Publications de Gianluca Castignani

Euclid preparation XXXVII. Galaxy colour selections with Euclid and ground photometry for cluster weak-lensing analyses

Frédéric Courbin, Georges Meylan, Gianluca Castignani, Maurizio Martinelli, Matthias Wiesmann, Yi Wang, Richard Massey, Fabio Finelli, Marcello Farina

Aims. We derived galaxy colour selections from Euclid and ground-based photometry, aiming to accurately define background galaxy samples in cluster weak-lensing analyses. These selections have been implemented in the Euclid data analysis pipelines for gala ...

Edp Sciences S A2024

XXXIV. The effect of linear redshift-space distortions in photometric galaxy clustering and its cross-correlation with cosmic shear

Frédéric Courbin, Georges Meylan, Gianluca Castignani, Maurizio Martinelli, Malte Tewes, Slobodan Ilic, Alessandro Pezzotta, Yi Wang, Richard Massey, Fabio Finelli

Context. The cosmological surveys that are planned for the current decade will provide us with unparalleled observations of the distribution of galaxies on cosmic scales, by means of which we can probe the underlying large-scale structure (LSS) of the Univ ...

Edp Sciences S A2024

Euclid preparation XXXVI. Modelling the weak lensing angular power spectrum

Frédéric Courbin, Georges Meylan, Gianluca Castignani, Austin Chandler Peel, Maurizio Martinelli, Yi Wang, Richard Massey, Fabio Finelli, Marcello Farina

This work considers which higher order modeling e ffects on the cosmic shear angular power spectra must be taken into account for Euclid. We identified the relevant terms and quantified their individual and cumulative impact on the cosmological parameter i ...

Edp Sciences S A2024

Euclid preparation XXII. Selection of quiescent galaxies from mock photometry using machine learning

Frédéric Courbin, Georges Meylan, Gianluca Castignani, Austin Chandler Peel, Maurizio Martinelli, Yi Wang, Richard Massey, Fabio Finelli, Marcello Farina

The Euclid Space Telescope will provide deep imaging at optical and near-infrared wavelengths, along with slitless near-infrared spectroscopy, across similar to 15 000deg(2) of the sky. Euclid is expected to detect similar to 12 billion astronomical source ...

EDP SCIENCES S A2023

Euclid preparation XXX. Performance assessment of the NISP red grism through spectroscopic simulations for the wide and deep surveys

Frédéric Courbin, Georges Meylan, Gianluca Castignani, Michaela Hirschmann, Maurizio Martinelli, Yi Wang, Richard Massey, Fabio Finelli, Marcello Farina

This work focusses on the pilot run of a simulation campaign aimed at investigating the spectroscopic capabilities of the Euclid NearInfrared Spectrometer and Photometer (NISP), in terms of continuum and emission line detection in the context of galaxy evo ...

EDP SCIENCES S A2023

Euclid preparation: XXVIII. Forecasts for ten different higher-order weak lensing statistics

Frédéric Courbin, Gianluca Castignani, Austin Chandler Peel, Jean-Luc Starck, Maurizio Martinelli, Yi Wang, Richard Massey, Fabio Finelli, Marcello Farina

Recent cosmic shear studies have shown that higher-order statistics (HOS) developed by independent teams now outperform standard two-point estimators in terms of statistical precision thanks to their sensitivity to the non-Gaussian features of large-scale ...

EDP SCIENCES S A2023

Euclid preparation XXIV. Calibration of the halo mass function in λ(ν)CDM cosmologies

Frédéric Courbin, Georges Meylan, Gianluca Castignani, Austin Chandler Peel, Maurizio Martinelli, Slobodan Ilic, Yi Wang, Fabio Finelli, Marcello Farina

Euclid's photometric galaxy cluster survey has the potential to be a very competitive cosmological probe. The main cosmological probe with observations of clusters is their number count, within which the halo mass function (HMF) is a key theoretical quanti ...

EDP SCIENCES S A2023

Euclid preparation - XXIII. Derivation of galaxy physical properties with deep machine learning using mock fluxes and H-band images

Frédéric Courbin, Georges Meylan, Robin Humphry-Baker, Gianluca Castignani, Maurizio Martinelli, Austin Chandler Peel, Yi Wang, Richard Massey, Marcello Farina

Next-generation telescopes, like Euclid, Rubin/LSST, and Roman, will open new windows on the Universe, allowing us to infer physical properties for tens of millions of galaxies. Machine-learning methods are increasingly becoming the most efficient tools to ...

OXFORD UNIV PRESS2023

Euclid preparation XXVI. The Euclid Morphology Challenge: Towards structural parameters for billions of galaxies

Frédéric Courbin, Georges Meylan, Gianluca Castignani, Maurizio Martinelli, Slobodan Ilic, Yi Wang, Richard Massey, Marcello Farina

The various Euclid imaging surveys will become a reference for studies of galaxy morphology by delivering imaging over an unprecedented area of 15000 square degrees with high spatial resolution. In order to understand the capabilities of measuring morpholo ...

2023

Euclid preparation XXI. Intermediate-redshift contaminants in the search for z > 6 galaxies within the Euclid Deep Survey

Frédéric Courbin, Georges Meylan, Gianluca Castignani, Austin Chandler Peel, Jean-Luc Starck, Maurizio Martinelli, Hakim Atek, Yi Wang, Richard Massey, Marcello Farina

Context. The Euclid mission is expected to discover thousands of z > 6 galaxies in three deep fields, which together will cover a similar to 50 deg(2) area. However, the limited number of Euclid bands (four) and the low availability of ancillary data could ...

EDP SCIENCES S A2022