclusion of $\langle M_{\rm ap}^3\rangle$ the existing tension between the data sets is at the level of $2.3σ$. We show that the third-order statistic enables us to self-calibrate the mean photometric redshift uncertainty parameter of the highest redshift bin with little degradation in the figure of merit. Our results demonstrate the constraining power of higher-order lensing statistics and establish $\langle M_{\rm ap}^3\rangle$ as a practical observable for joint analyses in current and future surveys.

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Dark Energy Survey Year 3 results: $w$CDM cosmology from simulation-based inference with persistent homology on the sphere

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 of 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.

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The Dark Energy Survey: Cosmology Results With ~1500 New High-redshift Type Ia Supernovae Using The Full 5-year Dataset

We present cosmological constraints from the sample of Type Ia supernovae (SN Ia) discovered during the full five years of the Dark Energy Survey (DES) Supernova Program. In contrast to most previous cosmological samples, in which SN are classified based on their spectra, we classify the DES SNe using a machine learning algorithm applied to their light curves in four photometric bands. Spectroscopic redshifts are acquired from a dedicated follow-up survey of the host galaxies. After accounting for the likelihood of each SN being a SN Ia, we find 1635 DES SNe in the redshift range $0.10 0.5$ SNe compared to the previous leading compilation of Pantheon+, and results in the tightest cosmological constraints achieved by any SN data set to date. To derive cosmological constraints we combine the DES supernova data with a high-quality external low-redshift sample consisting of 194 SNe Ia spanning $0.025<z<0.10$. Using SN data alone and including systematic uncertainties we find $Ω_{\rm M}=0.352\pm 0.017$ in flat $Λ$CDM. Supernova data alone now require acceleration ($q_0<0$ in $Λ$CDM) with over $5σ$ confidence. We find $(Ω_{\rm M},w)=(0.264^{+0.074}_{-0.096},-0.80^{+0.14}_{-0.16})$ in flat $w$CDM. For flat $w_0w_a$CDM, we find $(Ω_{\rm M},w_0,w_a)=(0.495^{+0.033}_{-0.043},-0.36^{+0.36}_{-0.30},-8.8^{+3.7}_{-4.5})$. Including Planck CMB data, SDSS BAO data, and DES $3\times2$-point data gives $(Ω_{\rm M},w)=(0.321\pm0.007,-0.941\pm0.026)$. In all cases dark energy is consistent with a cosmological constant to within $\sim2σ$. In our analysis, systematic errors on cosmological parameters are subdominant compared to statistical errors; paving the way for future photometrically classified supernova analyses.

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Constraints on cosmology and baryonic feedback with joint analysis of Dark Energy Survey Year 3 lensing data and ACT DR6 thermal Sunyaev-Zel'dovich effect observations

We present a joint analysis of weak gravitational lensing (shear) data obtained from the first three years of observations by the Dark Energy Survey and thermal Sunyaev-Zel'dovich (tSZ) effect measurements from a combination of Atacama Cosmology Telescope (ACT) and Planck data. A combined analysis of shear (which traces the projected mass) with the tSZ effect (which traces the projected gas pressure) can jointly probe both the distribution of matter and the thermodynamic state of the gas, accounting for the correlated effects of baryonic feedback on both observables. We detect the shear$~\times~$tSZ cross-correlation at a 21$σ$ significance, the highest to date, after minimizing the bias from cosmic infrared background leakage in the tSZ map. By jointly modeling the small-scale shear auto-correlation and the shear$~\times~$tSZ cross-correlation, we obtain $S_8 = 0.811^{+0.015}_{-0.012}$ and $Ω_{\rm m} = 0.263^{+0.023}_{-0.030}$, results consistent with primary CMB analyses from Planck and P-ACT. We find evidence for reduced thermal gas pressure in dark matter halos with masses $M < 10^{14} \, M_{\odot}/h$, supporting predictions of enhanced feedback from active galactic nuclei on gas thermodynamics. A comparison of the inferred matter power suppression reveals a $2-4σ$ tension with hydrodynamical simulations that implement mild baryonic feedback, as our constraints prefer a stronger suppression. Finally, we investigate biases from cosmic infrared background leakage in the tSZ-shear cross-correlation measurements, employing mitigation techniques to ensure a robust inference. Our code is publicly available on GitHub.

