Abstract

The Survey Science Centre of the XMM-Newton satellite released the first incremental version of the 2XMM catalogue in August 2008 . With more than 220,000 X-ray sources, the 2XMMi was at that time the largest catalogue of X-ray sources ever published and thus constitutes an unprecedented resource for studying the high-energy properties of various classes of X-ray emitters such as AGN and stars. The advent of the 7th release of the Sloan Digital Sky Survey offers the opportunity to cross-match two major surveys and extend the spectral energy distribution of many 2XMMi sources towards the optical bands. We here present a cross-matching algorithm based on the classical likelihood ratio estimator. The method developed has the advantage of providing true probabilities of identifications without resorting to Monte-Carlo simulations. Over 30,000 2XMMi sources have SDSS counterparts with individual probabilities of identification higher than 90%. Using spectroscopic identifications from the SDSS DR7 catalogue supplemented by extraction from other catalogues, we build an identified sample from which the way the various classes of X-ray emitters gather in the multi dimensional parameter space can be analysed. We investigate two scientific use cases. In the first example we show how these multi-wavelength data can be used to search for new QSO2s. Although no specific range of observed properties allows us to identify Compton Thick QSO2s, we show that the prospects are much better for Compton Thin AGN2 and discuss several possible multi-parameter selection strategies. In a second example, we confirm the hardening of the mean X-ray spectrum with increasing X-ray luminosity on a sample of over 500 X-ray active stars and reveal that on average X-ray active M stars display bluer $g-r$ colour indexes than less active ones (abridged).

Highlights

  • The growing collecting area and sensitivity of modern astronomical detectors combined with the increasing storage and processing capabilities offered by current computer facilities has made possible the gathering on comparatively short time scales of very large sky surveys that were beyond reach only a few years ago

  • We present the results of the cross-identification of the 2XMMi catalogue containing over 220 000 XMM-Newton EPIC

  • In order to ensure the best statistical control on the quality of the cross-correlation process, we use a likelihood ratio scheme only based on the probability of spatial coincidence of the X-ray source with the optical candidate

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Summary

Introduction

The growing collecting area and sensitivity of modern astronomical detectors combined with the increasing storage and processing capabilities offered by current computer facilities has made possible the gathering on comparatively short time scales of very large sky surveys that were beyond reach only a few years ago. The 2XMMi/SDSS DR7 crosscorrelation data file is available at the CDS via http://cdsweb.u-strasbg.fr/cgi-bin/qcat?J/A+A/527/A126 such as the Spitzer Space Telescope (Werner et al 2004) observing in the infra-red or the Chandra (Weisskopf et al 2000) and XMM-Newton (Jansen et al 2001) X-ray observatories are collecting at a high rate a wealth of measurements on an unprecedented number of objects in their energy range. The recent availability of wide angle surveys with high detection sensitivities allows us to measure with comparable accuracies and in several scientifically important wavelength ranges the spectral energy density of the main classes of X-ray emitting astrophysical sources. As part of its scientific activities, the Survey Science Centre of the XMM-Newton satellite has developed a specific crosscorrelation algorithm yielding actual probabilities of identification based on positional coincidence and applied this algorithm to the cross-identification of the 2XMMi and SDSS DR7 catalogues, creating one of the largest set of optically identified X-ray sources available so far. In the last part of this paper, we investigate two example science cases, the search for new QSO2s, and the study of the properties of the X-ray active late-type star population

Description of the cross-correlated catalogues
SDSS Data Release 7
Counterpart identification procedure
Selection criterion
Application to XMM-SDSS DR7 data
Likelihood ratio
Computing reliabilities
Fitting the reliability function
Computing probabilities of identification in the general case
Observation grouping
Results of the 2XMMi-SDSS DR7 cross-correlation
Building an identified sample
The stellar identified sample
The final identified sample
Sample properties and shortcomings
The main classes of X-ray sources
Separating stellar from extragalactic sources
Distinguishing between the various classes of extragalactic sources
Science cases
Searching for QSO2 candidates
X-ray active stars
Summary
Spherical trigonometry
Convolution product of two independent 2D Gaussians
Full Text
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