arXiv subjects

J. McCullough

Publications and source records attributed to J. McCullough.

At least 19 recordsLinked to original sources

arXiv2026

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.

astro-ph.CO↗

arXiv2026

Deep Spectroscopy with DESI for Photometric Redshift Training and Calibration

Deep spectroscopic samples can be used to improve photometric redshift (photo-$z$) estimates and reduce uncertainties on redshift distributions. Such improvements can increase the cosmological constraining power of large imaging-based experiments such as the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) and mitigate what may be a limiting systematic effect. We present results from the ``DESI-Deep pilot'' program, which was designed to assess the capability of the Dark Energy Spectroscopic Instrument (DESI) on the 4m Mayall telescope to measure redshifts of galaxies as faint as expected lensing samples for early LSST data ($m_i \leq 24.5$). We find that DESI is remarkably efficient at this task, with redshift success rates comparable to the results of observations from 10m-class telescopes with only $\sim2\times$ longer integration time (rather than $\sim 8\times$ longer as would be expected from aperture-area scaling), while simultaneously achieving $\sim30$ times larger multiplexing. We also find that the signal-to-noise ratio of the spectra scales as expected for background-limited observations even for the longest exposure times ($\sim 7$ hours) and faintest targets in the program. These results demonstrate that DESI could provide the definitive redshift sample for the early years of LSST with a modest investment of observing time. Based upon the results of this program, we provide updated predictions for the time required to collect benchmark samples for photo-$z$ training and calibration using a variety of spectroscopic facilities. Finally, we describe a potential "DESI-Deep" survey designed to train and calibrate photo-$z$'s for imaging experiments, and provide forecasts of its impact on cosmological inference.

astro-ph.IM↗

arXiv2026

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.

astro-ph.CO↗

arXiv2025

Weak Lensing Mass Calibration of the ACT DR5 Galaxy Clusters with the DES Year 3 Weak Lensing Data

We use weak gravitational lensing measurements from Year 3 Dark Energy Survey data to calibrate the masses of 443 galaxy clusters selected via the Sunyaev-Zel'dovich effect from Atacama Cosmology Telescope Data Release 5 maps of the cosmic microwave background. We incorporate redshift and SZ measurements for individual clusters into a hierarchical model for the stacked lensing signals and perform Bayesian analyses to constrain the hydrostatic mass bias of the clusters. Our treatment of systematic uncertainties includes a prescription for measuring and accounting for the weak lensing boost factor, consideration of a miscentering effect, as well as marginalization over uncertainties in the source galaxy photometric redshift distributions and shear calibration. The resultant constraints on the normalization of the mass-observable relation have a precision of approximately 7\%, with the mean WL halo mass of $M_{\rm 500c} = 5.4 \times 10^{14} M_{\odot}$. We measure the bias between the true cluster mass and the mass estimated from the SZ signal based on an X-ray--calibrated scaling relation assuming hydrostatic equilibrium, to be $1-b = 0.75^{+0.04}_{-0.06}$ over the full sample. When splitting the clusters into high ($z$=0.43-0.70) and low ($z$=0.15-0.43) redshift bins, we measure $1-b = 0.58^{+0.06}_{-0.05}$ and $0.82^{+0.07}_{-0.07}$, respectively. When introducing additional freedom in redshift and mass to the hydrostatic bias model, we find that $1-b$ decreases with redshift (with the power law of $-2.0^{+0.7}_{-0.4}$, 99.95\% confidence), consistent with findings from other recent studies, while we do not find any significant trend in mass. We also demonstrate that our result is robust against various systematics. The weak-lensing mass calibration presented in this study will be a useful tool for using the ACT clusters as probes of astrophysics and cosmology.

astro-ph.CO↗

arXiv2025

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 $\Omega_m - S_8$ 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.

astro-ph.CO↗

arXiv2025

Dark Energy Survey Year 6 Results: Redshift Calibration of the Weak Lensing Source Galaxies

