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QZO: A Catalog of 5 Million Quasars from the Zwicky Transient Facility
Journal article   Open access   Peer reviewed

QZO: A Catalog of 5 Million Quasars from the Zwicky Transient Facility

S. J. Nakoneczny, M. J. Graham, D. Stern, G. Helou, S. G. Djorgovski, E. C. Bellm, T. X. Chen, R. Dekany, A. Drake, A. A. Mahabal, …
The Astrophysical journal, v 992(1), 153
01 Jan 2025
url
https://doi.org/10.3847/1538-4357/adf4e4View
Published, Version of Record (VoR) Open

Abstract

Active galactic nuclei Catalogs Classification Light curves Neural networks Quasars
Machine learning methods are well established in the classification of quasars (QSOs). However, the advent of light-curve observations adds a great amount of complexity to the problem. Our goal is to use the Zwicky Transient Facility (ZTF) to create a catalog of QSOs. We process the ZTF DR20 light curves with a transformer artificial neural network and combine different surveys with extreme gradient boosting. Based on ZTF g -band and Wide-field Infrared Survey Explorer (WISE) observations, we find 4,849,574 objects classified as QSOs with confidence higher than 90% (QZO). We robustly classify objects fainter than the 5 σ signal-to-noise ratio (SNR) limit at g = 20.8 by requiring g  <  n _obs /80 + 20.375. For 33% of QZO objects, with available WISE data, we publish redshifts with estimated error Δ z /(1 +  z ) = 0.14. We find that ZTF classification is superior to the Pan-STARRS static bands, and on par with WISE and Gaia measurements, but the light curves provide the most important features for QSO classification in the ZTF data set. Using ZTF g -band data with at least 100 observational epochs per light curve, we obtain a 97% F1 score for QSOs. We find that with 3 day median cadence, a survey time span of at least 900 days is required to achieve a 90% QSO F1 score. However, one can obtain the same score with a survey time span of 1800 days and the median cadence prolonged to 12 days.

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Domestic collaboration
Web of Science research areas
Astronomy & Astrophysics
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