Перейти к основному содержанию
AkademIndex

Продукты

Для разработчиков

AkademBaseОткрытый API экосистемы
Статья

The XXL Survey

L. FaccioliAIM, CEA, CNRS, Université Paris-Saclay, Université Paris Diderot, Sorbonne Paris Cité, 91191 Gif-sur-Yvette, FranceF. PacaudArgelander Institut für Astronomie, Universität Bonn, 53121 Bonn, GermanyJ.‐L. SauvageotUniversité Paris CitéM. PierreAIM, CEA, CNRS, Université Paris-Saclay, Université Paris Diderot, Sorbonne Paris Cité, 91191 Gif-sur-Yvette, FranceL. ChiappettiINAF, IASF Milano, via Bassini 15, 20133 Milano, ItalyN. ClercIRAP, Université de Toulouse, CNRS, CNES, UPS, Toulouse, FranceR. GastaudAIM, CEA, CNRS, Université Paris-Saclay, Université Paris Diderot, Sorbonne Paris Cité, 91191 Gif-sur-Yvette, FranceE. KoulouridisUniversité Paris-SaclayA. M. C. Le BrunAIM, CEA, CNRS, Université Paris-Saclay, Université Paris Diderot, Sorbonne Paris Cité, 91191 Gif-sur-Yvette, FranceA. ValottiAIM, CEA, CNRS, Université Paris-Saclay, Université Paris Diderot, Sorbonne Paris Cité, 91191 Gif-sur-Yvette, France
2018en
ABI

Аннотация

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.

Перевод пока недоступен

Идентификаторы

Цитирования и источники

Цитирований: 2Использованных источников: 0