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arXiv · 2208.03269

An adaptive algorithm for detecting double stars in astrometric surveys

Mikhail V. Sazhin·Valerian Sementsov·Sergey Sorokin·Dan Lubarskiy·Alexander Raikov
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Abstract

The paper develops a method for detecting optical binary stars based on the use of astrometric catalogs in combination with machine learning (ML) methods. A computational experiment was carried out on the example of the HIPPARCOS mission catalog and the Pan-STARRS (PS1) catalog by applying the suggested method. It has shown that the reliability of predicting a stellar binarity reaches 90-95%. We note the prospects and effectiveness of creating a proprietary research platform - Cognotron.

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Mikhail V. Sazhin, Valerian Sementsov, Sergey Sorokin, Dan Lubarskiy, Alexander Raikov. 2022-08-05. An adaptive algorithm for detecting double stars in astrometric surveys. https://arxiv.org/abs/2208.03269

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