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Title: Machine Learning for the Zwicky Transient Facility

Journal Article · · Publications of the Astronomical Society of the Pacific
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  1. California Inst. of Technology (CalTech), Pasadena, CA (United States)
  2. California Inst. of Technology (CalTech), Pasadena, CA (United States). Jet Propulsion Lab. (JPL)
  3. California Inst. of Technology (CalTech), Pasadena, CA (United States). Caltech Optical Observatories
  4. Radboud Univ., Nijmegen (Netherlands)
  5. Stockholm Univ. (Sweden)
  6. National Central Univ. (Taiwan)
  7. Univ. of Washington, Seattle, WA (United States)
  8. Northwestern Univ., Evanston, IL (United States); The Adler Planetarium, Chicago, IL (United States)
  9. Humboldt Univ. of Berlin (Germany)
  10. Univ. of Maryland, College Park, MD (United States)
  11. Space Telescope Science Inst., Baltimore, MD (United States)
  12. Univ. of Oxford (United Kingdom); Univ. of Minnesota, Minneapolis, MN (United States)
  13. California Inst. of Technology (CalTech), Pasadena, CA (United States); Univ. of California, Santa Barbara, CA (United States)
  14. National Central Univ. (Taiwan); Univ. of Michigan, Ann Arbor, MI (United States)
  15. Univ. of Oxford (United Kingdom)
  16. Univ. of Freiburg (Germany)
  17. NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States); Univ. of Maryland, College Park, MD (United States). Joint Space-Science Inst.
  18. Weizmann Inst. of Science, Rehovot (Israel)
  19. California Inst. of Technology (CalTech), Pasadena, CA (United States); Tokyo Inst. of Technology, Meguro-ku, Tokyo (Japan)

The Zwicky Transient Facility is a large optical survey in multiple filters producing hundreds of thousands of transient alerts per night. We describe here various machine learning (ML) implementations and plans to make the maximal use of the large data set by taking advantage of the temporal nature of the data, and further combining it with other data sets. We start with the initial steps of separating bogus candidates from real ones, separating stars and galaxies, and go on to the classification of real objects into various classes. Besides the usual methods (e.g., based on features extracted from light curves) we also describe early plans for alternate methods including the use of domain adaptation, and deep learning. In a similar fashion we describe efforts to detect fast moving asteroids. We also describe the use of the Zooniverse platform for helping with classifications through the creation of training samples, and active learning. Finally we mention the synergistic aspects of ZTF and LSST from the ML perspective.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC); National Science Foundation (NSF); Weizmann Institute of Science; National Aeronautics and Space Administration (NASA)
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
1580382
Journal Information:
Publications of the Astronomical Society of the Pacific, Journal Name: Publications of the Astronomical Society of the Pacific Journal Issue: 997 Vol. 131; ISSN 0004-6280
Publisher:
Astronomical Society of the Pacific (ASP)Copyright Statement
Country of Publication:
United States
Language:
English

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First Results from the Catalina Real-time Transient Survey text January 2008
The Palomar Transient Factory: System Overview, Performance and First Results text January 2009
On Machine-Learned Classification of Variable Stars with Sparse and Noisy Time-Series Data text January 2011
Active Learning to Overcome Sample Selection Bias: Application to Photometric Variable Star Classification text January 2011
313 new asteroid rotation periods from Palomar Transient Factory observations text January 2014
The Catalina Surveys Periodic Variable Star Catalog text January 2014
ANTARES: A Prototype Transient Broker System text January 2014
Machine learning for transient discovery in Pan-STARRS1 difference imaging text January 2015
Automated Transient Identification in the Dark Energy Survey text January 2015
Asteroid lightcurves from the Palomar Transient Factory survey: Rotation periods and phase functions from sparse photometry text January 2015
A Package for the Automated Classification of Periodic Variable Stars text January 2015
Proper image subtraction - optimal transient detection, photometry and hypothesis testing text January 2016
Volumetric Survey Speed: A Figure of Merit for Transient Surveys text January 2016
Deep Recurrent Neural Networks for Supernovae Classification text January 2016
Small near-Earth asteroids in the Palomar Transient Factory survey: A real-time streak-detection system text January 2016
RATIR Followup of LIGO/Virgo Gravitational Wave Events text January 2017
Machine Learning-based Brokers for Real-time Classification of the LSST Alert Stream text January 2018
The ASAS-SN Catalog of Variable Stars I: The Serendipitous Survey text January 2018
Optimizing spectroscopic follow-up strategies for supernova photometric classification with active learning text January 2018
The Zwicky Transient Facility: Data Processing, Products, and Archive text January 2019
The Zwicky Transient Facility: System Overview, Performance, and First Results text January 2019
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A box-fitting algorithm in the search for periodic transits text January 2002
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Cited By (17)

Surveying the reach and maturity of machine learning and artificial intelligence in astronomy journal September 2019
Transient processing and analysis using AMPEL: alert management, photometry, and evaluation of light curves journal November 2019
2900 Square Degree Search for the Optical Counterpart of Short Gamma-Ray Burst GRB 180523B with the Zwicky Transient Facility journal February 2019
Toward Efficient Detection of Small Near-Earth Asteroids Using the Zwicky Transient Facility (ZTF) journal May 2019
The Zwicky Transient Facility: Observing System journal January 2020
Palomar Gattini-IR: Survey Overview, Data Processing System, On-sky Performance and First Results journal January 2020
Transient processing and analysis using AMPEL: alert management, photometry, and evaluation of light curves text January 2019
GROWTH on S190425z: Searching Thousands of Square Degrees to Identify an Optical or Infrared Counterpart to a Binary Neutron Star Merger with the Zwicky Transient Facility and Palomar Gattini-IR text January 2019
A New Class of Changing-look LINERs journal September 2019
Evidence for Late-stage Eruptive Mass Loss in the Progenitor to SN2018gep, a Broad-lined Ic Supernova: Pre-explosion Emission and a Rapidly Rising Luminous Transient journal December 2019
Discovery of an Intermediate-luminosity Red Transient in M51 and Its Likely Dust-obscured, Infrared-variable Progenitor journal July 2019
GROWTH on S190425z: Searching Thousands of Square Degrees to Identify an Optical or Infrared Counterpart to a Binary Neutron Star Merger with the Zwicky Transient Facility and Palomar Gattini-IR journal October 2019
2900 square degree search for the optical counterpart of short gamma-ray burst GRB 180523B with the Zwicky Transient Facility text January 2019
Transient processing and analysis using $\texttt{AMPEL}$: Alert Management, Photometry and Evaluation of Lightcurves text January 2019
Discovery of an intermediate-luminosity red transient in M51 and its likely dust-obscured, infrared-variable progenitor text January 2019
Evidence for Late-stage Eruptive Mass-loss in the Progenitor to SN2018gep, a Broad-lined Ic Supernova: Pre-explosion Emission and a Rapidly Rising Luminous Transient text January 2019
Palomar Gattini-IR: Survey overview, data processing system, on-sky performance and first results text January 2019

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