Gaia Data Release 2. Cross-match with external catalogues - Algorithms and results

TL;DR

This paper details the algorithms and results of cross-matching Gaia DR2 with multiple external dense and sparse astronomical surveys, enhancing data integration for research.

Contribution

It introduces a new algorithm for sparse catalogues and provides the first comprehensive cross-match results for Gaia DR2 with various surveys.

Findings

Cross-matched Gaia DR2 with multiple surveys including Pan-STARRS1, 2MASS, SDSS, and others.

Developed a new algorithm specifically for sparse catalogues.

Published the cross-match results as part of Gaia DR2.

Abstract

Context. Although the Gaia catalogue on its own is a very powerful tool, it is the combination of this high-accuracy archive with other archives that will truly open up amazing possibilities for astronomical research. The advanced interoperation of archives is based on cross-matching, leaving the user with the feeling of working with one single data archive. The data retrieval should work not only across data archives but also across wavelength domains. The first step for a seamless access to the data is the computation of the cross-match between Gaia and external surveys. Aims. We describe the adopted algorithms and results of the pre-computed cross-match of the Gaia Data Release 2 (DR2) catalogue with dense surveys (Pan-STARRS1 DR1, 2MASS, SDSS DR9, GSC 2.3, URAT-1, allWISE, PPMXL, and APASS DR9) and sparse catalogues (Hipparcos2, Tycho-2, and RAVE 5). Methods. A new algorithm is developed specifically for sparse catalogues. Improvements and changes with respect to the algorithm adopted for DR1 are described in detail. Results. The outputs of the cross-match are part of the official Gaia DR2 catalogue. The global analysis of the cross-match results is also presented.