Query : 2021A&A...653A.106H

2021A&A...653A.106H - Astronomy and Astrophysics, volume 653A, 106-106 (2021/9-1)

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


Abstract (from CDS):

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=1014M) high-redshift (up to z≤1) galaxy cluster candidates.

Abstract Copyright: © G. Hurier et al. 2021

Journal keyword(s): large-scale structure of Universe - galaxies: clusters: general - methods: data analysis

VizieR on-line data: <Available at CDS (J/A+A/653/A106): hadv1.dat>

Status at CDS : All or part of tables of objects will not be ingested in SIMBAD.

Simbad objects: 0

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