Poster Abstract

P10.45 Ylse Anna de Vries (Kapteyn Astronomical Institute, University of Groningen)

Theme: Data processing pipelines

Data mining the Kilo-Degree Survey for Solar System objects

I present the results of my Bachelor research project. I started with an existing data processing pipeline to discover Solar System Objects (SSOs) in the Kilo-Degree Survey (KiDS) Data Release 4 (DR4) and added further functionality to characterize the nature of the new SSO detections. The detection pipeline uses calibrated single KiDS exposures stored in the Astro-WISE system and applies catalog filtering to find moving objects and to take out false positives.

Using the detection pipeline on DR4 yielded new SSO candidates in a number of fields adding to the 20221 candidates from DR3, with an estimated false positive rate of 0.05%. Exploring how to further constrain the nature of the new SSO candidates yielded two tentative approaches: a simplified method of population estimation for the SSOs, and a method of estimating the admissible distance based on its motion and photometric magnitude. These approaches are currently implemented as python notebooks and are extensions of the detection pipeline, to aid in understanding and selecting samples for further study.

In my contribution I present the detection pipeline software and my characterization software. I also discuss the potential of automated serendipitous discovery of SSOs in wide-field surveys designed for extragalactic science.