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arXiv · 1705.01722

Searching for Moving Objects in HSC-SSP: Pipeline and Preliminary Results

Ying-Tung Chen·Hsing-Wen Lin·Mike Alexandersen·Matthew J. Lehner·Shiang-Yu Wang·Jen-Hung Wang·Fumi Yoshida·Yutaka Komiyama·Satoshi Miyazaki
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Abstract

The Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) is currently the deepest wide- field survey in progress. The 8.2 m aperture of Subaru telescope is very powerful in detect- ing faint/small moving objects, including near-Earth objects, asteroids, centaurs and Tran- Neptunian objects (TNOs). However, the cadence and dithering pattern of the HSC-SSP are not designed for detecting moving objects, making it difficult to do so systematically. In this paper, we introduce a new pipeline for detecting moving objects (specifically TNOs) in a non-dedicated survey. The HSC-SSP catalogs are re-arranged into the HEALPix architecture. Then, the stationary detections and false positive are removed with a machine learning al- gorithm to produce a list of moving object candidates. An orbit linking algorithm and visual inspections are executed to generate the final list of detected TNOs. The preliminary results of a search for TNOs using this new pipeline on data from the first HSC-SSP data release (Mar 2014 to Nov 2015) are also presented.

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Ying-Tung Chen, Hsing-Wen Lin, Mike Alexandersen, Matthew J. Lehner, Shiang-Yu Wang, Jen-Hung Wang, Fumi Yoshida, Yutaka Komiyama, Satoshi Miyazaki. 2017-05-04. Searching for Moving Objects in HSC-SSP: Pipeline and Preliminary Results. https://doi.org/10.1093/pasj%2Fpsx145

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