The IPAC Image Subtraction and Discovery Pipeline for the intermediate Palomar Transient Factory

Creators: Masci, Frank J.; Laher, Russ R.; Rebbapragada, Umaa D.; Doran, Gary B.; Miller, Adam A.; Bellm, Eric; Kasliwal, Mansi; Ofek, Eran O.; Surace, Jason; Shupe, David L.; Grillmair, Carl J.; Jackson, Ed; Barlow, Tom; Yan, Lin; Cao, Yi; Cenko, S. Bradley; Storrie-Lombardi, Lisa J.; Helou, George; Prince, Thomas A.; Kulkarni, Shrinivas R.

Abstract

We describe the near real-time transient-source discovery engine for the intermediate Palomar Transient Factory (iPTF), currently in operations at the Infrared Processing and Analysis Center (IPAC), Caltech. We coin this system the IPAC/iPTF Discovery Engine (or IDE). We review the algorithms used for PSF-matching, image subtraction, detection, photometry, and machine-learned (ML) vetting of extracted transient candidates. We also review the performance of our ML classifier. For a limiting signal-to-noise ratio of 4 in relatively unconfused regions, bogus candidates from processing artifacts and imperfect image subtractions outnumber real transients by ≃10:1. This can be considerably higher for image data with inaccurate astrometric and/or PSF-matching solutions. Despite this occasionally high contamination rate, the ML classifier is able to identify real transients with an efficiency (or completeness) of ≃97% for a maximum tolerable false-positive rate of 1% when classifying raw candidates. All subtraction-image metrics, source features, ML probability-based real-bogus scores, contextual metadata from other surveys, and possible associations with known Solar System objects are stored in a relational database for retrieval by the various science working groups. We review our efforts in mitigating false-positives and our experience in optimizing the overall system in response to the multitude of science projects underway with iPTF.

Additional Information

© 2016 The Astronomical Society of the Pacific. Received 2016 August 5; accepted 2016 September 27; published 2016 December 8. This work was funded in part by the iPTF and ZTF projects at the California Institute of Technology. iPTF is a partnership led by the California Institute of Technology and includes the Infrared Processing & Astronomical Center; Los Alamos National Laboratory; University of Wisconsin at Milwaukee; Oskar-Klein Center of the University of Stockholm, Sweden; Weizmann Institute of Sciences, Israel; University System of Taiwan, Taiwan; the Institute for Physics & Mathematics of the universe, Japan; Lawrence Berkeley National Laboratory and the University of California, Berkeley. ZTF is funded by the National Science Foundation under grant no. AST-144034. M.M.K. acknowledges support from the National Science Foundation PIRE GROWTH award. A.A.M. acknowledges support for this work by NASA from a Hubble Fellowship grant: HST-HF-51325.01, awarded by STScI, operated by AURA, Inc., for NASA, under contract NAS 5-26555. Part of the research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with NASA. The pipelines use a number of software packages from other institutions and past projects (see Table 1), for which we are indebted. Portions of the analysis presented here made use of the Perl Data Language (PDL) developed by K. Glazebrook, J. Brinchmann, J. Cerney, C. DeForest, D. Hunt, T. Jenness, T. Lukka, R. Schwebel, and C. Soeller and can be obtained from http://pdl.perl.org. PDL provides a high-level numerical functionality for the Perl scripting language (Glazebrook & Economou 1997). We thank the anonymous referee for valuable comments that helped improve the quality of this manuscript. Facility: PO:1.2m.

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