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Dark Energy Survey Year 6 Results: Synthetic-source Injection Across the Full Survey Using Balrog

Synthetic source injection (SSI), the insertion of sources into pixel-level on-sky images, is a powerful method for characterizing object detection and measurement in wide-field, astronomical imaging surveys. Within the Dark Energy Survey (DES), SSI plays a critical role in characterizing all necessary algorithms used in converting images to catalogs, and in deriving quantities needed for the cosmology analysis, such as object detection rates, galaxy redshift estimation, galaxy magnification, star-galaxy classification, and photometric performance. We present here a source injection catalog of $146$ million injections spanning the entire 5000 deg$^2$ DES footprint, generated using the Balrog SSI pipeline. Through this sample, we demonstrate that the DES Year 6 (Y6) image processing pipeline provides accurate estimates of the object properties, for both galaxies and stars, at the percent-level, and we highlight specific regimes where the accuracy is reduced. We then show the consistency between SSI and data catalogs, for all galaxy samples developed within the weak lensing and galaxy clustering analyses of DES Y6. The consistency between the two catalogs also extends to their correlations with survey observing properties (seeing, airmass, depth, extinction, etc.). Finally, we highlight a number of applications of this catalog to the DES Y6 cosmology analysis. This dataset is the largest SSI catalog produced at this fidelity and will serve as a key testing ground for exploring the utility of SSI catalogs in upcoming surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time.

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High-Significance Detection of Correlation Between the Unresolved Gamma-Ray Background and the Large Scale Cosmic Structure

Our understanding of the $γ$-ray sky has improved dramatically in the past decade, however, the unresolved $γ$-ray background (UGRB) still has a potential wealth of information about the faintest $γ$-ray sources pervading the Universe. Statistical cross-correlations with tracers of cosmic structure can indirectly identify the populations that most characterize the $γ$-ray background. In this study, we analyze the angular correlation between the $γ$-ray background and the matter distribution in the Universe as traced by gravitational lensing, leveraging more than a decade of observations from the Fermi-Large Area Telescope (LAT) and 3 years of data from the Dark Energy Survey (DES). We detect a correlation at signal-to-noise ratio of 8.9. Most of the statistical significance comes from large scales, demonstrating, for the first time, that a substantial portion of the UGRB aligns with the mass clustering of the Universe as traced by weak lensing. Blazars provide a plausible explanation for this signal, especially if those contributing to the correlation reside in halos of large mass ($\sim 10^{14} M_{\odot}$) and account for approximately 30-40 % of the UGRB above 10 GeV. Additionally, we observe a preference for a curved $γ$-ray energy spectrum, with a log-parabolic shape being favored over a power-law. We also discuss the possibility of modifications to the blazar model and the inclusion of additional $gamma$-ray sources, such as star-forming galaxies or particle dark matter.

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Dark Energy Survey Year 6 Results: Point-spread Function Modeling

We present the point-spread function (PSF) modeling for weak lensing shear measurement using the full six years of the Dark Energy Survey (DES Y6) data. We review the PSF estimation procedure using the PIFF (PSFs In the Full FOV) software package and describe the key improvements made to PIFF and modeling diagnostics since the DES year three (Y3) analysis: (i) use of external Gaia and infrared photometry catalogs to ensure higher purity of the stellar sample used for model fitting, (ii) addition of color-dependent PSF modeling, the first for any weak lensing analysis, and (iii) inclusion of model diagnostics inspecting fourth-order moments, which can bias weak lensing measurements to a similar degree as second-order modeling errors. Through a comprehensive set of diagnostic tests, we demonstrate the improved accuracy of the Y6 models evident in significantly smaller systematic errors than those of the Y3 analysis, in which all $g$ band data were excluded due to insufficiently accurate PSF models. For the Y6 weak lensing analysis, we include $g$ band photometry data in addition to the $riz$ bands, providing a fourth band for photometric redshift estimation. Looking forward to the next generation of wide-field surveys, we describe several ongoing improvements to PIFF, which will be the default PSF modeling software for weak lensing analyses for the Vera C. Rubin Observatory's Legacy Survey of Space and Time.

