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20182021
most citedDark Energy Survey Year 3 Results: Optimizing the Lens Sample in Combined Galaxy Clustering and Galaxy-Galaxy Lensing Analysis

76 citations · 122 across the 2 of their papers we have counts for

collaborators

10 papers

astro-ph.CO202146 cited

Dark Energy Survey Year 3 Results: Multi-Probe Modeling Strategy and Validation

E. Krause, X. Fang, S. Pandey +121

This paper details the modeling pipeline and validates the baseline analysis choices of the DES Year 3 joint analysis of galaxy clustering and weak lensing (a so-called "32…

astro-ph.CO2020

Assessing tension metrics with Dark Energy Survey and Planck data

P. Lemos, M. Raveri, A. Campos +103

Quantifying tensions -- inconsistencies amongst measurements of cosmological parameters by different experiments -- has emerged as a crucial part of modern cosmological data analys…

astro-ph.CO2020

Dark Energy Survey Year 3 Results: Covariance Modelling and its Impact on Parameter Estimation and Quality of Fit

O. Friedrich, F. Andrade-Oliveira, H. Camacho +109

We describe and test the fiducial covariance matrix model for the combined 2-point function analysis of the Dark Energy Survey Year 3 (DES-Y3) dataset. Using a variety of new ansat…

astro-ph.CO202076 cited

Dark Energy Survey Year 3 Results: Optimizing the Lens Sample in Combined Galaxy Clustering and Galaxy-Galaxy Lensing Analysis

A. Porredon, M. Crocce, P. Fosalba +77

We investigate potential gains in cosmological constraints from the combination of galaxy clustering and galaxy-galaxy lensing by optimizing the lens galaxy sample selection using…

astro-ph.CO2020

DES Y1 results: Splitting growth and geometry to test CDM

J. Muir, E. Baxter, V. Miranda +100

We analyze Dark Energy Survey (DES) data to constrain a cosmological model where a subset of parameters -- focusing on -- are split into versions associated with structure gr…

astro-ph.CO2020

Linear Systematics Mitigation in Galaxy Clustering in the Dark Energy Survey Year 1 Data

Erika L. Wagoner, Eduardo Rozo, Xiao Fang +3

We implement a linear model for mitigating the effect of observing conditions and other sources of contamination in galaxy clustering analyses. Our treatment improves upon the fidu…