The IPAC Image Subtraction and Discovery Pipeline for the Intermediate Palomar Transient Factory. (8th December 2016)

• Record Type: Journal Article
• Authors: 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.
• Is Part Of: Publications of the Astronomical Society of the Pacific. Volume 129:Number 971(2017)
• Publication Date: 2016-12-08
• Subjects: methods: analytical -- methods: data analysis -- methods: statistical -- techniques: image processing -- techniques: photometric; Astronomy -- Periodicals; Astronomy; Periodicals; Periodicals; 520.5
• DOI: 10.1088/1538-3873/129/971/014002
• Languages: English
• ISSNs: 0004-6280

Abstract

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.