MILCANN: A tSZ map for galaxy cluster detection assessed using a neural network - CNRS - Centre national de la recherche scientifique Accéder directement au contenu
Article Dans Une Revue Astronomy and Astrophysics - A&A Année : 2021

MILCANN: A tSZ map for galaxy cluster detection assessed using a neural network

Résumé

We present the first combination of a thermal Sunyaev-Zel’dovich (tSZ) map with a multi-frequency quality assessment of the sky pixels based on artificial neural networks with the aim being to detect tSZ sources from submillimeter observations of the sky by Planck. We present the construction of the resulting filtered and cleaned tSZ map, MILCANN. We show that this combination leads to a significant reduction of noise fluctuations and foreground residuals compared to standard reconstructions of tSZ maps. From the MILCANN map, we constructed a tSZ source catalog of about 4000 sources with a purity of 90%. Finally, we compare this catalog with ancillary catalogs and show that the galaxy-cluster candidates in our catalog are essentially low-mass (down to M500 = 1014 M⊙) high-redshift (up to z ≤ 1) galaxy cluster candidates.
Fichier principal
Vignette du fichier
aa30534-17.pdf (3.6 Mo) Télécharger le fichier
Origine : Publication financée par une institution

Dates et versions

hal-03347111 , version 1 (16-09-2021)

Identifiants

Citer

G. Hurier, N. Aghanim, M. Douspis. MILCANN: A tSZ map for galaxy cluster detection assessed using a neural network. Astronomy and Astrophysics - A&A, 2021, 653, pp.A106. ⟨10.1051/0004-6361/201730534⟩. ⟨hal-03347111⟩
26 Consultations
17 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More