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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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Dark Energy Survey Year 3 Results: Cosmological Constraints from Cluster Abundances, Weak Lensing, and Galaxy Clustering

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 5,000 $\rm{deg}^2$ using DES Year 3 data sets. Our analysis leverages a consistent modeling framework for galaxy cluster cosmology and DES-Y3 joint analyses of galaxy clustering and weak lensing (3x2pt), ensuring direct comparability with the DES-Y3 3x2pt analysis. We obtain constraints of $S_8 = 0.864 \pm 0.035$ and $Ω_{\rm{m}} = 0.265^{+0.019}_{-0.031}$ from the cluster-based data vector. We find that cluster constraints and 3x2pt constraints are consistent under the $Λ$CDM model with a Posterior Predictive Distribution (PPD) value of $0.53$. The consistency between clusters and 3x2pt provides a stringent test of $Λ$CDM across different mass and spatial scales. Jointly analyzing clusters with 3x2pt further improves cosmological constraints, yielding $S_8 = 0.811^{+0.022}_{-0.020}$ and $Ω_{\rm{m}} = 0.294^{+0.022}_{-0.033}$, a $24\%$ improvement in the $Ω_{\rm{m}}-S_8$ figure-of-merit over 3x2pt 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 $S_8$ tension claims. Finally, combining DES 3x2pt, DES clusters, and Planck CMB places an upper limit on the sum of neutrino masses of $\sum m_ν< 0.26$ 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.

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Multiprobe Cosmology from the Abundance of SPT Clusters and DES Galaxy Clustering and Weak Lensing

Cosmic shear, galaxy clustering, and the abundance of massive halos each probe the large-scale structure of the Universe in complementary ways. We present cosmological constraints from the joint analysis of the three probes, building on the latest analyses of the lensing-informed abundance of clusters identified by the South Pole Telescope (SPT) and of the auto- and cross-correlation of galaxy position and weak lensing measurements (3$\times$2pt) in the Dark Energy Survey (DES). We consider the cosmological correlation between the different tracers and we account for the systematic uncertainties that are shared between the large-scale lensing correlation functions and the small-scale lensing-based cluster mass calibration. Marginalized over the remaining $Λ$ cold dark matter ($Λ$CDM) parameters (including the sum of neutrino masses) and 52 astrophysical modeling parameters, we measure $Ω_\mathrm{m}=0.300\pm0.017$ and $σ_8=0.797\pm0.026$. Compared to constraints from Planck primary cosmic microwave background (CMB) anisotropies, our constraints are only 15% wider with a probability to exceed of 0.22 ($1.2σ$) for the two-parameter difference. We further obtain $S_8\equivσ_8(Ω_\mathrm{m}/0.3)^{0.5}=0.796\pm0.013$ which is lower than the Planck measurement at the $1.6σ$ level. The combined SPT cluster, DES 3$\times$2pt, and Planck datasets mildly prefer a nonzero positive neutrino mass, with a 95% upper limit $\sum m_ν<0.25~\mathrm{eV}$ on the sum of neutrino masses. Assuming a $w$CDM model, we constrain the dark energy equation of state parameter $w=-1.15^{+0.23}_{-0.17}$ and when combining with Planck primary CMB anisotropies, we recover $w=-1.20^{+0.15}_{-0.09}$, a $1.7σ$ difference with a cosmological constant. The precision of our results highlights the benefits of multiwavelength multiprobe cosmology.

