arXiv subjects

K. Kuehn

Publications and source records attributed to K. Kuehn.

At least 19 recordsLinked to original sources

arXiv2026

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 $Λ$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.

astro-ph.CO↗

arXiv2026

Dark Energy Survey Year 6 Results: improved mitigation of spatially varying observational systematics with masking for the MagLim++ lens sample

As photometric surveys reach unprecedented statistical precision, systematic uncertainties increasingly dominate large-scale structure probes relying on galaxy number density. Defining the final survey footprint is critical, as it excludes regions affected by artefacts or suboptimal observing conditions. For galaxy clustering, spatially varying observational systematics, such as seeing, are a leading source of bias. Template maps of contaminants are used to derive spatially dependent corrections, but extreme values may fall outside the applicability range of mitigation methods, compromising correction reliability. The complexity and accuracy of systematics modelling depend on footprint conservativeness, with aggressive masking enabling simpler, robust mitigation. We present a unified approach to define the DES Y6 JOINT footprint, integrating observational systematics templates and artefact indicators that degrade mitigation performance. This removes extreme values from an initial SEED footprint, leading to the final JOINT footprint. By evaluating the DES Y6 lens sample MagLim++ on this footprint, we enhance the Iterative Systematics Decontamination (ISD) method, detecting non-linear systematic contamination and improving correction accuracy. While the mask's impact on clustering is less significant than systematics decontamination, it remains non-negligible, comparable to statistical uncertainties in certain w(theta) scales and redshift bins. Supporting coherent analyses of galaxy clustering and cosmic shear, the final footprint spans 4,031.04 deg2, setting the basis for DES Y6 1x2pt, 2x2pt, and 3x2pt analyses. This work highlights how targeted masking strategies optimise the balance between statistical power and systematic control in Stage-III and -IV surveys.

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arXiv2026

Enhancing weak lensing redshift distribution characterization by optimizing the Dark Energy Survey Self-Organizing Map Photo-z method

Characterization of the redshift distribution of ensembles of galaxies is pivotal for large scale structure cosmological studies. In this work, we focus on improving the Self-Organizing Map (SOM) methodology for photometric redshift estimation (SOMPZ), specifically in anticipation of the Dark Energy Survey Year 6 (DES Y6) data. This data set, featuring deeper and fainter galaxies than DES Year 3 (DES Y3), demands adapted techniques to ensure accurate recovery of the underlying redshift distribution. We investigate three strategies for enhancing the existing SOM-based approach used in DES Y3: 1) Replacing the Y3 SOM algorithm with one tailored for redshift estimation challenges; 2) Incorporating $\textit{g}$-band flux information to refine redshift estimates (i.e. using $\textit{griz}$ fluxes as opposed to only $\textit{riz}$); 3) Augmenting redshift data for galaxies where available. These methods are applied to DES Y3 data, and results are compared to the Y3 fiducial ones. Our analysis indicates significant improvements with the first two strategies, notably reducing the overlap between redshift bins. By combining strategies 1 and 2, we have successfully managed to reduce redshift bin overlap in DES Y3 by up to 66$\%$. Conversely, the third strategy, involving the addition of redshift data for selected galaxies as an additional feature in the method, yields inferior results and is abandoned. Our findings contribute to the advancement of weak lensing redshift characterization and lay the groundwork for better redshift characterization in DES Year 6 and future stage IV surveys, like the Rubin Observatory.

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arXiv2026

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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arXiv2026

Characterizing Photonic Ring Resonator Filters for OH Suppressed Near-infrared Astronomy

Supernova cosmology relies on accurate measurement of the absolute magnitudes of Type Ia supernovae. Observation in the visible incurs significant systematic uncertainties in these measurements due to their high degree of interstellar dust extinction. Observing in the near-infrared (750-2500 nm) mitigates this issue by decreasing attenuation, decreasing dispersion, and increasing supernova observation distances. However, ground-based observations in the near-infrared suffer from sky background caused by atmospheric OH emission lines. Advancements in photonic ring resonator filter devices make it feasible to suppress these lines. In this paper, we evaluate the performance of a prototype photonic ring resonator device developed for use in the lower H-band (1480-1620 nm). Specifically, we characterize the progression of suppressed wavelengths into the upper H-band (1620-1800 nm) enabling the suppression of emission lines over a broader wavelength range.

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arXiv2026

Galaxy Clusters Selected via the Sunyaev-Zel'dovich Effect in 5 year data from the SPT-3G Main Survey

