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QZO: A Catalog of 5 Million Quasars from the Zwicky Transient Facility
18 Feb 2025
Abstract
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 the Pan-STARRS
(PS), AllWISE, and Gaia surveys with extreme gradient boosting. Using ZTF
g-band data with at least 100 observational epochs per light curve, we obtain
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 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. We find that ZTF classification is superior to
the PS static bands, and on par with WISE and Gaia measurements. Additionally,
we find that the light curves provide the most important features for QSO
classification in the ZTF dataset. We robustly classify objects fainter than
the $5\sigma$ SNR limit at $g=20.8$ by requiring $g < \mathrm{n_{obs}} / 80 +
20.375$. For this sample, we run inference with added WISE observations, and
find 4,849,574 objects classified as QSOs. For 33% of QZO objects, with
available WISE data, we publish redshifts with estimated error $\Delta z/(1 +
z) = 0.14$.
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Details
- Title
- QZO: A Catalog of 5 Million Quasars from the Zwicky Transient Facility
- Creators
- S. J NakonecznyM. J GrahamD SternG HelouS. G DjorgovskiE. C BellmT. X ChenR DekanyA DrakeA. A MahabalT. A PrinceR RiddleB RusholmeN Sravan
- Resource Type
- Preprint
- Language
- English
- Academic Unit
- Physics
- Other Identifier
- 991022028048804721