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Dark Energy Survey Year 6 Results: Photometric Data Set for Cosmology

We describe the photometric data set assembled from the full six years of observations by the Dark Energy Survey (DES) in support of static-sky cosmology analyses. DES Y6 Gold is a curated data set derived from DES Data Release 2 (DR2) that incorporates improved measurement, photometric calibration, object classification and value added information. Y6 Gold comprises nearly $5000~{\rm deg}^2$ of $grizY$ imaging in the south Galactic cap and includes 669 million objects with a depth of $i_{AB} \sim 23.4$ mag at S/N $\sim 10$ for extended objects and a top-of-the-atmosphere photometric uniformity $< 2~{\rm mmag}$. Y6 Gold augments DES DR2 with simultaneous fits to multi-epoch photometry for more robust galaxy shapes, colors, and photometric redshift estimates. Y6 Gold features improved morphological star-galaxy classification with efficiency $98.6\%$ and contamination $0.8\%$ 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 paper will be complemented by online data access and documentation.

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Dark Energy Survey Year 3: Blue Shear

Modeling the intrinsic alignment (IA) of galaxies poses a challenge to weak lensing analyses. The Dark Energy Survey is expected to be less impacted by IA when limited to blue, star-forming galaxies. The cosmological parameter constraints from this blue cosmic shear sample are stable to IA model choice, unlike passive galaxies in the full DES Y3 sample, the goodness-of-fit is improved and the $Ω_{m}$ and $S_8$ better agree with the cosmic microwave background. Mitigating IA with sample selection, instead of flexible model choices, can reduce uncertainty in $S_8$ by a factor of 1.5.

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Weak Gravitational Lensing around Low Surface Brightness Galaxies in the DES Year 3 Data

We present galaxy-galaxy lensing measurements using a sample of low surface brightness galaxies (LSBGs) drawn from the Dark Energy Survey Year 3 (Y3) data as lenses. LSBGs are diffuse galaxies with a surface brightness dimmer than the ambient night sky. These dark-matter-dominated objects are intriguing due to potentially unusual formation channels that lead to their diffuse stellar component. Given the faintness of LSBGs, using standard observational techniques to characterize their total masses proves challenging. Weak gravitational lensing, which is less sensitive to the stellar component of galaxies, could be a promising avenue to estimate the masses of LSBGs. Our LSBG sample consists of 23,790 galaxies separated into red and blue color types at $g-i\ge 0.60$ and $g-i< 0.60$, respectively. Combined with the DES Y3 shear catalog, we measure the tangential shear around these LSBGs and find signal-to-noise ratios of 6.67 for the red sample, 2.17 for the blue sample, and 5.30 for the full sample. We use the clustering redshifts method to obtain redshift distributions for the red and blue LSBG samples. Assuming all red LSBGs are satellites, we fit a simple model to the measurements and estimate the host halo mass of these LSBGs to be $\log(M_{\rm host}/M_{\odot}) = 12.98 ^{+0.10}_{-0.11}$. We place a 95% upper bound on the subhalo mass at $\log(M_{\rm sub}/M_{\odot})<11.51$. By contrast, we assume the blue LSBGs are centrals, and place a 95% upper bound on the halo mass at $\log(M_\mathrm{host}/M_\odot) < 11.84$. We find that the stellar-to-halo mass ratio of the LSBG samples is consistent with that of the general galaxy population. This work illustrates the viability of using weak gravitational lensing to constrain the halo masses of LSBGs.

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SPT Clusters with DES and HST Weak Lensing. I. Cluster Lensing and Bayesian Population Modeling of Multi-Wavelength Cluster Datasets

