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PCA Tomography and Its Application to Nearby Galactic Nuclei

Published online by Cambridge University Press:  03 June 2010

J. E. Steiner ,
R. B. Menezes ,
T. V. Ricci  and
A. S. de Oliveira
J. E. Steiner
Affiliation:
IAG, Universidade de São Paulo, Rua do Matão, 1226, São Paulo - SP, Brazil
R. B. Menezes
Affiliation:
IAG, Universidade de São Paulo, Rua do Matão, 1226, São Paulo - SP, Brazil
T. V. Ricci
Affiliation:
IAG, Universidade de São Paulo, Rua do Matão, 1226, São Paulo - SP, Brazil
A. S. de Oliveira
Affiliation:
IP&D, Universidade do Vale do Paraiba, Av. Shishima Hifumi, 2911 CEP 12244-000, São José dos Campos, SP, Brazil Email: [email protected]
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Abstract

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With the development of modern technologies such as integral field units, it is possible to obtain data cubes in which one produces images with spectral resolution. Extracting information from them can be quite complex, and hence the development of new methods of data analysis is desirable. We briefly describe a method of analysis of data cubes (data from single field observations, containing two spatial and one spectral dimension) that uses principal component analysis to express the data in the form of reduced dimensionality, facilitating efficient information extraction from very large data sets. We applied the method, for illustrative purposes, to the central region of the LINER galaxy NGC 4736, and demonstrate that it has a type 1 active nucleus, which was not known before. Furthermore, we show that it is displaced from the center of its stellar bulge.

Keywords

methods: data analysismethods: statisticaltechniques: image processing
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 5 , Symposium S267: Co-Evolution of Central Black Holes and Galaxies , August 2009 , pp. 85 - 89
Copyright
Copyright © International Astronomical Union 2010

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