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A. Porredon

Publications and source records attributed to A. Porredon.

At least 19 recordsLinked to original sources

Infrared-enhanced Photometric Redshifts for the Dark Energy Survey Y6 Gold catalogue

The Dark Energy Survey (DES) provides optical data across 5000 square degrees of the southern sky, enabling a broad range of extragalactic and cosmological studies. Combining DES data with infrared surveys offers the opportunity to improve its photometric redshift (photo-z) estimates. We aim to investigate improvements in photometric redshift estimation achieved by combining DES optical data with infrared measurements from the VISTA Hemisphere Survey (VHS) and the Wide-field Infrared Survey Explorer (WISE), and release an updated version of the catalogue. We performed a positional sky cross-match between the DES Y6 Gold catalogue matched to a spectroscopic dataset, the 2013 AllWISE Data Release, and VHS Data Release 5, in order to test these improvements using the Directional Neighbourhood Fitting (DNF) algorithm (Y6 Gold catalogue reference estimator). We additionally matched it to the unWISE catalogue to verify the performance against this deeper dataset. Adding infrared data reduces all the metrics (scatter, bias and outlier fraction) in photo-z estimates, particularly at higher redshifts in comparison with only using optical data from DES. The obtained results are globally better for the DES+WISE sample, with improvements that are statistically significant. On the other hand, the addition of the VHS bands to available depth is only marginal. The combined use of DES and WISE W1 and W2 data improves the photometric redshift metrics analysed here. The addition of VHS data at the DES and VHS depths explored here does not provide any further improvement at z less than 1.5, indicating that, under these constraints, WISE data may already capture the key infrared features and depth needed for accurate photo-z estimation. In addition, low signal-to-noise (less than 10) infrared data does not contribute to any improvement beyond the DES optical dataset.

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Dark Energy Survey Year 3 results: optimized $w$CDM simulation-based inference with weak lensing map-level hybrid statistics

We present cosmological constraints from the Dark Energy Survey Year 3 (DES Y3) weak lensing data using hierarchical hybrid statistics within a Bayesian simulation-based inference framework that is based on the Gower Street simulations. To maximize the precision of the inference, we have developed a new, information-theory based, data compression of the weak lensing maps to just seven highly informative summary statistics. The hybrid scheme exploits the high information content of the power spectrum, compressing both the power spectrum and neural-based summaries that are designed to extract further information. Our simulation-based approach enables principled forward modelling of all major sources of systematic uncertainty and survey properties into realistic mock observations, including the survey mask, photometric redshift uncertainties, intrinsic galaxy alignments, multiplicative shear calibration bias, source galaxy clustering, non-Gaussian shape noise, and non-linear structure formation. The summary statistics are then used in a Bayesian simulation-based inference pipeline. The inference is validated through coverage tests and checks for robustness against baryonic feedback. Assuming a $w$CDM cosmology, our analysis yields $S_8 = 0.808 \pm 0.017$, $\Omega_{\rm m} = 0.325 \pm 0.024$, and $w < -0.766$ (marginalized posterior 68 per cent credible intervals). This rigorous combination of information theory, physics- and neural network-based extreme data compression, and principled Bayesian analysis improves the figure of merit for $(\Omega_{\rm m}, S_8, w)$ by 60 per cent over the previous state-of-the-art, and by almost a factor of 3 over two-point analyses of the same data. They are the most precise joint constraints on $(\Omega_{\rm m}, S_8, w)$ from weak gravitational lensing data alone of any survey to date. We intend to apply this analysis to the more recent DES Y6 data.

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Euclid preparation. Impact of redshift distribution uncertainties on the joint analysis of photometric galaxy clustering and weak gravitational lensing

