The TAOS II Survey: Real-time Detection and Characterization of Occultation Events. (17th February 2021)

• Record Type: Journal Article
• Authors: Huang, Chung-Kai; Lehner, Matthew J.; Granados Contreras, Agueda Paula; Castro-Chacón, Joel H.; Chen, Wen-Ping; Alcock, Charles; Alvarez-Santana, Fernando I.; Cook, Kem H.; Geary, John C.; Guerrero Peña, Carlos Alberto; Hernández-Águila, Joannes Bosco; Hernández-Valencia, Benjamín; Karr, Jennifer; Kavelaars, J. J.; Norton, Timothy; Nuñez, Juan Manuel; Ochoa, Diego; Reyes-Ruiz, Mauricio; Sánchez, Edilberto; Silva, José Sergio; Szentgyorgyi, Andrew; Wang, Shiang-Yu; Yen, Wei-Ling; Zhang, Zhi-Wei
• Is Part Of: Publications of the Astronomical Society of the Pacific. Volume 133:Number 1021(2021)
• Publication Date: 2021-02-17
• Subjects: Trans-Neptunian objects -- Stellar occultation -- Astronomy data modeling -- Time domain astronomy -- Light curves; Astronomy -- Periodicals; Astronomy; Periodicals; Periodicals; 520.5
• DOI: 10.1088/1538-3873/abd4bc
• Languages: English
• ISSNs: 0004-6280

Abstract

Abstract: The Transneptunian Automated Occultation Survey (TAOS II) is a blind occultation survey with the aim of measuring the size distribution of Trans-Neptunian Objects with diameters in the range of 0.3 ≲ D ≲ 30 km. TAOS II will observe as many as 10, 000 stars at a cadence of 20 Hz with all three telescopes simultaneously. This will produce up to ∼20 billion photometric measurements per night, and as many as ∼6 trillion measurements per year, corresponding to over 70 million individual light curves. A very fast analysis pipeline for event detection and characterization is needed to handle this massive data set. The pipeline should be capable of real-time detection of events (within 24 hours of observations) for follow-up observations of any occultations by larger TNOs. In addition, the pipeline should be fast and scalable for large simulations where simulated events are added to the observed light curves to measure detection efficiency and biases in event characterization. Finally, the pipeline should provide estimates of the size of and distance to any occulting objects, including those with non-spherical shapes. This paper describes a new data analysis pipeline for the detection and characterization of occultation events.