Determining the distribution of redshifts for galaxies in wide-field photometric surveys is essential for robust cosmological studies of weak gravitational lensing. We present the methodology, calibrated redshift distributions, and uncertainties of the final Dark Energy Survey Year 6 (Y6) weak lensing galaxy data, divided into four redshift bins centered at $\langle z \rangle = [0.414, 0.538, 0.846, 1.157]$. We combine independent information from two methods on the full shape of redshift distributions: optical and near-infrared photometry within an improved Self-Organizing Map $p(z)$ (SOMPZ) framework, and cross-correlations with spectroscopic galaxy clustering measurements (WZ), which we demonstrate to be consistent both in terms of the redshift calibration itself and in terms of resulting cosmological constraints within 0.1$\sigma$. We describe the process used to produce an ensemble of redshift distributions that account for several known sources of uncertainty. Among these, imperfection in the calibration sample due to the lack of faint, representative spectra is the dominant factor. The final uncertainty on mean redshift in each bin is $\sigma_{\langle z\rangle} = [0.012, 0.008,0.009, 0.024]$. We ensure the robustness of the redshift distributions by leveraging new image simulations and a cross-check with galaxy shape information via the shear ratio (SR) method.

astro-ph.CO↗

arXiv2025

A DECADE of dwarfs: first detection of weak lensing around spectroscopically confirmed low-mass galaxies

We present the first detection of weak gravitational lensing around spectroscopically confirmed dwarf galaxies, using the large overlap between DESI DR1 spectroscopic data and DECADE/DES weak lensing catalogs. A clean dwarf galaxy sample with well-defined redshift and stellar mass cuts enables excess surface mass density measurements in two stellar mass bins ($\log \rm{M}_*=[8.2, 9.2]~M_\odot$ and $\log \rm{M}_*=[9.2, 10.2]~M_\odot$), with signal-to-noise ratios of $5.6$ and $12.4$ respectively. This signal-to-noise drops to $4.5$ and $9.2$ respectively for measurements without applying individual inverse probability (IIP) weights, which mitigates fiber incompleteness from DESI's targeting. The measurements are robust against variations in stellar mass estimates, photometric shredding, and lensing calibration systematics. Using a simulation-based modeling framework with stellar mass function priors, we constrain the stellar mass-halo mass relation and find a satellite fraction of $\simeq 0.3$, which is higher than previous photometric studies but $1.5\sigma$ lower than $\Lambda$CDM predictions. We find that IIP weights have a significant impact on lensing measurements and can change the inferred $f_{\rm{sat}}$ by a factor of two, highlighting the need for accurate fiber incompleteness corrections for dwarf galaxy samples. Our results open a new observational window into the galaxy-halo connection at low masses, showing that future massively multiplexed spectroscopic observations and weak lensing data will enable stringent tests of galaxy formation models and $\Lambda$CDM predictions.

astro-ph.GA↗

arXiv2025

Biasing from galaxy trough and peak profiles with the DES Y3 redMaGiC galaxies and the weak lensing mass map

We measure the correspondence between the distribution of galaxies and matter around troughs and peaks in the projected galaxy density, by comparing \texttt{redMaGiC} galaxies ($0.15<z<0.65$) to weak lensing mass maps from the Dark Energy Survey (DES) Y3 data release. We obtain stacked profiles, as a function of angle $\theta$, of the galaxy density contrast $\delta_{\rm g}$ and the weak lensing convergence $\kappa$, in the vicinity of these identified troughs and peaks, referred to as `void' and `cluster' superstructures. The ratio of the profiles depend mildly on $\theta$, indicating good consistency between the profile shapes. We model the amplitude of this ratio using a function $F(\eta, \theta)$ that depends on cosmological parameters $\eta$, scaled by the galaxy bias. We construct templates of $F(\eta, \theta)$ using a suite of $N$-body (`Gower Street') simulations forward-modelled with DES Y3-like noise and systematics. We discuss and quantify the caveats of using a linear bias model to create galaxy maps from the simulation dark matter shells. We measure the galaxy bias in three lens tomographic bins (near to far): $2.32^{+0.86}_{-0.27}, 2.18^{+0.86}_{-0.23}, 1.86^{+0.82}_{-0.23}$ for voids, and $2.46^{+0.73}_{-0.27}, 3.55^{+0.96}_{-0.55}, 4.27^{+0.36}_{-1.14}$ for clusters, assuming the best-fit \textit{Planck} cosmology. Similar values with $\sim0.1\sigma$ shifts are obtained assuming the mean DES Y3 cosmology. The biases from troughs and peaks are broadly consistent, although a larger bias is derived for peaks, which is also larger than those measured from the DES Y3 $3\times2$-point analysis. This method shows an interesting avenue for measuring field-level bias that can be applied to future lensing surveys.