We report a new galaxy cluster catalog, selected using the thermal Sunyaev-Zel'dovich (SZ) effect, from 5 years of observations of the SPT-3G Main field. Drawn from arcminute-resolution data with white noise levels of 3.2, 2.5, and 8.9 $μ$K-arcmin at 95, 150, and 220 GHz, respectively, the sample consists of 8,892 cluster candidates detected above significance $ξ=4$, with an expected purity of $>82\%$ (4,480 at $ξ\ge5$ with purity $>99\%$). Using optical and infrared data we have confirmed 7,190 candidates as clusters. The sample spans a mass range $7.9 \times 10^{13}$ $M_\odot/h_{70}$ \ $< M_\textrm{500c} < $ $1.6 \times 10^{15}$ $M_\odot/h_{70}$ with a median mass of $1.65 \times 10^{14}$ $M_\odot/h_{70}$, and a redshift range of $0.037 1$ and 271 at $z>1.5$. Compared to previous SZ cluster samples from South Pole Telescope and Atacama Cosmology Telescope data, the SPT-3G sample is highly consistent in mass and redshift but is significantly deeper, with per-cluster detection signal-to-noise 2-4 times higher and a cluster density of 4.5 confirmed clusters/deg$^2$. We cross match with eRASS1 cluster and point source catalogs, finding 1,279 and 1,319 matches, respectively. The SPT and eROSITA cluster mass estimates are in relatively good agreement. We perform a series of validation checks using both internal data splits and comparisons to external samples. These tests show increasing correlated (dusty) emission with redshift, with a $\sim17\times$ larger 220 GHz temperature increment for clusters at $z\sim1.5$ than $z\sim0.25$, but only weak evidence for correlated synchrotron emission. Finally, a number of clusters are flagged as candidate strong gravitational lenses.

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arXiv2026

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$σ$. 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 $σ_{\langle z\rangle} = [0.012, 0.008,0.009, 0.024]$. 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↗

arXiv2026

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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arXiv2026

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 $Λ$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 $0.3σ$ in this preference (from $3.7σ$ to $4.0σ$), 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 $3.7σ$ to $3.8σ$ when using DESI DR1 BAO, and from $4.0σ$ to $4.1σ$ when updating to the more recent DESI data release 2 (DR2) BAO. These significances reduce to $3.1σ$ 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.

astro-ph.CO↗

arXiv2026

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.

astro-ph.CO↗

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 $S_8 = 0.808 \pm 0.017$, $Ω_{\rm m} = 0.325 \pm 0.024$, 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 $(Ω_{\rm m}, S_8, w)$ 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 $(Ω_{\rm m}, S_8, w)$ 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

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 $2.2σ$ 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 $2.3σ$ 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 $3.0σ$ deviation. We find that including 3$\times$2pt in the previously studied SN + DESI BAO + CMB combination leaves the significance essentially unchanged ($3.2 σ$ to $3.0σ$) while improving the figure of merit by $\sim$10\%. We systematically investigate the impact of leaving out each one of the probes and find that the significance of the deviation from a cosmological constant ranges from 2.3 to 3.2$σ$, with best-fit parameters consistently in the region $w_0 >-1$ and $w_a <0$. Excluding SN from the all data combination yields a $2.6σ$ departure from $Λ$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.

astro-ph.CO↗

arXiv2026

Robust Measurement of Stellar Streams Around the Milky Way: Correcting Spatially Variable Observational Selection Effects in Optical Imaging Surveys

Observations of density variations in stellar streams are a promising probe of low-mass dark matter substructure in the Milky Way. However, survey systematics such as variations in seeing and sky brightness can also induce artificial fluctuations in the observed densities of known stellar streams. These variations arise because survey conditions affect both object detection and star--galaxy misclassification rates. To mitigate these effects, we use Balrog synthetic source injections in the Dark Energy Survey (DES) Y3 data to calculate detection rate variations and classification rates as functions of survey properties. We show that these rates are nearly separable with respect to survey properties and can be estimated with sufficient statistics from the synthetic catalogs. Applying these corrections reduces the standard deviation of relative detection rates across the DES footprint by a factor of five, and our corrections significantly change the inferred linear density of the Phoenix stream when including faint objects. Additionally, for artificial streams with DES like survey properties we are able to recover density power spectra with reduced bias. We also find that uncorrected power-spectrum results for LSST-like data can be around five times more biased, highlighting the need for such corrections in future ground based surveys.

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arXiv2026

The Dark Energy Survey Supernova Program: A Reanalysis Of Cosmology Results And Evidence For Evolving Dark Energy With An Updated Type Ia Supernova Calibration

We present improved cosmological constraints from a re-analysis of the Dark Energy Survey (DES) 5-year sample of Type Ia supernovae (DES-SN5YR). This re-analysis includes an improved photometric cross-calibration, recent white dwarf observations to cross-calibrate between DES and low redshift surveys, retraining the SALT3 light curve model and fixing a numerical approximation in the host galaxy colour law. Our fully recalibrated sample, which we call DES-Dovekie, comprises $\sim$1600 likely Type Ia SNe from DES and $\sim$200 low-redshift SNe from other surveys. With DES-Dovekie, we obtain $Ω_{\rm m} = 0.330 \pm 0.015$ in Flat $Λ$CDM which changes $Ω_{\rm m}$ by $-0.022$ compared to DES-SN5YR. Combining DES-Dovekie with CMB data from Planck, ACT and SPT and the DESI DR2 measurements in a Flat $w_0 w_a$CDM cosmology, we find $w_0 = -0.803 \pm 0.054$, $w_a = -0.72 \pm 0.21$. Our results hold a significance of $3.2σ$, reduced from $4.2σ$ for DES-SN5YR, to reject the null hypothesis that the data are compatible with the cosmological constant. This significance is equivalent to a Bayesian model preference odds of approximately 5:1 in favour of the Flat $w_0 w_a$CDM model. Using generally accepted thresholds for model preference, our updated data exhibits only a weak preference for evolving dark energy.

astro-ph.CO↗

arXiv2026

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.

astro-ph.GA↗

arXiv2026

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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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.

astro-ph.CO↗