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Photometric identification of quasars from the Sloan Survey

Published online by Cambridge University Press:  01 August 2006

Rameshwar P. Sinha ,
Ninan S. Philip ,
Ajit K. Kembahvi  and
Ashish A. Mahabal
Rameshwar P. Sinha
Affiliation:
Inter-University Centre for Astronomy and Astrophysics (IUCAA), Post Bag 4, Ganeshkhind, Pune University Campus, Pune 411 007, India email: rsinha@iucaa.ernet.in, akk@iucaa.ernet.in
Ninan S. Philip
Affiliation:
St. Thomas College, Kozhencheri, Kerala, India
Ajit K. Kembahvi
Affiliation:
Inter-University Centre for Astronomy and Astrophysics (IUCAA), Post Bag 4, Ganeshkhind, Pune University Campus, Pune 411 007, India email: rsinha@iucaa.ernet.in, akk@iucaa.ernet.in
Ashish A. Mahabal
Affiliation:
Astronomy Department, California Institute of Technology, Pasadena, CA 91125, USA email: milan@astro.caltech.edu
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We have developed a neural network based technique for identifying quasars from the photometric database of the Sloan Digital Sky Survey (SDSS). We have queried the SDSS data release 5 (DR5) to produce a dataset of spectroscopically identified samples of unresolved objects consisting of quasars and stars which forms the training set.

Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 2 , Highlights of Astronomy 14: Highlights of Astronomy , August 2006 , pp. 609
Copyright
Copyright © International Astronomical Union 2007