astro-ph.CO↗

arXiv2025

DECADE+DES Y3 Weak Lensing Mass Map: A 13,000 deg$^2$ View of Cosmic Structure from 270 Million Galaxies

We present the largest galaxy weak lensing mass map of the late-time Universe, reconstructed from 270 million galaxies in the DECADE and DES Year 3 datasets, covering 13,000 square degrees. We validate the map through systematic tests against observational conditions (depth, seeing, etc.), finding the map is statistically consistent with no contamination. The large area covered by the mass map makes it a well-suited tool for cosmological analyses, cross-correlation studies and the identification of large-scale structure features. We demonstrate its potential by detecting cosmic filaments directly from the mass map for the first time and validating them through their association with galaxy clusters selected using the Sunyaev-Zeldovich effect from Planck and ACT DR6.

astro-ph.CO↗

arXiv2025

The Dark Energy Camera All Data Everywhere cosmic shear project V: Constraints on cosmology and astrophysics from 270 million galaxies across 13,000 deg$^2$ of the sky

We present constraints on models of cosmology and astrophysics using cosmic shear data vectors from three datasets: the northern and southern Galactic cap of the Dark Energy Camera All Data Everywhere (DECADE) project, and the Dark Energy Survey (DES) Year 3. These data vectors combined consist of 270 million galaxies spread across 13,000 ${\rm deg}^2$ of the sky. We first extract constraints for $\Lambda$CDM cosmology and find $S_8= 0.805^{+0.019}_{-0.019}$ and $\Omega_{\rm m} = 0.262^{+0.023}_{-0.036}$, which is consistent within $1.9 \sigma$ of constraints from the Planck satellite. Extending our analysis to dynamical dark energy models shows that lensing provides some (but still minor) improvements to existing constraints from supernovae and baryon acoustic oscillations. Finally, we study six different models for the impact of baryons on the matter power spectrum. We show the different models provide consistent constraints on baryon suppression, and associated cosmology, once the astrophysical priors are sufficiently wide. Current scale-cut approaches for mitigating baryon contamination result in a residual bias of $\approx 0.3\sigma$ in the $S_8, \Omega_{\rm m}$ posterior. Using all scales with dedicated baryon modeling leads to negligible improvement as the new information is used solely to self-calibrate the baryon model on small scales. Additional non-lensing datasets, and/or calibrations of the baryon model, will be required to access the full statistical power of the lensing measurements. The combined dataset in this work represents the largest lensing dataset to date (most galaxies, largest area) and provides an apt testing ground for analyses of upcoming datasets from Stage IV surveys. The DECADE shear catalogs, data vectors, and likelihoods are made publicly available.

astro-ph.CO↗

arXiv2025

The Compilation and Validation of the Spectroscopic Redshift Catalogs for the DESI-COSMOS and DESI-XMMLSS Fields

Over several dedicated programs that include targets beyond the main cosmological samples, the Dark Energy Spectroscopic Instrument (DESI) collected spectra for 304,970 unique objects in two fields centered on the COSMOS and XMM-LSS fields. In this work, we develop spectroscopic redshift robustness criteria for those spectra, validate these criteria using visual inspection, and provide two custom Value-Added Catalogs with our redshift characterizations. With these criteria, we reliably classify 212,935 galaxies below z < 1.6, 9,713 quasars and 35,222 stars. As a critical element in characterizing the selection function, we provide the description of 70 different algorithms that were used to select these targets from imaging data. To facilitate joint imaging/spectroscopic analyses, we provide row-matched photometry from the Dark Energy Camera, Hyper-Suprime Cam, and public COSMOS2020 photometric catalogs. Finally, we demonstrate example applications of these large catalogs to photometric redshift estimation, cluster finding, and completeness studies.

