Palomar gattini-ir: Survey overview, data processing system, on-sky performance and first results

dc.contributor.authorDe, Kishalay
dc.contributor.authorHankins, Matthew J.
dc.contributor.authorKasliwal, M M
dc.contributor.authorMoore, Anna
dc.contributor.authorOfek, Eran
dc.contributor.authorAdams, Scott M
dc.contributor.authorAshley, Michael
dc.contributor.authorBabul, Aliya-Nur
dc.contributor.authorBagdasaryan, Ashot
dc.contributor.authorBurdge, Kevin B.
dc.contributor.authorBurnham, Jill
dc.contributor.authorGalla, Antony
dc.contributor.authorSoon, Jamie
dc.contributor.authorTravouillon, Tony
dc.date.accessioned2023-04-04T23:49:50Z
dc.date.issued2020
dc.date.updated2022-01-16T07:23:00Z
dc.description.abstractPalomar Gattini-IR is a new wide-field, near-infrared (NIR) 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 (FOV) of 25 sq. deg. with a pixel scale of 8farcs7 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 ≈7500 square degrees of the sky every night to a median 5σ depth of 15.7 AB mag outside the Galactic plane. The survey covers ≈15,000 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 point-spread function (PSF)-fit source catalogs and transient candidates identified from subtractions within a median delay of ≈4 hr from the time of observation. The calibrated data products achieve an astrometric accuracy (rms) of ≈0farcs7 with respect to Gaia DR2 for sources with signal-to-noise ratio > 10, and better than ≈0farcs35 for sources brighter than ≈12 Vega mag. The photometric accuracy (rms) achieved in the PSF-fit source catalogs is better than ≈3% for sources brighter than ≈12 Vega mag and fainter than the saturation magnitude of ≈8.5 Vega mag, as calibrated against the Two Micron All Sky Survey catalog. The detection efficiency of transient candidates injected into the images is better than 90% for sources brighter than the 5σ limiting magnitude. The photometric recovery precision of injected sources is 3% for sources brighter than 13 mag, and the astrometric recovery rms is ≈0farcs9. Reference images generated by stacking several field visits achieve depths of ≳16.5 AB mag over 60% of the sky, while it is limited by confusion in the Galactic plane. With a FOV ≈40× larger than any other existing NIR 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 microlensing 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.en_AU
dc.description.sponsorshipM.M.K. and E.O. acknowledge the US-Israel Binational Science Foundation Grant 2016227. M.M.K. and J.L.S. acknowledge the Heising-Simons foundation for support via a Scialog fellowship of the Research Corporation. M.M.K. and A.M.M. acknowledge the Mt Cuba foundation. J. Soon is supported by an Australian Government Research Training Program (RTP) Scholarship. SED Machine is based upon work supported by the National Science Foundation under Grant No. 1106171.en_AU
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.issn0004-6280en_AU
dc.identifier.urihttp://hdl.handle.net/1885/288092
dc.language.isoen_AUen_AU
dc.publisherUniversity of Chicago Pressen_AU
dc.rights© 2020. The Astronomical Society of the Pacific.en_AU
dc.sourcePublications of the Astronomical Society of the Pacificen_AU
dc.subjectastronomical databases: miscellaneousen_AU
dc.subjectcatalogsen_AU
dc.subjectinfrared: generalen_AU
dc.subjectmethods: data analysisen_AU
dc.subjectsurveysen_AU
dc.subjecttechniques: image processingen_AU
dc.subjecttechniques: photometricen_AU
dc.titlePalomar gattini-ir: Survey overview, data processing system, on-sky performance and first resultsen_AU
dc.typeJournal articleen_AU
local.bibliographicCitation.issue1008en_AU
local.bibliographicCitation.lastpage31en_AU
local.bibliographicCitation.startpage1en_AU
local.contributor.affiliationDe, Kishalay, California Institute of Technologyen_AU
local.contributor.affiliationHankins, Matthew J., California Institute of Technologyen_AU
local.contributor.affiliationKasliwal, M M, California Institute of Technologyen_AU
local.contributor.affiliationMoore, Anna, College of Science, ANUen_AU
local.contributor.affiliationOfek, Eran, Weizmann Institute of Scienceen_AU
local.contributor.affiliationAdams, Scott M, California Institute of Technologyen_AU
local.contributor.affiliationAshley, Michael, University of New South Walesen_AU
local.contributor.affiliationBabul, Aliya-Nur, Columbia Universityen_AU
local.contributor.affiliationBagdasaryan, Ashot, California Institute of Technologyen_AU
local.contributor.affiliationBurdge, Kevin B., California Institute of Technologyen_AU
local.contributor.affiliationBurnham, Jill, California Institute of Technologyen_AU
local.contributor.affiliationGalla, Antony, College of Science, ANUen_AU
local.contributor.affiliationSoon, Jamie, College of Science, ANUen_AU
local.contributor.affiliationTravouillon, Tony, College of Science, ANUen_AU
local.contributor.authoremailu1036159@anu.edu.auen_AU
local.contributor.authoruidMoore, Anna, u1036159en_AU
local.contributor.authoruidGalla, Antony, u1062088en_AU
local.contributor.authoruidSoon, Jamie, u6333999en_AU
local.contributor.authoruidTravouillon, Tony, u1057001en_AU
local.description.embargo2099-12-31
local.description.notesImported from ARIESen_AU
local.identifier.absfor401001 - Engineering designen_AU
local.identifier.absfor510102 - Astronomical instrumentationen_AU
local.identifier.absfor461208 - Software testing, verification and validationen_AU
local.identifier.absseo280115 - Expanding knowledge in the information and computing sciencesen_AU
local.identifier.absseo280110 - Expanding knowledge in engineeringen_AU
local.identifier.absseo280120 - Expanding knowledge in the physical sciencesen_AU
local.identifier.ariespublicationu6269649xPUB894en_AU
local.identifier.citationvolume132en_AU
local.identifier.doi10.1088/1538-3873/ab6069en_AU
local.identifier.scopusID2-s2.0-85078765269
local.identifier.uidSubmittedByu6269649en_AU
local.publisher.urlhttps://iopscience.iop.org/article/10.1088/1538-3873/ab6069en_AU
local.type.statusPublished Versionen_AU

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