One of the $\textit{Euclid}$ mission's key projects is the so-called 3$\times$2pt analysis, that is, the combination of cosmic shear, photometric galaxy clustering, and galaxy-galaxy lensing. Although $\textit{Euclid}$ has established quality requirements for the photo-$z$ accuracy needed for the weak lensing galaxy sample, no such requirements have been set for the photometric clustering sample. In this paper, we investigate the impact of redshift uncertainties on $\textit{Euclid}$'s photometric galaxy clustering analysis and its combination with weak gravitational lensing, focusing on data release 1 (DR1). In particular, we study whether having precise knowledge of the mean of the redshift distributions per bin is sufficient to avoid biases in the resulting cosmological constraints or whether accuracy in the higher-order moments of the distribution is required. We evaluate the results based on their constraining power on $w_{\mathrm{0}}$ and $w_{a}$ and define thresholds for the precision and accuracy of $\textit{Euclid}$'s redshift distribution of the photometric clustering sample. We find that the redshift distributions of the photometric clustering sample must be known at an accuracy of 0.004(1+$z$) in the mean in order to recover 80$\%$ of the constraining power in $\textit{Euclid}$'s DR1 $w_{\mathrm{0}}w_{a}$CDM 3$\times$2pt analysis. The impact of the uncertainty on the width is negligible, provided the mean redshift is constrained with sufficient accuracy. For most sources of redshift distribution error, attaining the requirement on the mean will also reduce uncertainty in the width well below the required level.

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DELVE Milky Way Satellite Galaxy Census I: Satellite Population and Survey Selection Function in DES, DELVE, and Pan-STARRS

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 $\sim$13,600 deg$^2$ to $g \sim 24.0$ and $\sim$27,700 deg$^2$ to $g \sim 22.5$, spanning $\sim$91% of the high-Galactic-latitude sky ($|b| \geq 15^\circ$). 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 $-20 \leq M_V \leq 0$, half-light radii of $15 \leq r_{1/2} (\rm pc) \leq 3000$, and galactocentric distances of $10 \leq D_{\rm GC} (\rm kpc) \leq 300$. We also identify a mild anisotropy in the angular distribution of the observed galaxies, at a significance of $\sim$$2σ$, which can be attributed to the clustering of satellites associated with the LMC.

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Ultra-Faint Milky Way Satellites Discovered in Carina, Phoenix, and Telescopium with DELVE Data Release 3

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 ($τ\gtrsim 10$ Gyr, [Fe/H] $ \lesssim -1.4$). Carina IV ($M_V = -2.8;\ r_{1/2} = 40 {\rm pc}$) and Phoenix III ($M_V = -1.2;\ r_{1/2} = 19 {\rm pc}$) have half-light radii that are consistent with the known population of dwarf galaxies, while DELVE 7 ($M_V = 1.2;\ r_{1/2} = 2 {\rm pc}$) is very compact and seems more likely to be a star cluster, though its nature remains ambiguous without spectroscopic followup. The Gaia proper motions of stars in Carina IV ($M_* = 2250^{+1180}_{-830} {\rm M_\odot}$) indicate that it is unlikely to be associated with the LMC, while DECam CaHK photometry confirms that its member stars are metal-poor. Phoenix III ($M_* = 520^{+660}_{-290} {\rm M_\odot}$) is the faintest known satellite in the extreme outer stellar halo ($D_{\rm GC} > 100$ kpc), while DELVE 7 ($M_* = 60^{+120}_{-40} {\rm M_\odot}$) is the faintest known satellite with $D_{\rm GC} > 20$ kpc.

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Dark Energy Survey Year 6 Results: Clustering-redshifts and importance sampling of Self-Organised-Maps $n(z)$ realizations for $3\times2$pt samples

This work is part of a series establishing the redshift framework for the $3\times2$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 $n(z)$ realizations, selecting those consistent with the clustering measurements to produce a posterior sample for each lens and source bin. The analysis uses angular scales of 1.5-5 Mpc to optimize signal-to-noise 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 SOMPZ 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 $3\times2$pt analysis, primarily due to the WZ calibration of the source samples.

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Euclid preparation. CIV. Impact of galaxy intrinsic alignment modelling choices on Euclid 3x2pt cosmology

The Euclid galaxy survey will provide unprecedented constraints on cosmology, but achieving unbiased results will require an optimal characterisation and mitigation of systematic effects. The intrinsic alignments (IAs) of galaxies are one of the dominant contaminants of the weak lensing (WL) and galaxy-galaxy lensing (GGL) probes. In this work, we assess IA modelling choices for Euclid DR1 3x2pt analyses by using synthetic data vectors and comparing the performance of the two most commonly used IA models, non-linear alignment (NLA) and tidal alignment tidal torquing (TATT), along with several variations. Our analyses combine three perspectives: (i) the constraining power on the IA and cosmological parameters for each IA model, (ii) the bias that results when the IA analysis model differs from the model used to generate the synthetic data vector, and (iii) the degeneracies between IAs and photometric redshift (photo-z) nuisance parameters. Amongst the IA models analysed, the redshift-dependent TATT model (zTATT) provides the most flexible description of IAs, with a constraining power similar to simpler IA models, making it a suitable choice for Euclid DR1 3x2pt analyses.

