The use of neural networks to probe the structure of the nearby universe

Details The use of neural networks to probe the structure of the nearby universe The use of neural networks to probe the structure of the nearby universe

2007-01-05

arxiv.org/abs/astro-ph/0701137v1

Astronomy and Astrophysics

Astrophysics

7 pages, 5 figures. To appear in the proceedings of the Astronomical Data Analysis -IV workshop held in Marseille in 2006. J.L

Scientific paper

In the framework of the European VO-Tech project, we are implementing new machine learning methods specifically tailored to match the needs of astronomical data mining. In this paper, we shortly present the methods and discuss an application to the Sloan Digital Sky Survey public data set. In particular, we discuss some preliminary results on the 3-D taxonomy of the nearby (z < 0.5) universe. Using neural networks trained on the available spectroscopic base of knowledge we derived distance estimates for ca. 30 million galaxies distributed over 8,000 sq. deg. We also use unsupervised clustering tools to investigate whether it is possible to characterize in broad morphological bins the nature of each object and produce a reliable list of candidate AGNs and QSOs.

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