The IPAC image subtraction and discovery pipeline for the intermediate palomar transient factory

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

Research output: Contribution to journalArticlepeer-review

70 Scopus citations


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.

Original languageEnglish (US)
Article number014002
JournalPublications of the Astronomical Society of the Pacific
Issue number971
StatePublished - Jan 1 2017
Externally publishedYes


  • Methods: analytical
  • Methods: data analysis
  • Methods: statistical
  • Techniques: image processing
  • Techniques: photometric

ASJC Scopus subject areas

  • Astronomy and Astrophysics
  • Space and Planetary Science


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