Hostname: page-component-cd9895bd7-gvvz8 Total loading time: 0 Render date: 2024-12-28T03:24:21.814Z Has data issue: false hasContentIssue false
  • English
  • Français

GUASOM: Gaia Utility for Analysis and Knowledge Discovery based on Self Organizing Maps

Published online by Cambridge University Press:  17 July 2015

D. Fustes ,
M. Manteiga ,
C. Dafonte ,
B. Arcay ,
M.A. Alvarez  and
D. Garabato
D. Fustes*
Affiliation:
Computer Science Faculty, University of A Coruña, 15071 A Coruña, Spain
M. Manteiga*
Affiliation:
Computer Science Faculty, University of A Coruña, 15071 A Coruña, Spain
C. Dafonte*
Affiliation:
Computer Science Faculty, University of A Coruña, 15071 A Coruña, Spain
B. Arcay*
Affiliation:
Computer Science Faculty, University of A Coruña, 15071 A Coruña, Spain
M.A. Alvarez*
Affiliation:
Computer Science Faculty, University of A Coruña, 15071 A Coruña, Spain
D. Garabato*
Affiliation:
Computer Science Faculty, University of A Coruña, 15071 A Coruña, Spain
*
e-mail: [email protected]
e-mail: [email protected]
e-mail: [email protected]
e-mail: [email protected]
e-mail: [email protected]
e-mail: [email protected]
Get access

Abstract

We present a method for knowledge analysis in large astronomical spectrophotometric archives. The method is based on a type of unsupervised learning Artificial Neural Networks named Self-organizing maps (SOMs). SOMs 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.

Our algorithm has been tested by means of simulated Gaia spectrophotometry (150,000 objects), which is based on SDSS observations and theoretical spectral libraries covering a wide sample of astronomical objects. We demonstrate the usefulness of the method by analyzing over 10,000 objects, mostly fainted objects and unsuccessful observations, that were rejected by the SDSS spectroscopic classification pipeline and thus classified as “UNKNOWN”. This dataset was transformed to Gaia BP and RP format by the use of GOG simulator.

GUASOM provides a useful toolbox to study the data distribution in extense archives. Even more, the discovered neighbourhood relationships help to unveil the physical nature of objects never observed before. To this effect, we used the SIMBAD catalog to perform crossmatching with the SDSS astrometry, seeking for more identifications.

Type
Research Article
Information
European Astronomical Society Publications Series , Volume 68: The Milky Way Unravelled by Gaia: GREAT Science from the Gaia Data Releases , 2014 , pp. 373
Copyright
© EAS, EDP Sciences, 2015

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Fustes, D., Manteiga, M., Dafonte, C., et al., 2013, A&A, 559, A7