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Dark Energy Survey Year 3 results: Simulation-based $w$CDM inference from weak lensing and galaxy clustering maps with deep learning: Analysis design

Data-driven approaches using deep learning are emerging as powerful techniques to extract non-Gaussian information from cosmological large-scale structure. This work presents the first simulation-based inference (SBI) pipeline that combines weak lensing and galaxy clustering maps in a realistic Dark Energy Survey Year 3 (DES Y3) configuration and serves as preparation for a forthcoming analysis of the survey data. We develop a scalable forward model based on the CosmoGridV1 suite of N-body simulations to generate over one million self-consistent mock realizations of DES Y3 at the map level. Leveraging this large dataset, we train deep graph convolutional neural networks on the full survey footprint in spherical geometry to learn low-dimensional features that approximately maximize mutual information with target parameters. These learned compressions enable neural density estimation of the implicit likelihood via normalizing flows in a ten-dimensional parameter space spanning cosmological $w$CDM, intrinsic alignment, and linear galaxy bias parameters, while marginalizing over baryonic, photometric redshift, and shear bias nuisances. To ensure robustness, we extensively validate our inference pipeline using synthetic observations derived from both systematic contaminations in our forward model and independent Buzzard galaxy catalogs. Our forecasts yield significant improvements in cosmological parameter constraints, achieving $2-3\times$ higher figures of merit in the $Ω_m - S_8$ plane relative to our implementation of baseline two-point statistics and effectively breaking parameter degeneracies through probe combination. These results demonstrate the potential of SBI analyses powered by deep learning for upcoming Stage-IV wide-field imaging surveys.

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Dark Energy Survey: Galaxy Sample for the Baryonic Acoustic Oscillation Measurement from the Final Dataset

In this paper we present and validate the galaxy sample used for the analysis of the baryon acoustic oscillation (BAO) signal in the Dark Energy Survey (DES) Y6 data. The definition is based on a color and redshift-dependent magnitude cut optimized to select galaxies at redshifts higher than 0.6, while ensuring a high-quality photo-$z$ determination. The optimization is performed using a Fisher forecast algorithm, finding the optimal $i$-magnitude cut to be given by $i$<19.64+2.894$z_{\rm ph}$. For the optimal sample, we forecast an increase in precision in the BAO measurement of $\sim$25% with respect to the Y3 analysis. Our BAO sample has a total of 15,937,556 galaxies in the redshift range 0.6<$z_{\rm ph}$<1.2, and its angular mask covers 4,273.42 deg${}^2$ to a depth of $i$=22.5. We validate its redshift distributions with three different methods: directional neighborhood fitting algorithm (DNF), which is our primary photo-$z$ estimation; direct calibration with spectroscopic redshifts from VIPERS; and clustering redshift using SDSS galaxies. The fiducial redshift distribution is a combination of these three techniques performed by modifying the mean and width of the DNF distributions to match those of VIPERS and clustering redshift. In this paper we also describe the methodology used to mitigate the effect of observational systematics, which is analogous to the one used in the Y3 analysis. This paper is one of the two dedicated to the analysis of the BAO signal in DES Y6. In its companion paper, we present the angular diameter distance constraints obtained through the fitting to the BAO scale.