We present a Bayesian population modeling method to analyze the abundance of galaxy clusters identified by the South Pole Telescope (SPT) with a simultaneous mass calibration using weak gravitational lensing data from the Dark Energy Survey (DES) and the Hubble Space Telescope (HST). We discuss and validate the modeling choices with a particular focus on a robust, weak-lensing-based mass calibration using DES data. For the DES Year 3 data, we report a systematic uncertainty in weak-lensing mass calibration that increases from 1% at $z=0.25$ to 10% at $z=0.95$, to which we add 2% in quadrature to account for uncertainties in the impact of baryonic effects. We implement an analysis pipeline that joins the cluster abundance likelihood with a multi-observable likelihood for the Sunyaev-Zel'dovich effect, optical richness, and weak-lensing measurements for each individual cluster. We validate that our analysis pipeline can recover unbiased cosmological constraints by analyzing mocks that closely resemble the cluster sample extracted from the SPT-SZ, SPTpol ECS, and SPTpol 500d surveys and the DES Year 3 and HST-39 weak-lensing datasets. This work represents a crucial prerequisite for the subsequent cosmological analysis of the real dataset.

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SPT Clusters with DES and HST Weak Lensing. II. Cosmological Constraints from the Abundance of Massive Halos

We present cosmological constraints from the abundance of galaxy clusters selected via the thermal Sunyaev-Zel'dovich (SZ) effect in South Pole Telescope (SPT) data with a simultaneous mass calibration using weak gravitational lensing data from the Dark Energy Survey (DES) and the Hubble Space Telescope (HST). The cluster sample is constructed from the combined SPT-SZ, SPTpol ECS, and SPTpol 500d surveys, and comprises 1,005 confirmed clusters in the redshift range $0.25-1.78$ over a total sky area of 5,200 deg$^2$. We use DES Year 3 weak-lensing data for 688 clusters with redshifts $z<0.95$ and HST weak-lensing data for 39 clusters with $0.6<z<1.7$. The weak-lensing measurements enable robust mass measurements of sample clusters and allow us to empirically constrain the SZ observable--mass relation. For a flat $Λ$CDM cosmology, and marginalizing over the sum of massive neutrinos, we measure $Ω_\mathrm{m}=0.286\pm0.032$, $σ_8=0.817\pm0.026$, and the parameter combination $σ_8\,(Ω_\mathrm{m}/0.3)^{0.25}=0.805\pm0.016$. Our measurement of $S_8\equivσ_8\,\sqrt{Ω_\mathrm{m}/0.3}=0.795\pm0.029$ and the constraint from Planck CMB anisotropies (2018 TT,TE,EE+lowE) differ by $1.1σ$. In combination with that Planck dataset, we place a 95% upper limit on the sum of neutrino masses $\sum m_ν<0.18$ eV. When additionally allowing the dark energy equation of state parameter $w$ to vary, we obtain $w=-1.45\pm0.31$ from our cluster-based analysis. In combination with Planck data, we measure $w=-1.34^{+0.22}_{-0.15}$, or a $2.2σ$ difference with a cosmological constant. We use the cluster abundance to measure $σ_8$ in five redshift bins between 0.25 and 1.8, and we find the results to be consistent with structure growth as predicted by the $Λ$CDM model fit to Planck primary CMB data.

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Dark Energy Survey Year 3 Results: Cosmology from galaxy clustering and galaxy-galaxy lensing in harmonic space

We present the joint tomographic analysis of galaxy-galaxy lensing and galaxy clustering in harmonic space, using galaxy catalogues from the first three years of observations by the Dark Energy Survey (DES Y3). We utilise the redMaGiC and MagLim catalogues as lens galaxies and the METACALIBRATION catalogue as source galaxies. The measurements of angular power spectra are performed using the pseudo-$C_\ell$ method, and our theoretical modelling follows the fiducial analyses performed by DES Y3 in configuration space, accounting for galaxy bias, intrinsic alignments, magnification bias, shear magnification bias and photometric redshift uncertainties. We explore different approaches for scale cuts based on non-linear galaxy bias and baryonic effects contamination. Our fiducial covariance matrix is computed analytically, accounting for mask geometry in the Gaussian term, and including non-Gaussian contributions and super-sample covariance terms. To validate our harmonic space pipelines and covariance matrix, we used a suite of 1800 log-normal simulations. We also perform a series of stress tests to gauge the robustness of our harmonic space analysis. In the $Λ$CDM model, the clustering amplitude $S_8 =σ_8(Ω_m/0.3)^{0.5}$ is constrained to $S_8 = 0.704\pm 0.029$ and $S_8 = 0.753\pm 0.024$ ($68\%$ C.L.) for the redMaGiC and MagLim catalogues, respectively. For the $w$CDM, the dark energy equation of state is constrained to $w = -1.28 \pm 0.29$ and $w = -1.26^{+0.34}_{-0.27}$, for redMaGiC and MagLim catalogues, respectively. These results are compatible with the corresponding DES Y3 results in configuration space and pave the way for harmonic space analyses using the DES Y6 data.

