1. The TAOS Project: Statistical Analysis of Multi-Telescope Time Series Data
- Author
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S. L. Marshall, C.-Y. Wen, Megan E. Schwamb, John Rice, K. H. Cook, Dae-Won Kim, Pavlos Protopapas, Shiang-Yu Wang, Charles Alcock, Typhoon Lee, Yong-Ik Byun, I. de Pater, J.-H. Wang, Matthew J. Lehner, S. K. King, Wen Ping Chen, Tim Axelrod, N. K. Coehlo, Zhi-Wei Zhang, and Federica B. Bianco
- Subjects
Earth and Planetary Astrophysics (astro-ph.EP) ,0303 health sciences ,Series (mathematics) ,Computer science ,FOS: Physical sciences ,Flux ,Astronomy and Astrophysics ,01 natural sciences ,Occultation ,law.invention ,Data set ,Telescope ,03 medical and health sciences ,Stars ,Space and Planetary Science ,law ,0103 physical sciences ,Time series ,010303 astronomy & astrophysics ,Astrophysics - Earth and Planetary Astrophysics ,030304 developmental biology ,Remote sensing ,Event (probability theory) - Abstract
The Taiwanese-American Occultation Survey (TAOS) monitors fields of up to ~1000 stars at 5 Hz simultaneously with four small telescopes to detect occultation events from small (~1 km) Kuiper Belt Objects (KBOs). The survey presents a number of challenges, in particular the fact that the occultation events we are searching for are extremely rare and are typically manifested as slight flux drops for only one or two consecutive time series measurements. We have developed a statistical analysis technique to search the multi-telescope data set for simultaneous flux drops which provides a robust false positive rejection and calculation of event significance. In this paper, we describe in detail this statistical technique and its application to the TAOS data set., 15 pages, 14 figures. Submitted to PASP
- Published
- 2010
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