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          Institute: MPI für Astronomie     Collection: Publikationen_mpia     Display Documents

ID: 693741.0, MPI für Astronomie / Publikationen_mpia
An approach to the analysis of SDSS spectroscopic outliers based on self-organizing maps. Designing the outlier analysis software package for the next Gaia survey
Authors:Fustes, D.; Manteiga, M.; Dafonte, C.; Arcay, B.; Ulla, A.; Smith, K.; Borrachero, R.; Sordo, R.
Date of Publication (YYYY-MM-DD):2013
Title of Journal:Astronomy and Astrophysics
Start Page:id.A7 (10 pp)
Audience:Not Specified
Abstract / Description:<BR /> Aims: A new method applied to the segmentation and further analysis of the outliers resulting from the classification of astronomical objects in large databases is discussed. The method is being used in the framework of the Gaia satellite Data Processing and Analysis Consortium (DPAC) activities to prepare automated software tools that will be used to derive basic astrophysical information that is to be included in final Gaia archive. <BR /> Methods: Our algorithm has been tested by means of simulated Gaia spectrophotometry, which is based on SDSS observations and theoretical spectral libraries covering a wide sample of astronomical objects. Self-organizing maps networks are used to organize the information in clusters of objects, as homogeneously as possible according to their spectral energy distributions, and to project them onto a 2D grid where the data structure can be visualized. <BR /> Results: We demonstrate the usefulness of the method by analyzing the spectra that were rejected by the SDSS spectroscopic classification pipeline and thus classified as "UNKNOWN". First, our method can help distinguish between astrophysical objects and instrumental artifacts. Additionally, the application of our algorithm to SDSS objects of unknown nature has allowed us to identify classes of objects with similar astrophysical natures. In addition, the method allows for the potential discovery of hundreds of new objects, such as white dwarfs and quasars. Therefore, the proposed method is shown to be very promising for data exploration and knowledge discovery in very large astronomical databases, such as the archive from the upcoming Gaia mission.
Free Keywords:Galaxy: general; methods: data analysis; methods: statistical; methods: miscellaneous
External Publication Status:published
Document Type:Article
Communicated by:N. N.
Affiliations:MPI für Astronomie
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