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S. Allam

Publications and source records attributed to S. Allam.

At least 19 recordsLinked to original sources

Constraints on Dynamical Dark Energy from Multiple Probes in the Full Dark Energy Survey

We present results on dark energy evolution, assuming a time-dependent equation of state $w(a)=w_0+w_a(1-a)$, from growth and geometric probes using the full six-year Dark Energy Survey dataset: type Ia supernovae, baryon acoustic oscillations, and weak gravitational lensing and galaxy clustering (3$\times$2pt). The combination yields $w_0=-0.84^{+0.10}_{-0.10}$ and $w_a=-0.44^{+0.60}_{-0.55}$, the tightest constraints ever obtained from a single survey, with $2.2\sigma$ deviation from a cosmological constant. Adding the DESI DR2 BAO data yields $w_0=-0.84^{+0.06}_{-0.07}$ and $w_a=-0.53^{+0.33}_{-0.28}$, representing the most stringent low-redshift-only test of dynamical dark energy to date, with a $2.3\sigma$ deviation. In this combination, adding 3$\times$2pt doubles the constraining power. Finally, when combined with primary CMB information, we obtain $w_0=-0.82^{+0.05}_{-0.05}$, $w_a=-0.63^{+0.21}_{-0.18}$, with a $3.0\sigma$ deviation. We find that including 3$\times$2pt in the previously studied SN + DESI BAO + CMB combination leaves the significance essentially unchanged ($3.2 \sigma$ to $3.0\sigma$) while improving the figure of merit by $\sim$10\%. We systematically investigate the impact of leaving out each one of the probes and find that the significance of the deviation from a cosmological constant ranges from 2.3 to 3.2$\sigma$, with best-fit parameters consistently in the region $w_0 >-1$ and $w_a <0$. Excluding SN from the all data combination yields a $2.6\sigma$ departure from $\Lambda$CDM, providing a cross-check independent of supernova photometric calibration. These results support the weak preference for evolving dark energy reported by several recent cosmological analyses. By combining growth and geometric probes from a single survey, this work realizes the multi-probe dark energy program envisioned at the inception of DES.

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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$\sigma$ in $S_8$ and -0.84$\sigma$ in $\Omega_m$ (with cosmic shear included: -0.61$\sigma$ in $S_8$ and -0.71$\sigma$ in $\Omega_m$), 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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Constraints on the normal branch of DGP gravity from SPT galaxy clusters with DES and HST weak-lensing mass calibration and from Planck PR4 CMB anisotropies

We present constraints on the normal branch of the Dvali-Gabadadze-Porrati (nDGP) braneworld gravity model from the abundance of massive galaxy clusters. On scales below the nDGP crossover scale $r_{\rm c}$, the nDGP model features an effective gravity-like fifth force that alters the growth of structure, leading to an enhancement of the halo mass function (HMF) on cluster scales. The enhanced cluster abundance allows for constraints on the nDGP model using cluster samples. We employ the SPT cluster sample, selected through the thermal Sunyaev-Zel`dovich effect (tSZE) with the South Pole Telescope (SPT) and with mass calibration using weak-lensing data from the Dark Energy Survey (DES) and the Hubble Space Telescope (HST). The cluster sample contains 1,005 clusters with redshifts $0.25 < z < 1.78$, which are confirmed with the Multi-Component Matched Filter (MCMF) algorithm using optical and near-infrared data. Weak-lensing data from DES and HST enable a robust mass measurement of the cluster sample. We use DES Year 3 data for 688 clusters with redshifts $z < 0.95$, and HST data for 39 clusters with redshifts $ 0.6 < z <1.7$. We account for the enhancement in the HMF through a semi-analytic correction factor to the standard cosmology HMF derived from the spherical collapse model in the nDGP model. We then further calibrate this model using $N$-body simulations. In addition, for the first time, we analyze the primary cosmic microwave background (CMB) temperature and polarization anisotropy measurements from Planck PR4 within the nDGP model. We obtain a competitive constraint from the joint analysis of the SPT cluster abundance with the Planck PR4 data, and report an upper bound of $1/\sqrt{(H_0r_{\rm c})}< 1.41$ at $95\,\%$ when assuming a cosmology with massive neutrinos.

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OzDES Reverberation Mapping Program: CIV lags from six years of data

We present 29 successfully recovered CIV time lags in Active Galactic Nuclei from the complete Dark Energy Survey Reverberation Mapping campaign. The AGN in this sample span a redshift range of 1.9<z<3.5. We successfully measure the velocity dispersion from the CIV spectral linewidth for 25 of these 29 sources, and use these to calculate new high-redshift black hole mass estimates, finding masses between 0.8 and 1.3 billion solar masses. We also identify a selection effect due to the duration of the survey that can impact the radius-luminosity relation derived from this and other (high-redshift) data. This paper represents the culmination of the OzDES CIV campaign.

