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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…
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…
Biasing from galaxy trough and peak profiles with the DES Y3 redMaGiC galaxies and the weak lensing mass map
Q. Hang, N. Jeffrey, L. Whiteway +83
We measure the correspondence between the distribution of galaxies and matter around troughs and peaks in the projected galaxy density, by comparing \texttt{redMaGiC} galaxies ($0.…
Dark Energy Survey Year 3 Results: Cosmological constraints from second and third-order shear statistics
R. C. H. Gomes, S. Sugiyama, B. Jain +95
We present a cosmological analysis of the third-order aperture mass statistic using Dark Energy Survey Year 3 (DES Y3) data. We perform a complete tomographic measurement of the th…
Constraints on cosmology and baryonic feedback with joint analysis of Dark Energy Survey Year 3 lensing data and ACT DR6 thermal Sunyaev-Zel'dovich effect observations
S. Pandey, J. C. Hill, A. Alarcon +137
We present a joint analysis of weak gravitational lensing (shear) data obtained from the first three years of observations by the Dark Energy Survey and thermal Sunyaev-Zel'dovich…
Constraining the Stellar-to-Halo Mass Relation with Galaxy Clustering and Weak Lensing from DES Year 3 Data
G. Zacharegkas, C. Chang, J. Prat +100
We develop a framework to study the relation between the stellar mass of a galaxy and the total mass of its host dark matter halo using galaxy clustering and galaxy-galaxy lensing…