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Dark Energy Survey Year 6 Results: Cosmological Constraints from Cosmic Shear

We present legacy cosmic shear measurements and cosmological constraints using six years of Dark Energy Survey imaging data. From these data, we study ~140 million galaxies (8.29 galaxies/arcmin$^2$) that are 50% complete at i=24.0 and extend beyond z=1.2. We divide the galaxies into four redshift bins, and obtain cosmic shear measurement with a signal-to-noise of 83, a factor of 2 higher than the Year 3 analysis. We model the uncertainties due to shear and redshift calibrations, and discard measurements on small angular scales to mitigate baryon feedback and other small-scale uncertainties. We consider two fiducial models to account for the intrinsic alignment (IA) of the galaxies. We conduct a blind analysis in the context of the $Λ$CDM model and find $S_8 \equiv σ_8(Ω_m/0.3)^{0.5}=0.798^{+0.014}_{-0.015}$ (marginalized mean with 68% CL) when using the non-linear alignment model (NLA) and $S_{8} = 0.783^{+0.019}_{-0.015}$ with the tidal alignment and tidal torque model (TATT), providing 1.8% and 2.5% uncertainty on $S_8$. Compared to constraints from the cosmic microwave background from Planck 2018, ACT DR6 and SPT-3G DR1, we find consistency in the full parameter space at 1.1$σ$ (1.7$σ$) and in $S_8$ at 2.0$σ$ (2.3$σ$) for NLA (TATT). The result using the NLA model is preferred according to the Bayesian evidence. We find that the model choice for IA and baryon feedback can impact the value of our $S_8$ constraint up to $1σ$. For our fiducial model choices, the resultant uncertainties in $S_8$ are primarily degraded by the removal of scales, as well as the marginalization over the IA parameters. We demonstrate that our result is internally consistent and robust to different choices in calibrating the data, owing to methodological improvements in shear and redshift measurement, laying the foundation for next-generation cosmic shear programs.

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Dark Energy Survey Year 6 Results: Cell-based Coadds and Metadetection Weak Lensing Shape Catalogue

We present the Metadetection weak lensing galaxy shape catalogue from the six-year Dark Energy Survey (DES Y6) imaging data. This dataset is the final release from DES, spanning 4422 deg$^2$ of the southern sky. We describe how the catalogue was constructed, including the two new major processing steps, cell-based image coaddition and shear measurements with Metadetection. The DES Y6 Metadetection weak lensing shape catalogue consists of 151,922,791 galaxies detected over riz bands, with an effective number density of $n_{\rm eff}$ =8.22 galaxies per arcmin$^2$ and shape noise of $σ_e$ = 0.29. We carry out a suite of validation tests on the catalogue, including testing for PSF leakage, testing for the impact of PSF modeling errors, and testing the correlation of the shear measurements with galaxy, PSF, and survey properties. In addition to demonstrating that our catalogue is robust for weak lensing science, we use the DES Y6 image simulation suite (Mau, Becker et al. 2025) to estimate the overall multiplicative shear bias of our shear measurement pipeline. We find no detectable multiplicative bias at the roughly half-percent level, with m = (3.4 $\pm$ 6.1) x $10^{-3}$, at 3$σ$ uncertainty. This is the first time both cell-based coaddition and Metadetection algorithms are applied to observational data, paving the way to the Stage-IV weak lensing surveys.

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Dark Energy Survey: implications for cosmological expansion models from the final DES Baryon Acoustic Oscillation and Supernova data

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). 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, $\sim2σ$ away from Planck's $Λ$CDM predictions, pushes for low values of $Ω_{\rm m}$ compared to Planck, in contrast to SN which prefers a higher value. We identify several tensions among datasets in the $Λ$CDM model that cannot be resolved by including either curvature or a constant dark energy equation of state. By combining BAO+SN+CMB despite these mild tensions, we obtain $Ω_k$=$-5.5^{+4.6}_{-4.2}\times10^{-3}$ in $kΛ$CDM, and $w=-0.948^{+0.028}_{-0.027}$ in $w$CDM. In $w$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 $w_0w_a$CDM, 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 $3.2σ$ deviation from $Λ$CDM, with $w_0=-0.673^{+0.098}_{-0.097}$, $w_a = -1.37^{+0.51}_{-0.50}$, a Hubble constant of $H_0=67.81^{+0.96}_{-0.86}$km s$^{-1}$Mpc$^{-1}$, and an abundance of matter of $Ω_{\rm m}=0.3109^{+0.0086}_{-0.0099}$. For the combination of all the background cosmological probes considered we still find a deviation of $2.8σ$ from $Λ$CDM in the $w_0-w_a$ plane. Assuming a minimal neutrino mass, this work provides tentative evidence for non-$Λ$CDM physics, which is consistent with recent claims in support of evolving dark energy, or a source of unknown systematics.