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OzDES Reverberation Mapping of Active Galactic Nuclei: Final Data Release, Black-Hole Mass Results, & Scaling Relations

Over the last decade, the Australian Dark Energy (OzDES) collaboration has used Reverberation Mapping to measure the masses of high redshift supermassive black holes. Here we present the final review and analysis of this OzDES reverberation mapping campaign. These observations use 6-7 years of photometric and spectroscopic observations of 735 Active Galactic Nuclei (AGN) in the redshift range 0.13-3.85 and bolometric luminosity range 44.3 - 47.5 erg/s. Both photometry and spectra are observed in visible wavelengths, allowing for the physical scale of the AGN broad line region to be estimated from reverberations of the H\b{eta}, MgII and CIV emission lines. We successfully use reverberation mapping to constrain the masses of 62 super-massive black holes, and combine with existing data to fit a power law to the lag-luminosity relation for the H\b{eta} and MgII lines with a scatter of ~0.25 dex, the tightest yet identified, fit specifically for consistency with high redshift AGN. We fit a similarly constrained relation for CIV, resolving a tension with the low luminosity literature AGN by accounting for selection effects arising from finite survey length. We also examine the impact of emission line width and luminosity (related to accretion rate) in reducing the scatter of these scaling relationships and find no significant improvement over the lag-only approach for any of the three lines. Using these relations, we further estimate the masses and accretion rates of 246 AGN with single epoch methods. We also use these relations to estimate the relative sizes of the H\b{eta}, MgII and CIV emitting regions. In short, we provide a comprehensive benchmark of high redshift AGN reverberation mapping at the close of this most recent generation of surveys, including light curves, time-delays, and a set of significantly improved radius-luminosity relations for use with high-redshift populations.

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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 $\Omega_m - S_8$ 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.

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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$$2\sigma$, which can be attributed to the clustering of satellites associated with the LMC.

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Dark Energy Survey Year 6 Results: Redshift Calibration of the MagLim++ Lens Sample

In this work, we derive and calibrate the redshift distribution of the MagLim++ lens galaxy sample used in the Dark Energy Survey Year 6 (DES Y6) 3x2pt cosmology analysis. The 3x2pt analysis combines galaxy clustering from the lens galaxy sample and weak gravitational lensing. The redshift distributions are inferred using the SOMPZ method - a Self-Organizing Map framework that combines deep-field multi-band photometry, wide-field data, and a synthetic source injection (Balrog) catalog. Key improvements over the DES Year 3 (Y3) calibration include a noise-weighted SOM metric, an expanded Balrog catalogue, and an improved scheme for propagating systematic uncertainties, which allows us to generate O($10^8$) redshift realizations that collectively span the dominant sources of uncertainty. These realizations are then combined with independent clustering-redshift measurements via importance sampling. The resulting calibration achieves typical uncertainties on the mean redshift of 1-2%, corresponding to a 20-30% average reduction relative to DES Y3. We compress the $n(z)$ uncertainties into a small number of orthogonal modes for use in cosmological inference. Marginalizing over these modes leads to only a minor degradation in cosmological constraints. This analysis establishes the MagLim++ sample as a robust lens sample for precision cosmology with DES Y6 and provides a scalable framework for future surveys.

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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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The final WaZP galaxy cluster catalog of the Dark Energy Survey and comparison with SZE data

In this work, we present and characterize the galaxy cluster catalog detected by the WaZP cluster finder, which is not based on red-sequence identification, on the full six years of observations of the Dark Energy Survey (DES-Y6). The full catalog contains over 400k detected clusters with richnesses, Ngals, above 5 and that reach redshifts up to 1.3. We also provide a version of the catalog where the observation depth and richness computation are homogenized to be used for cosmology, containing 33k rich (Ngals >25) clusters. We compare our results with the previous WaZP catalog obtained from the DES first-year data release (DES-Y1). We find that essentially all clusters within the common footprint and depth limit are recovered. The deeper observations on DES-Y6 and the more complete available spectroscopic redshift sample lead to improvements in the redshifts of the clusters, resulting in an average scatter of 1.4% and offset of 0.2%. The optical clusters are also cross-matched with Sunyaev Zel'dovich Effect (SZE) cluster samples detected by the South Pole Telescope (SPT) and the Atacama Cosmology Telescope (ACT). We find that essentially all SZE clusters with reasonable overlapping footprint have a corresponding WaZP cluster. Conversely, 90% of the optical detections with richness greater than 150 have a counterpart in the deeper regions of the SZE surveys. Based on cross-match with the SZE catalogs, we also find that 15-20% of the SZE matched systems have more than one possible WaZP counterpart at the same redshift and within the SZE R500c, indicating possible interacting or unrelaxed systems. Finally, given the optical and SZE beams, WaZP and SZE centerings are found to be consistent. A more detailed study of the SZE-WaZP mass-richness relation will be presented in a separate paper.

