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20212026
most citedThe SRG/eROSITA All-Sky Survey: Dark Energy Survey Year 3 Weak Gravitational Lensing by eRASS1 selected Galaxy Clusters

45 citations · 96 across the 26 of their papers we have counts for

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astro-ph.CO2026

Dark Energy Survey Year 6 Results: Cosmological Constraints from Galaxy Clustering and Weak Lensing

DES Collaboration, T. M. C. Abbott, M. Adamow +169

We present cosmology results combining galaxy clustering and weak gravitational lensing measured in the full six years (Y6) of observations by the Dark Energy Survey (DES) covering…

astro-ph.CO2026

Dark Energy Survey Year 6 Results: Galaxy-galaxy lensing

G. Giannini, G. Camacho-Ciurana, A. Whyley +116

We present galaxy--galaxy lensing (GGL) measurements from the full six years of data from the Dark Energy Survey (DES Y6), covering and used in the DES Y6 $3…

astro-ph.CO2026

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

D. Sanchez-Cid, A. Ferté, J. Blazek +115

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 pi…

astro-ph.CO2026

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

E. Legnani, J. Elvin-Poole, D. Anbajagane +72

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 struc…

astro-ph.CO2025

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

T. Shin, E. J. Baxter, E. Lee +93

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 At…

astro-ph.CO2025★ 2 cited

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

A. Thomsen, J. Bucko, T. Kacprzak +99

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 f…