astro-ph.CO↗

arXiv2025

Intrinsic alignment demographics for next-generation lensing: Revealing galaxy property trends with DESI Y1 direct measurements

We present direct measurements of the intrinsic alignments (IA) of over 2 million spectroscopic galaxies using DESI Data Release 1 and imaging from four lensing surveys: DES, HSC, KiDS, and SDSS. In this uniquely data-rich regime, we take initial steps towards a more tailored IA modelling approach by building a library of IA measurements across colour, luminosity, stellar mass, and redshift. We map the dependence between galaxy type -- in terms of rest-frame colour, strength of the 4000 Angstrom break, and specific star formation rate -- and IA amplitude; the bluest galaxies have an alignment consistent with zero, across low ($0.05<z<0.5$) and high ($0.8<z<1.55$) redshifts. In order to construct cosmic shear samples that are minimally impacted by IA but maintain maximum sample size and statistical power, we map the dependence of alignment with colour purity. Red, quenched galaxies are strongly aligned and the amplitude of the signal increases with luminosity, which is tightly correlated with stellar mass in our catalogues. For DESI galaxies between $0<z<1.5$, trends in luminosity and colour alone are sufficient to explain the alignments we measure -- with no need for an explicit redshift dependence. In a companion paper (Jeffrey et al., in prep), we perform detailed modelling of the IA signals with significant detections, including model comparison. Finally, to direct efforts for future IA measurements, we juxtapose the colour-magnitude-redshift coverage of existing IA measurements against modern and future lensing surveys.

astro-ph.CO↗

arXiv2025

Constraining the Stellar-to-Halo Mass Relation with Galaxy Clustering and Weak Lensing from DES Year 3 Data

We develop a framework to study the relation between the stellar mass of a galaxy and the total mass of its host dark matter halo using galaxy clustering and galaxy-galaxy lensing measurements. We model a wide range of scales, roughly from $\sim 100 \; {\rm kpc}$ to $\sim 100 \; {\rm Mpc}$, using a theoretical framework based on the Halo Occupation Distribution and data from Year 3 of the Dark Energy Survey (DES) dataset. The new advances of this work include: 1) the generation and validation of a new stellar mass-selected galaxy sample in the range of $\log M_\star/M_\odot \sim 9.6$ to $\sim 11.5$; 2) the joint-modeling framework of galaxy clustering and galaxy-galaxy lensing that is able to describe our stellar mass-selected sample deep into the 1-halo regime; and 3) stellar-to-halo mass relation (SHMR) constraints from this dataset. In general, our SHMR constraints agree well with existing literature with various weak lensing measurements. We constrain the free parameters in the SHMR functional form $\log M_\star (M_h) = \log(\epsilon M_1) + f\left[ \log\left( M_h / M_1 \right) \right] - f(0)$, with $f(x) \equiv -\log(10^{\alpha x}+1) + \delta [\log(1+\exp(x))]^\gamma / [1+\exp(10^{-x})]$, to be $\log M_1 = 11.506^{+0.325}_{-0.404}$, $\log \epsilon = -1.632^{+0.306}_{-0.181}$, $\alpha = -1.638^{+0.108}_{-0.099}$, $\gamma = 0.596^{+0.251}_{-0.210}$ and $\delta = 3.810^{+2.045}_{-1.811}$. The inferred average satellite fraction is within $\sim 5-35\%$ for our fiducial results and we do not see any clear trends with redshift or stellar mass. Furthermore, we find that the inferred average galaxy bias values follow the generally expected trends with stellar mass and redshift. Our study is the first SHMR in DES in this mass range, and we expect the stellar mass sample to be of general interest for other science cases.

