| Issue |
A&A
Volume 653, September 2021
|
|
|---|---|---|
| Article Number | A106 | |
| Number of page(s) | 12 | |
| Section | Cosmology (including clusters of galaxies) | |
| DOI | https://doi.org/10.1051/0004-6361/201730534 | |
| Published online | 16 September 2021 | |
MILCANN: A tSZ map for galaxy cluster detection assessed using a neural network⋆
1
Centro de Estudios de Física del Cosmos de Aragón (CEFCA), Plaza de San Juan, 1, Planta 2, 44001 Teruel, Spain
2
Université Paris Saclay, CNRS, Institut d’Astrophysique Spatiale, Bâtiment 121 Campus Paris-Sud, 91405 Orsay, France
e-mail: nabila.aghanim@ias.u-psud.fr
Received:
31
January
2017
Accepted:
14
December
2019
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.
Key words: large-scale structure of Universe / galaxies: clusters: general / methods: data analysis
The list of candidate clusters is only available at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/cat/J/A+A/653/A106
© G. Hurier et al. 2021
Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.