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\begin{document}

\title{IDENTIFYING CANDIDATES FOR FREE-FLOATING ARTIFACTS IN THE SOLAR SYSTEM}



\author[1]{Virisha Timmaraju}%
\author[2]{George Djorgovski}%
\affil[1]{NASA Jet Propulsion Laboratory}%
\affil[2]{California Institute of Technology}%


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  \date{May 18, 2024}


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\begin{abstract}
One approach to a search for the artifacts within the Solar system is to
look for the objects (e.g., probes, defunct or active) with anomalous
orbits that are significantly different from those of the asteroids. To
this effect, we used the data on the orbital parameters of 524,214
asteroids from AstDys-2. Approximately 24\% of the asteroids belong to
the known families in the orbital parameter space. The unclassified ones
are labeled as the `background', produced mainly by the dynamical
scattering in the course of the evolution of the solar system. We apply
Machine Learning tools to identify objectively defined outliers in the
feature space of orbital parameters. Various techniques can be used for
this task, including DBSCAN, which use distance measures, and Isolation
Forest, which use decision trees, and many others.%
\end{abstract}%



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