astro-ph.GA↗

arXiv2025

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 $0.3\sigma$) in the $\Omega_\mathrm{m}-S_8$ plane. Assuming the $w$CDM model, our combined Betti numbers and second moments analysis yields $S_8 = 0.821 \pm 0.018$ and $\Omega_\mathrm{m} = 0.304\pm0.037$-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.

astro-ph.CO↗

arXiv2025

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$\sigma$ 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 $\Omega_{\rm m} = 0.263^{+0.023}_{-0.030}$, 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 $2-4\sigma$ 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.

astro-ph.CO↗

arXiv2025

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 $\Lambda$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 $\Omega_{\rm{m}} = 0.265^{+0.019}_{-0.031}$ from the cluster-based data vector. We find that cluster constraints and 3x2pt constraints are consistent under the $\Lambda$CDM model with a Posterior Predictive Distribution (PPD) value of $0.53$. The consistency between clusters and 3x2pt provides a stringent test of $\Lambda$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 $\Omega_{\rm{m}} = 0.294^{+0.022}_{-0.033}$, a $24\%$ improvement in the $\Omega_{\rm{m}}-S_8$ 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 $\sum m_\nu < 0.26$ eV at 95% confidence under the $\Lambda$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.

astro-ph.CO↗

arXiv2025

The DECADE cosmic shear project I: A new weak lensing shape catalog of 107 million galaxies

We present the Dark Energy Camera All Data Everywhere (DECADE) weak lensing dataset: a catalog of 107 million galaxies observed by the Dark Energy Camera (DECam) in the northern Galactic cap. This catalog was assembled from public DECam data including survey and standard observing programs. These data were consistently processed with the Dark Energy Survey Data Management pipeline as part of the DECADE campaign and serve as the basis of the DECam Local Volume Exploration survey (DELVE) Early Data Release 3 (EDR3). We apply the Metacalibration measurement algorithm to generate and calibrate galaxy shapes. After cuts, the resulting cosmology-ready galaxy shape catalog covers a region of $5,\!412 \,\,{\rm deg}^2$ with an effective number density of $4.59\,\, {\rm arcmin}^{-2}$. The coadd images used to derive this data have a median limiting magnitude of $r = 23.6$, $i = 23.2$, and $z = 22.6$, estimated at ${\rm S/N} = 10$ in a 2 arcsecond aperture. We present a suite of detailed studies to characterize the catalog, measure any residual systematic biases, and verify that the catalog is suitable for cosmology analyses. In parallel, we build an image simulation pipeline to characterize the remaining multiplicative shear bias in this catalog, which we measure to be $m = (-2.454 \pm 0.124) \times10^{-2}$ for the full sample. Despite the significantly inhomogeneous nature of the data set, due to it being an amalgamation of various observing programs, we find the resulting catalog has sufficient quality to yield competitive cosmological constraints.

astro-ph.CO↗

arXiv2025

The DECADE cosmic shear project II: photometric redshift calibration of the source galaxy sample

We present the photometric redshift characterization and calibration for the Dark Energy Camera All Data Everywhere (DECADE) weak lensing dataset: a catalog of 107 million galaxies observed by the Dark Energy Camera (DECam) in the northern Galactic cap. The redshifts are estimated from a combination of wide-field photometry, deep-field photometry with associated redshift estimates, and a transfer function between the wide field and deep field that is estimated using a source injection catalog. We construct four tomographic bins for the galaxy catalog, and estimate the redshift distribution, $n(z)$, within each one using the Self-organizing Map Photo-Z (SOMPZ) methodology. Our estimates include the contributions from sample variance, zeropoint calibration uncertainties, and redshift biases, as quantified for the deep-field dataset. The total uncertainties on the mean redshifts are $\sigma_{\langle z \rangle} \approx 0.01$. The SOMPZ estimates are then compared to those from the clustering redshift method, obtained by cross-correlating our source galaxies with galaxies in spectroscopic surveys, and are shown to be consistent with each other.

astro-ph.CO↗