Issue |
A&A
Volume 620, December 2018
The XXL Survey: second series
|
|
---|---|---|
Article Number | A9 | |
Number of page(s) | 20 | |
Section | Cosmology (including clusters of galaxies) | |
DOI | https://doi.org/10.1051/0004-6361/201832931 | |
Published online | 20 November 2018 |
The XXL Survey
XXIV. The final detection pipeline
1
AIM, CEA, CNRS, Université Paris-Saclay, Université Paris Diderot, Sorbonne Paris Cité,
91191
Gif-sur-Yvette,
France
e-mail: lorenzo.faccioli@cea.fr
2
Argelander Institut für Astronomie, Universität Bonn,
53121
Bonn,
Germany
3
INAF, IASF Milano,
via Bassini 15,
20133
Milano,
Italy
4
IRAP, Université de Toulouse, CNRS, CNES, UPS,
Toulouse,
France
Received:
1
March
2018
Accepted:
18
July
2018
Aims. A well characterised detection pipeline is an important ingredient for X-ray cluster surveys.
Methods. We present the final development of the XXL Survey pipeline. The pipeline optimally uses X-ray information by combining many overlapping observations of a source when possible, both for its detection and its characterisation. It can robustly detect and characterise several types of X-ray sources: AGNs (point-like), galaxy clusters (extended), galaxy clusters contaminated by a central AGN, and pairs of AGNs close on the sky. We perform a thorough suite of validation tests via realistic simulations of XMM-Newton images and we introduce new selection criteria for various types of sources that will be detected by the survey.
Results. We find that the use of overlapping observations allows new clusters to be securely identified that would be missed or less securely identified by using only one observation at a time. We also find that, with the new pipeline we can robustly identify clusters with a central AGN that would otherwise have been missed, and we can flag pairs of AGNs close on the sky that might have been mistaken for a cluster.
Key words: galaxies: clusters: general / X-rays: galaxies: clusters / large-scale structure of Universe / methods: numerical
© ESO 2018
Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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