Toward Efficient Detection of Small Near-Earth Asteroids Using the Zwicky Transient Facility (ZTF)

We describe ZStreak, a semi-real-time pipeline specialized in detecting small, fast-moving, near-Earth asteroids (NEAs), which is currently operating on the data from the newly commissioned Zwicky Transient Facility (ZTF) survey. Based on a prototype originally developed by Waszczak et al. (2017) fo...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Publications of the Astronomical Society of the Pacific 2019-07, Vol.131 (1001), p.1-12
Hauptverfasser: Ye, Quanzhi, 叶 泉志, Masci, Frank J., Lin, Hsing Wen, 林 省文, Bolin, Bryce, Chang, Chan-Kao, 章 展誥, Duev, Dmitry A., Helou, George, Ip, Wing-Huen, 葉 永烜, Kaplan, David L., Kramer, Emily, Mahabal, Ashish, Ngeow, Chow-Choong, Nielsen, Avery J., Prince, Thomas A., Tan, Hanjie, 谭 瀚杰, Yeh, Ting-Shuo, 葉 庭碩, Bellm, Eric C., Dekany, Richard, Giomi, Matteo, Graham, Matthew J., Kulkarni, Shrinivas R., Kupfer, Thomas, Laher, Russ R., Rusholme, Ben, Shupe, David L., Ward, Charlotte
Format: Artikel
Sprache:eng
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:We describe ZStreak, a semi-real-time pipeline specialized in detecting small, fast-moving, near-Earth asteroids (NEAs), which is currently operating on the data from the newly commissioned Zwicky Transient Facility (ZTF) survey. Based on a prototype originally developed by Waszczak et al. (2017) for the Palomar Transient Factory (PTF), the predecessor of ZTF, ZStreak features an improved machine-learning model that can cope with the 10× data rate increment between PTF and ZTF. Since its first discovery on 2018 February 5 (2018 CL), ZTF/ZStreak has discovered 45 confirmed new NEAs over a total of 232 observable nights until 2018 December 31. Most of the discoveries are small NEAs, with diameters less than ∼100 m. By analyzing the discovery circumstances, we find that objects having the first to last detection time interval under 2 hr are at risk of being lost. We will further improve real-time follow-up capabilities, and work on suppressing false positives using deep learning.
ISSN:0004-6280
1538-3873