45 citations · 323 across the 54 of their papers we have counts for
5 papers · 1 filter
Cosmology with galaxy clusters using machine learning. Application to eROSITA Data
Fucheng Zhong, Nicola R. Napolitano, Johan Comparat +8
Context: We present the first Cosmological Parameter inferences from eROSITA X-ray observations of galaxy clusters using a Machine Learning algorithm. Methods: We train a Random Fo…
Euclid Quick Data Release (Q1). Searching for giant gravitational arcs in galaxy clusters with mask region-based convolutional neural networks
Euclid Collaboration, L. Bazzanini, G. Angora +306
Strong gravitational lensing (SL) by galaxy clusters is a powerful probe of their inner mass distribution and a key test bed for cosmological models. However, the detection of SL e…
Euclid Quick Data Release (Q1). The first catalogue of strong-lensing galaxy clusters
Euclid Collaboration, P. Bergamini, M. Meneghetti +375
We present the first catalogue of strong lensing galaxy clusters identified in the Euclid Quick Release 1 observations (covering ). This catalogue is the resu…
Euclid Quick Data Release (Q1). NIR processing and data products
Euclid Collaboration, G. Polenta, M. Frailis +367
This paper describes the near-infrared processing function (NIR PF) that processes near-infrared images from the Near-Infrared Spectrometer and Photometer (NISP) instrument onboard…
Euclid Quick Data Release (Q1). LEMON -- Lens Modelling with Neural networks. Automated and fast modelling of Euclid gravitational lenses with a singular isothermal ellipsoid mass profile
Euclid Collaboration, V. Busillo, C. Tortora +312
The Euclid mission aims to survey around 14000 deg^{2} of extragalactic sky, providing around 10^{5} gravitational lens images. Modelling of gravitational lenses is fundamental to…