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.

We present a new pipeline based on the Support Vector Machine algorithm to confirm the detection and perform classification of small solar system objects by serendipitous stellar occultations. This pipeline is designed to analyze light curves and to identify the occultation events and the classification of the occulting bodies according to their size, typically from a fraction to a few kilometers, and their distance from the Sun, typically a few tens of astronomical units. The input light curves for this pipeline were obtained from the event simulator for the Trans-Neptunian Automated Occultation Survey (TAOS II). We explore parameters affecting occultation light curves such as spectral type, apparent magnitude and finite angular size of the occulted star, angle from opposition, and readout cadence for the observations; also we assumed a Poisson noise distribution as expected from the TAOS II project. We find that occultation events, especially by trans-Neptunian objects with diameters ≥2 km are detected with 99.99%, 99.53%, and 86% efficiency for stars with a visual apparent magnitude of 12, 14, and 16, respectively at 0.05 s of exposure time. In terms of size and distance classification the overall accuracy is 94%. However, for smaller objects the confirmation and classification depends mostly upon the signal-to-noise ratio.

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