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

We present cosmological constraints from Dark Energy Survey Year 3 (DES Y3) weak lensing data using persistent homology, a topological data analysis technique that tracks how features like clusters and voids evolve across density thresholds. For the first time, we apply spherical persistent homology to galaxy survey data through the algorithm TopoS2, which is optimized for curved-sky analyses and HEALPix compatibility. Employing a simulation-based inference framework with the Gower Street simulation suite, specifically designed to mimic DES Y3 data properties, we extract topological summary statistics from convergence maps across multiple smoothing scales and redshift bins. After neural network compression of these statistics, we estimate the likelihood function and validate our analysis against baryonic feedback effects, finding minimal biases (under $0.3\sigma$) 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.

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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, $\sim2\sigma$ away from Planck's $\Lambda$CDM predictions, pushes for low values of $\Omega_{\rm m}$ compared to Planck, in contrast to SN which prefers a higher value. We identify several tensions among datasets in the $\Lambda$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 $\Omega_k$=$-5.5^{+4.6}_{-4.2}\times10^{-3}$ in $k\Lambda$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 $3.2\sigma$ deviation from $\Lambda$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 $\Omega_{\rm m}=0.3109^{+0.0086}_{-0.0099}$. For the combination of all the background cosmological probes considered we still find a deviation of $2.8\sigma$ from $\Lambda$CDM in the $w_0-w_a$ plane. Assuming a minimal neutrino mass, this work provides tentative evidence for non-$\Lambda$CDM physics, which is consistent with recent claims in support of evolving dark energy, or a source of unknown systematics.

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Cosmology with second and third-order shear statistics for the Dark Energy Survey: Methods and simulated analysis

We present a new pipeline designed for the robust inference of cosmological parameters using both second- and third-order shear statistics. We build a theoretical model for rapid evaluation of three-point correlations using our fastnc code and integrate it into the CosmoSIS framework. We measure the two-point functions $\xi_{\pm}$ and the full configuration-dependent three-point shear correlation functions across all auto- and cross-redshift bins. We compress the three-point functions into the mass aperture statistic $\langle M_{\rm ap}^3\rangle$ for a set of 796 simulated shear maps designed to model the Dark Energy Survey (DES) Year 3 data. We estimate from it the full covariance matrix and model the effects of intrinsic alignments, shear calibration biases and photometric redshift uncertainties. We apply scale cuts to minimize the contamination from the baryonic signal as modeled through hydrodynamical simulations. We find a significant improvement of $83\%$ on the Figure of Merit in the $\Omega_{\rm m}$-$S_8$ plane when we add the $\langle M_{\rm ap}^3\rangle$ data to the $\xi_{\pm}$ information. We present our findings for all relevant cosmological and systematic uncertainty parameters and discuss the complementarity of third-order and second-order statistics.

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Selection Function of Clusters in Dark Energy Survey Year 3 Data from Cross-Matching with South Pole Telescope Detections

Galaxy clusters selected based on overdensities of galaxies in photometric surveys provide the largest cluster samples. Yet modeling the selection function of such samples is complicated by non-cluster members projected along the line of sight (projection effects) and the potential detection of unvirialized objects (contamination). We empirically constrain the magnitude of these effects by cross-matching galaxy clusters selected in the Dark Energy survey data with the \rdmpr$\,$ algorithm with significant detections in three South Pole Telescope surveys (SZ, pol-ECS, pol-500d). For matched clusters, we augment the \rdmpr$\,$catalog by the SPT detection significance. For unmatched objects we use the SPT detection threshold as an upper limit on the SZe signature. Using a Bayesian population model applied to the collected multi-wavelength data, we explore various physically motivated models to describe the relationship between observed richness and halo mass. Our analysis reveals the limitations of a simple lognormal scatter model in describing the data. We rule out significant contamination by unvirialized objects at the high-richness end of the sample. While dedicated simulations offer a well-fitting calibration of projection effects, our findings suggest the presence of redshift-dependent trends that these simulations may not have captured. Our findings highlight that modeling the selection function of optically detected clusters remains a complicated challenge, requiring a combination of simulation and data-driven approaches.

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It's not $\sigma_8$ : constraining the non-linear matter power spectrum with the Dark Energy Survey Year-5 supernova sample

The weak gravitational lensing magnification of Type Ia supernovae (SNe Ia) is sensitive to the matter power spectrum on scales $k>1 h$ Mpc$^{-1}$, making it unwise to interpret SNe Ia lensing in terms of power on linear scales. We compute the probability density function of SNe Ia magnification as a function of standard cosmological parameters, plus an empirical parameter $A_{\rm mod}$ which describes the suppression or enhancement of matter power on non-linear scales compared to a cold dark matter only model. While baryons are expected to enhance power on the scales relevant to SN Ia lensing, other physics such as neutrino masses or non-standard dark matter may suppress power. Using the Dark Energy Survey Year-5 sample, we find $A_{\rm mod} = 0.77^{+0.69}_{-0.40}$ (68\% credible interval around the median). Although the median is consistent with unity there are hints of power suppression, with $A_{\rm mod} < 1.09$ at 68\% credibility.

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