XGAPS: a sub-arcsec cross-match of galactic plane surveys

Abstract

This article has been accepted for publication in Monthly notices of the Royal Astronomical Society ©: 2023 Scaringi, S. et al. XGAPS: a sub-arcsec cross-match of galactic plane surveys. Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved.

We present a sub-arcsec cross-match of Gaia Data Release 3 (DR3) against the INT Galactic Plane Surveys (IGAPS) and the United Kingdom Infrared Deep Sky Survey (UKIDSS). The resulting cross-match of Galactic Plane Surveys (XGAPS) provides additional precise photometry (URGO, g, r, i, Ha, J, H, and K) to the Gaia photometry. In building the catalogue, proper motions given in Gaia DR3 are wound back to match the epochs of the IGAPS constituent surveys (INT Photometric HaSurvey of the Northern Galactic Plane, IPHAS, and the UV-Excess Survey of the Northern Galactic Plane, UVEX) and UKIDSS, ensuring high-proper motion objects are appropriately cross-matched. The catalogue contains 33¿987¿180 sources. The requirement of >3s parallax detection for every included source means that distances out to 1–1.5¿kpc are well covered. In producing XGAPS, we have also trained a Random Forest classifier to discern targets with problematic astrometric solutions. Selection cuts based on the classifier results can be used to clean colour-magnitude and colour–colour diagrams in a controlled and justified manner, as well as producing subsets of astrometrically reliable targets. We provide XGAPS as a 111 column table. Uses of the catalogue include the selection of Galactic targets for multi-object spectroscopic surveys as well as identification of specific Galactic populations.

MM work was funded by the Spanish MICIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe” by the “European Union” through grant RTI2018-095076-B-C21, and the Institute of Cosmos Sciences University of Barcelona (ICCUB, Unidad de Excelencia “María de Maeztu”) through grant CEX2019-000918-M. ARM acknowledges support from Grant RYC2016-20254 funded by MCIN/AEI/10.13039/501100011033 and by ESF Investing in your future, and from MINECO under the PID2020-117252GB-I00 grant.

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