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The Atacama Cosmology Telescope: DR6 Sunyaev-Zel'dovich Selected Galaxy Clusters Catalog

We present the results of a search for galaxy clusters in the Atacama Cosmology Telescope (ACT) Data Release 6 (DR6) microwave sky maps covering 16293 square degrees in three frequency bands, using data obtained over the lifetime of the project (2008-2022). We report redshifts and mass estimates for 10040 clusters detected via their Sunyaev-Zel'dovich (SZ) effect with signal-to-noise greater than 4 at a 2.4 arcminute filter scale. The catalog includes 1180 clusters at redshifts greater than 1, and 124 clusters at redshifts greater than 1.5. Using a relation between cluster SZ signal and mass that is consistent with recent weak-lensing measurements, we estimate that clusters detected with signal-to-noise greater than 5 form a sample which is 90% complete for clusters with masses greater than $5 \times 10^{14}$ MSun (measured within a spherical volume with mean density 500 times the critical density). El Gordo, a cluster found in an initial ACT survey of 755 square degrees, remains the most extreme cluster in mass and redshift; we find no cluster with a mass and redshift combination high enough to falsify the standard LCDM cosmology with Gaussian initial perturbations. We make public a variety of data products, including the full cluster candidate list, noise maps, and sky masks, along with our software for cluster detection and instructions for reproducing our cluster catalogs from the public ACT maps.

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Dark Energy Survey Year 6 Results: Magnification modeling and its impact on galaxy clustering and galaxy-galaxy lensing cosmology

Gravitational lensing magnification alters the observed spatial distribution of galaxies and must be accounted for to prevent biases in cosmological probes of the large-scale structure. We investigate its effects on the Dark Energy Survey Year 6 galaxy clustering and galaxy-galaxy lensing analyses using the fiducial lens (position tracer) sample MagLim++. Magnification bias is parameterized by a coefficient that describes the response of the number of selected objects per unlensed area element to a change in the lensing convergence. We quantify this coefficient using the Balrog synthetic source injection catalog to account for the complexity of the selection function, and compare these results with simplified estimates. The resulting values of the magnification coefficients for each redshift bin are [3.16 $\pm$ 0.08, 2.76 $\pm$ 0.21, 4.09 $\pm$ 0.15, 4.42 $\pm$ 0.16, 4.90 $\pm$ 0.29, 4.83 $\pm$ 0.25]. Relative to Year 3, this analysis provides more precise and accurate magnification bias estimates through a larger Balrog area and reweighting to better match the data properties. The cosmological results are robust when tested against various magnification parameter prior choices and also when adding cross-clustering between lens redshift bins. Neglecting magnification, however, introduces significant systematic shifts: relative to the fiducial analysis with Gaussian priors centered on the Balrog-derived estimates, we observe shifts of 1.37$σ$ in $S_8$ and -0.84$σ$ in $Ω_m$ (with cosmic shear included: -0.61$σ$ in $S_8$ and -0.71$σ$ in $Ω_m$), in agreement with findings from simulated data, demonstrating that magnification must be modeled to avoid biases. Freeing the magnification bias in lens bin 2 leads to unphysical negative values, further justifying its exclusion from the fiducial Year 6 analysis.

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Dark Energy Survey Year 6 Results: Galaxy-galaxy lensing

We present galaxy--galaxy lensing (GGL) measurements from the full six years of data from the Dark Energy Survey (DES Y6), covering $4031\,\mathrm{deg}^2$ and used in the DES Y6 $3\times2$pt cosmological analysis. We use the MagLim++ lens sample, containing $\sim 9$ million galaxies divided into six redshift bins, and the Metadetection source catalog, including $\sim 140$ million galaxies divided into four redshift bins. The mean tangential shear signal achieves a total signal-to-noise ratio (S/N) of $173$, corresponding to a $17\%$ improvement over DES Y3. After applying the scale cuts used in the cosmological analysis, with $R_{\min}=6\,\mathrm{Mpc}/h$ ($4\,\mathrm{Mpc}/h$) for the linear (nonlinear) galaxy-bias model, the S/N is reduced to $75$ (90). A comprehensive suite of validation tests demonstrates that the measurement is robust against observational and astrophysical systematics at the statistical precision required for the DES Y6 analysis. Although not used in the main cosmological analysis, we extract high--signal-to-noise geometric shear-ratio measurements from the galaxy--galaxy lensing signal on small angular scales. These measurements provide an internal consistency check on the photometric redshift distributions and shear calibration used in the $3\times2$pt analysis.