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Dark Energy Survey Year 3 results: likelihood-free, simulation-based $w$CDM inference with neural compression of weak-lensing map statistics

We present simulation-based cosmological $w$CDM inference using Dark Energy Survey Year 3 weak-lensing maps, via neural data compression of weak-lensing map summary statistics: power spectra, peak counts, and direct map-level compression/inference with convolutional neural networks (CNN). Using simulation-based inference, also known as likelihood-free or implicit inference, we use forward-modelled mock data to estimate posterior probability distributions of unknown parameters. This approach allows all statistical assumptions and uncertainties to be propagated through the forward-modelled mock data; these include sky masks, non-Gaussian shape noise, shape measurement bias, source galaxy clustering, photometric redshift uncertainty, intrinsic galaxy alignments, non-Gaussian density fields, neutrinos, and non-linear summary statistics. We include a series of tests to validate our inference results. This paper also describes the Gower Street simulation suite: 791 full-sky PKDGRAV dark matter simulations, with cosmological model parameters sampled with a mixed active-learning strategy, from which we construct over 3000 mock DES lensing data sets. For $w$CDM inference, for which we allow $-1<w<-\frac{1}{3}$, our most constraining result uses power spectra combined with map-level (CNN) inference. Using gravitational lensing data only, this map-level combination gives $Ω_{\rm m} = 0.283^{+0.020}_{-0.027}$, ${S_8 = 0.804^{+0.025}_{-0.017}}$, and $w < -0.80$ (with a 68 per cent credible interval); compared to the power spectrum inference, this is more than a factor of two improvement in dark energy parameter ($Ω_{\rm DE}, w$) precision.

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Dark Energy Survey: A 2.1% measurement of the angular Baryonic Acoustic Oscillation scale at redshift $z_{\rm eff}$=0.85 from the final dataset

We present the angular diameter distance measurement obtained with the Baryonic Acoustic Oscillation feature from galaxy clustering in the completed Dark Energy Survey, consisting of six years (Y6) of observations. We use the Y6 BAO galaxy sample, optimized for BAO science in the redshift range 0.6<$z$<1.2, with an effective redshift at $z_{\rm eff}$=0.85 and split into six tomographic bins. The sample has nearly 16 million galaxies over 4,273 square degrees. Our consensus measurement constrains the ratio of the angular distance to sound horizon scale to $D_M(z_{\rm eff})/r_d$ = 19.51$\pm$0.41 (at 68.3% confidence interval), resulting from comparing the BAO position in our data to that predicted by Planck $Λ$CDM via the BAO shift parameter $α=(D_M/r_d)/(D_M/r_d)_{\rm Planck}$. To achieve this, the BAO shift is measured with three different methods, Angular Correlation Function (ACF), Angular Power Spectrum (APS), and Projected Correlation Function (PCF) obtaining $α=$ 0.952$\pm$0.023, 0.962$\pm$0.022, and 0.955$\pm$0.020, respectively, which we combine to $α=$ 0.957$\pm$0.020, including systematic errors. When compared with the $Λ$CDM model that best fits Planck data, this measurement is found to be 4.3% and 2.1$σ$ below the angular BAO scale predicted. To date, it represents the most precise angular BAO measurement at $z$>0.75 from any survey and the most precise measurement at any redshift from photometric surveys. The analysis was performed blinded to the BAO position and it is shown to be robust against analysis choices, data removal, redshift calibrations and observational systematics.

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