arXiv subjects

J. Myles

Publications and source records attributed to J. Myles.

At least 37 records · Page 2Linked to original sources

arXiv2026

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.

astro-ph.CO↗

arXiv2026

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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arXiv2026

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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arXiv2026

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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arXiv2026

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.

astro-ph.CO↗

arXiv2026

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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arXiv2026

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, $b_iσ_8=[1.16^{+0.04}_{-0.06},\ 1.40^{+0.04}_{-0.06},\ 1.57^{+0.04}_{-0.06},\ 1.59^{+0.04}_{-0.05},\ 1.50^{+0.04}_{-0.05},\ 1.74^{+0.06}_{-0.08}]$.

astro-ph.CO↗

arXiv2026

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 $θ$, of the galaxy density contrast $δ_{\rm g}$ and the weak lensing convergence $κ$, in the vicinity of these identified troughs and peaks, referred to as `void' and `cluster' superstructures. The ratio of the profiles depend mildly on $θ$, indicating good consistency between the profile shapes. We model the amplitude of this ratio using a function $F(η, θ)$ that depends on cosmological parameters $η$, scaled by the galaxy bias. We construct templates of $F(η, θ)$ 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 $\sim0.1σ$ 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↗

arXiv2026

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.

astro-ph.CO↗

arXiv2026

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 $\log M_\star (M_h) = \log(εM_1) + f\left[ \log\left( M_h / M_1 \right) \right] - f(0)$, with $f(x) \equiv -\log(10^{αx}+1) + δ[\log(1+\exp(x))]^γ/ [1+\exp(10^{-x})]$, to be $\log M_1 = 11.506^{+0.325}_{-0.404}$, $\log ε= -1.632^{+0.306}_{-0.181}$, $α= -1.638^{+0.108}_{-0.099}$, $γ= 0.596^{+0.251}_{-0.210}$ and $δ= 3.810^{+2.045}_{-1.811}$. 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 $0.3σ$) 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.

astro-ph.CO↗

arXiv2025

Spectroscopic Characterization of redMaPPer Galaxy Clusters with DESI

Optical galaxy cluster identification algorithms such as redMaPPer promise to enable an array of astrophysical and cosmological studies, but suffer from biases whereby galaxies in front of and behind a galaxy cluster are mistakenly associated with the primary cluster halo. These projection effects caused by irreducible photometric redshift uncertainty must be quantified to facilitate the use of optical cluster catalogues. We present measurements of galaxy cluster projection effects and velocity dispersion using spectroscopy from the Dark Energy Spectroscopic Instrument (DESI). Our findings are as follows: we confirm that the fraction of redMaPPer putative member galaxies mistakenly associated with cluster haloes is richness dependent, being more than twice as large at low richness than high richness; we present the first spectroscopic evidence of an increase in projection effects with increasing redshift, by as much as 25 per cent from $z\sim0.1$ to $z\sim0.2$; moreover, we find qualitative evidence for luminosity dependence in projection effects, with fainter galaxies being more commonly far behind clusters than their bright counterparts; finally we fit the scaling relation between measured mean spectroscopic richness and velocity dispersion, finding an implied linear scaling between spectroscopic richness and halo mass. We discuss further directions for the application of spectroscopic datasets to improve use of optically selected clusters to test cosmological models.

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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 $σ_{\langle z \rangle} \approx 0.01$. 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↗

arXiv2025

The DECADE cosmic shear project IV: cosmological constraints from 107 million galaxies across 5,400 deg$^2$ of the sky

We present cosmological constraints from the Dark Energy Camera All Data Everywhere (DECADE) cosmic shear analysis. This work uses shape measurements for 107 million galaxies measured through Dark Energy Camera (DECam) imaging of $5,\!412$ deg$^2$ of sky that is outside the Dark Energy Survey (DES) footprint. We derive constraints on the cosmological parameters $S_8 = 0.791^{+0.027}_{-0.032}$ and $Ω_{\rm m} =0.269^{+0.034}_{-0.050}$ for the $Λ$CDM model, which are consistent with those from other weak lensing surveys and from the cosmic microwave background. We combine our results with cosmic shear results from DES Y3 at the likelihood level, since the two datasets span independent areas on the sky. The combined measurements, which cover $\approx\! 10,\!000$ deg$^2$, prefer $S_8 = 0.791 \pm 0.023$ and $Ω_{\rm m} = 0.277^{+0.034}_{-0.046}$ under the $Λ$CDM model. These results are the culmination of a series of rigorous studies that characterize and validate the DECADE dataset and the associated analysis methodologies (Anbajagane et. al 2025a,b,c). Overall, the DECADE project demonstrates that the cosmic shear analysis methods employed in Stage-III weak lensing surveys can provide robust cosmological constraints for fairly inhomogeneous datasets. This opens the possibility of using data that have been previously categorized as ``unusable'' for cosmic shear analyses, thereby increasing the statistical power of upcoming weak lensing surveys.

astro-ph.CO↗

arXiv2025

Year six photometric measurements of known Trans-Neptunian Objects and Centaurs by the Dark Energy Survey

We identified known Trans-Neptunian Objects (TNOs) and Centaurs in the complete Dark Energy Survey (DES) year six catalog (DES Y6) through the Sky Body Tracker (SkyBoT) tool. We classified our dataset of 144 objects into a widely used 4-class taxonomic system of TNOs. No such previous classification was available in the literature for most of these objects. From absolute magnitudes and average albedos, an estimation of the diameters of all these objects is obtained. Correlations involving colours, orbital parameters, dynamical classes and sizes are also discussed. In particular, our largest reddest object has a diameter of $390^{+68}_{-53}$ km and our largest cold classical, $255^{+19}_{-17}$ km. Also, a weak correlation between colour and inclination is found within the population of resonant TNOs in addition to weak correlations between colour and phase slope in different bands.

astro-ph.EP↗

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$σ$ 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.

astro-ph.CO↗

arXiv2025

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.

astro-ph.CO↗

arXiv2025

Discovering Strong Gravitational Lenses in the Dark Energy Survey with Interactive Machine Learning and Crowd-sourced Inspection with Space Warps

We conduct a search for strong gravitational lenses in the Dark Energy Survey (DES) Year 6 imaging data. We implement a pre-trained Vision Transformer (ViT) for our machine learning (ML) architecture and adopt Interactive Machine Learning to construct a training sample with multiple classes to address common types of false positives. Our ML model reduces 236 million DES cutout images to 22,564 targets of interest, including around 85% of previously reported galaxy-galaxy lens candidates discovered in DES. These targets were visually inspected by citizen scientists, who ruled out approximately 90% as false positives. Of the remaining 2,618 candidates, 149 were expert-classified as 'definite' lenses and 516 as 'probable' lenses, with 147 of these candidates being newly identified. Additionally, we trained a second ViT to find double-source plane lens systems, finding at least one double-source system. Our main ViT excels at identifying galaxy-galaxy lenses, consistently assigning high scores to candidates with high confidence. The top 800 ViT-scored images include around 100 of our `definite' lens candidates. This selection is an order of magnitude higher in purity than previous convolutional neural network-based lens searches and demonstrates the feasibility of applying our methodology for discovering large samples of lenses in future surveys.

astro-ph.GA↗