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Dark Energy Survey Year 6 Results: Weak Lensing and Galaxy Clustering Cosmological Analysis Framework

We present the methodology for the weak lensing and galaxy clustering analyses of the Dark Energy Survey (DES) Year 6 data set. In this work, we design and validate the analysis pipeline for the cosmic shear, galaxy clustering plus galaxy$-$galaxy lensing ($2 \times 2$pt), and the joint analysis in the $3 \times 2$pt. Our framework accounts for key theoretical uncertainties, such as baryonic feedback and galaxy bias, incorporating both linear and non-linear models. We apply scale cuts in regimes where theoretical modeling becomes unreliable. The robustness of the pipeline is validated using mock data and simulations, confirming unbiased cosmological constraints and highlighting the importance of posterior projection effects in the validation process. As a result, we deliver robust and validated analysis pipelines for cosmic shear, $2 \times 2$pt, and $3 \times 2$pt in $\Lambda$CDM and $w$CDM scenarios, including a well-defined set of scales suitable for real data analysis, a robust prescription for theoretical systematics, and the theoretical covariance of the signal. This comprehensive methodology also lays the groundwork for future galaxy surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time.

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Dark Energy Survey: DESI-Independent Angular BAO Measurement

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 year 6 (Y6) BAO analysis. We interpret the impact of this measurement in the context of the statistical preference for $w_0w_a$ cold dark matter (CDM) over $\Lambda$CDM when combined with DES Y5 Type Ia supernovae (SN), Planck Cosmic Microwave Background (CMB) and DESI BAO. Based on our previous work, 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 $w_0w_a$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 \texttt{BAOfit\_wtheta}, the BAO fitting code for the angular correlation function used in the DES Y6 BAO analysis.

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Dark Energy Survey Year 6 Results: MagLim++ Lens Sample Selection and Measurements of Galaxy Clustering

Galaxy clustering is a sensitive probe of the expansion history and growth of structure of the universe, and key degeneracies can be broken by combining these data with measurements of cosmic shear and galaxy-galaxy lensing (a so-called 3$\times$2pt analysis). The largest and least biased statistical samples of galaxies for use in clustering analyses can be collected photometrically through large imaging surveys. However, selecting clean photometric subsamples for cosmology are crucial for avoiding contamination that can bias cosmological constraints. Here we present the MagLim++ galaxy sample, selected to optimize for cosmological constraining power and incorporating an array of novel quality cuts to identify and remove residual contamination. This sample comes from the full six years of observations from the Dark Energy Survey. We present measurements of the two-point angular clustering ($w(θ)$) of 9,186,205 galaxies distributed over 4031 sq. degrees and in six tomographic redshift bins centered at $\bar{z}\approx$ [0.31, 0.44, 0.62, 0.78, 0.90, 1.01]. These measurements are used as part of the 3$\times$2pt and other DES Y6 legacy cosmological analyses in companion works. We describe the battery of null tests and mitigation schemes implemented to address observational, astrophysical, and methodological systematics in the analysis. The resulting $w(θ)$ measurements have a S/N = 149 (90.2 for linear scales only), which we use to place galaxy-clustering-only constraints on the matter density of the Universe, $Ω_m=0.311^{+0.023}_{-0.035}$, and amplitude of galaxy clustering in each redshift bin, $b_iσ_8=[1.16^{+0.04}_{-0.06},\ 1.40^{+0.04}_{-0.06},\ 1.57^{+0.04}_{-0.06},\ 1.59^{+0.04}_{-0.05},\ 1.50^{+0.04}_{-0.05},\ 1.74^{+0.06}_{-0.08}]$.

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