218 citations · 2.4k across the 113 of their papers we have counts for
5 papers · 1 filter
A Deep Learning Approach to Infer Galaxy Cluster Masses from Planck Compton parameter maps
Daniel de Andres, Weiguang Cui, Florian Ruppin +8
Galaxy clusters are useful laboratories to investigate the evolution of the Universe, and accurately measuring their total masses allows us to constrain important cosmological para…
Multi-probe analysis of the galaxy cluster CL J1226.9+3332: Hydrostatic mass and hydrostatic-to-lensing bias
M. Muñoz-Echeverría, J. F. Macías-Pérez, G. W. Pratt +50
The precise estimation of the mass of galaxy clusters is a major issue for cosmology. Large galaxy cluster surveys rely on scaling laws that relate cluster observables to their mas…
The Three Hundred project: A Machine Learning method to infer clusters of galaxies mass radial profiles from mock Sunyaev-Zel'dovich maps
A. Ferragamo, D. de Andres, A. Sbriglio +9
We develop a machine learning algorithm to infer the 3D cumulative radial profiles of total and gas mass in galaxy clusters from thermal Sunyaev-Zel'dovich effect maps. We generate…
CHEX-MATE: Morphological analysis of the sample
Maria Giulia Campitiello, Stefano Ettori, Lorenzo Lovisari +17
In this work, we performed an analysis of the X-ray morphology of the 118 CHEX-MATE (Cluster HEritage project with XMM-Newton - Mass Assembly and Thermodynamics at the Endpoint of…
Polarization angle requirements for CMB B-mode experiments. Application to the LiteBIRD satellite
P. Vielva, E. Martínez-González, F. J. Casas +68
A methodology to provide the polarization angle requirements for different sets of detectors, at a given frequency of a CMB polarization experiment, is presented. The uncertainties…