Mining the Kilo-Degree Survey for solar system objects
M. Mahlke, H. Bouy, B. Altieri, G. Verdoes Kleijn, B. Carry, E., Bertin, J. T. A. de Jong, K. Kuijken, J. McFarland, E. Valentijn

TL;DR
This paper presents a method to detect and analyze solar system objects in wide imaging surveys, demonstrated on the KiDS survey, enabling discovery of new objects and improving understanding of the solar system's formation.
Contribution
The paper introduces a novel, efficient method for identifying and characterizing solar system objects in dithered survey data, applicable to multiple large-scale astronomical surveys.
Findings
Detected 20,221 SSO candidates with less than 0.05% false positives.
Identified 53.4% of candidates as known objects using SkyBoT.
Potential discovery of many new SSOs due to survey depth and coverage.
Abstract
The search for minor bodies in the solar system promises insights into its formation history. Wide imaging surveys offer the opportunity to serendipitously discover and identify these traces of planetary formation and evolution. We aim to present a method to acquire position, photometry, and proper motion measurements of solar system objects in surveys using dithered image sequences. The application of this method on the Kilo-Degree Survey is demonstrated. Optical images of 346 square degree fields of the sky are searched in up to four filters using the AstrOmatic software suite to reduce the pixel to catalog data. The solar system objects within the acquired sources are selected based on a set of criteria depending on their number of observation, motion, and size. The Virtual Observatory SkyBoT tool is used to identify known objects. We observed 20,221 SSO candidates, with an estimated…
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