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arXiv · 1910.13319

Palomar Gattini-IR: Survey overview, data processing system, on-sky performance and first results

Abstract

(Abridged) Palomar Gattini-IR is a new wide-field, near-infrared robotic time domain survey operating at Palomar Observatory. Using a 30 cm telescope mounted with a H2RG detector, Gattini-IR achieves a field of view of 25 sq. deg. with a pixel scale of 8.7" in J-band. Here, we describe the system design, survey operations, data processing system and on-sky performance of Palomar Gattini-IR. As a part of the nominal survey, Gattini-IR scans $\approx 7500$ square degrees of the sky every night to a median 5$σ$ depth of $15.7$ AB mag outside the Galactic plane. The survey covers $\approx 15000$ square degrees of the sky visible from Palomar with a median cadence of 2 days. A real-time data processing system produces stacked science images from dithered raw images taken on sky, together with PSF-fit source catalogs and transient candidates identified from subtractions within a median delay of $\approx 4$ hours from the time of observation. The calibrated data products achieve an astrometric accuracy (RMS) of $\approx 0.7$" with respect to Gaia DR2 for sources with S/N $> 10$, and better than $\approx 0.35$" for sources brighter than $\approx 12$ Vega mag. The photometric accuracy (RMS) achieved in the PSF-fit source catalogs is better than $\approx 3$% for sources brighter than $\approx 12$ Vega mag, as calibrated against the 2MASS catalog. With a field of view $\approx 40\times$ larger than any other existing near infrared imaging instrument, Gattini-IR is probing the reddest and dustiest transients in the local universe such as dust obscured supernovae in nearby galaxies, novae behind large columns of extinction within the galaxy, reddened micro-lensing events in the Galactic plane and variability from cool and dust obscured stars. We present results from transients and variables identified since the start of the commissioning period.

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BibTeXRIS

Kishalay De, Matthew J. Hankins, Mansi M. Kasliwal, Anna M. Moore, Eran O. Ofek, Scott M. Adams, Michael C. B. Ashley, Aliya-Nur Babul, Ashot Bagdasaryan, Kevin B. Burdge, Jill Burnham, Richard G. Dekany, Alexander Declacroix, Antony Galla, Tim Greffe, David Hale, Jacob E. Jencson, Ryan M. Lau, Ashish Mahabal, Daniel McKenna, Manasi Sharma, Patrick L. Shopbell, Roger M. Smith, Jamie Soon, Jennifer Sokoloski, Roberto Soria, Tony Travouillon. 2019-10-29. Palomar Gattini-IR: Survey overview, data processing system, on-sky performance and first results. https://doi.org/10.1088/1538-3873%2Fab6069

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