Abstract
Binary and multiple stellar systems have been observed using various methods and tools. Catalogs of binaries of different observational types are independent and use inherent star identification systems. Catalog rows describing components of stellar systems refer to identifiers of surveys and catalogs of single stars. The problem of cross-identification of stellar objects contained in sky surveys and catalogs of binaries of different observational types requires not only combining lists of existing identifiers of binary stars, but rather matching components and of multiple systems and pairs of components by their astrometric and astrophysical parameters. Existing identifiers are verified for belonging to matched components, pairs and systems. After that, they may be matched to one another. The framework of multiple system cross-matching presented in the paper uses domain knowledge of binaries of different observational types to form sets of matching criteria. The Identification List of Binaries (ILB) has been created after accurate matching of systems, their components and pairs of all observational types. This work continues research of binary and multiple system identification methods.
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Acknowledgements
This work has been supported by the Russian Foundation for Basic Research (grants 16-07-01162, 16-07-01028, 18-07-01434).
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Skvortsov, N.A., Kalinichenko, L.A., Karchevsky, A.V., Kovaleva, D.A., Malkov, O.Y. (2018). Matching and Verification of Multiple Stellar Systems in the Identification List of Binaries. In: Kalinichenko, L., Manolopoulos, Y., Malkov, O., Skvortsov, N., Stupnikov, S., Sukhomlin, V. (eds) Data Analytics and Management in Data Intensive Domains. DAMDID/RCDL 2017. Communications in Computer and Information Science, vol 822. Springer, Cham. https://doi.org/10.1007/978-3-319-96553-6_8
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