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20012026
most citedDark Energy Survey Year 1 Results: Cosmological Constraints from Galaxy Clustering and Weak Lensing

1.2k citations · 13.4k across the 165 of their papers we have counts for

collaborators

172 papers

astro-ph.CO2026

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

DES Collaboration, T. M. C. Abbott, M. Adamow +166

We present results on dark energy evolution, assuming a time-dependent equation of state , from growth and geometric probes using the full six-year Dark Energy S…

astro-ph.CO2026

Point Correlation Functions in Galaxy Surveys: Impact of Baryonic Feedback

Avijit Bera, Joachim Harnois-Déraps, Juan Mena-Fernández +5

We investigate the impact of baryonic feedback on two-point and three-point correlation functions (2PCFs and 3PCFs hereafter, respectively) involving galaxy density fields (g) and…

astro-ph.CO2026

Dark Energy Survey Year 6 Results: Cosmological Constraints from Cosmic Shear

DES Collaboration, T. M. C. Abbott, M. Aguena +126

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 g…

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.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…