1.3k citations · 4k across the 78 of their papers we have counts for
9 papers · 1 filter
SHAPing the Gas: Understanding Gas Shapes in Dark Matter Haloes with Interpretable Machine Learning
Luis Fernando Machado Poletti Valle, Camille Avestruz, David J. Barnes +3
The non-spherical shapes of dark matter and gas distributions introduce systematic uncertainties that affect observable-mass relations and selection functions of galaxy groups and…
Dark Energy Survey Year 1 Results: Cosmological Constraints from Cluster Abundances, Weak Lensing, and Galaxy Correlations
C. To, E. Krause, E. Rozo +105
Combining multiple observational probes is a powerful technique to provide robust and precise constraints on cosmological parameters. In this letter, we present the first joint ana…
PoPE: A population-based approach to model spatial structure of astronomical systems
Arya Farahi, Daisuke Nagai, Yang Chen
We present a novel population-based Bayesian inference approach to model the average and population variance of spatial distribution of a set of observables from ensemble analysis…
Masses: Weak Lensing Calibration of the Dark Energy Survey Year 1 redMaPPer Clusters using Stellar Masses
M. E. S. Pereira, A. Palmese, T. N. Varga +78
We present the weak lensing mass calibration of the stellar mass based mass proxy for redMaPPer galaxy clusters in the Dark Energy Survey Year 1. For the first time we…
Approximate Bayesian Uncertainties on Deep Learning Dynamical Mass Estimates of Galaxy Clusters
Matthew Ho, Arya Farahi, Markus Michael Rau +1
We study methods for reconstructing Bayesian uncertainties on dynamical mass estimates of galaxy clusters using convolutional neural networks (CNNs). We discuss the statistical bac…
Dark Energy Survey Year 1 Results: Cosmological Constraints from Cluster Abundances and Weak Lensing
DES Collaboration, Tim Abbott, Michel Aguena +129
We perform a joint analysis of the counts and weak lensing signal of redMaPPer clusters selected from the Dark Energy Survey (DES) Year 1 dataset. Our analysis uses the same shear…