paper

Discovery of planetary nebulae using predictive mid-infrared diagnostics

arXiv:1208.4164 · doi:10.1111/j.1365-2966.2012.21927.x

Abstract

We demonstrate a newly developed mid-infrared planetary nebula (PN) selection technique. It is designed to enable efficient searches for obscured, previously unknown, PN candidates present in the photometric source catalogues of Galactic plane MIR sky surveys. Such selection is now possible via new, sensitive, high-to-medium resolution, MIR satellite surveys such as those from the Spitzer Space Telescope and the all-sky Wide-Field Infrared Survey Explorer (WISE) satellite missions. MIR selection is based on how different colour-colour planes isolate zones (sometimes overlapping) that are predominately occupied by different astrophysical object types. These techniques depend on the reliability of the available MIR source photometry. In this pilot study we concentrate on MIR point source detections and show that it is dangerous to take the MIR GLIMPSE (Galactic Legacy Infrared Mid-Plane Survey Extraordinaire) photometry from Spitzer for each candidate at face value without examining the actual MIR image data. About half of our selected sources are spurious detections due to the applied source detection algorithms being affected by complex MIR backgrounds and the de-blending of diffraction spikes around bright MIR point sources into point sources themselves. Nevertheless, once this additional visual diagnostic checking is performed, valuable MIR selected PN candidates are uncovered. Four turned out to have faint, compact, optical counterparts in our H-alpha survey data missed in previous optical searches. We confirm all of these as true PNe via our follow-up optical spectroscopy. This lends weight to the veracity of our MIR technique. It demonstrates sufficient robustness that high-confidence samples of new Galactic PN candidates can be extracted from these MIR surveys without confirmatory optical spectroscopy and imaging. This is problematic or impossible when the extinction is large.

14 pages, 7 figures, 7 tables; accepted for publication in MNRAS

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