In the era of massive astronomical datasets, efficient identification of candidate quasars and the reconstruction of their three dimensional distribution in the Universe is a key requirement for constraining some of the main issues regarding the formation and evolution of QSOs. A method for the determination of photometric redshifts of QSOs based on multiwavelength photometry and on a combination of data mining techniques will be discussed. This procedure, specifically suited for accompanying the candidate selection method discussed in (D’Abrusco et al. 2008), makes use of specific tools developed under the EuroVO and NVO frameworks for data gathering, pre-processing and mining, while relying on the scaling capabilities of the computing grid. This method allowed us to obtain photometric redshifts with an increased accuracy (up to 30%) with respect to the literature.

A web application for photometric redshift estimation

BRESCIA M;A. CORAZZA;G. LONGO;
2009

Abstract

In the era of massive astronomical datasets, efficient identification of candidate quasars and the reconstruction of their three dimensional distribution in the Universe is a key requirement for constraining some of the main issues regarding the formation and evolution of QSOs. A method for the determination of photometric redshifts of QSOs based on multiwavelength photometry and on a combination of data mining techniques will be discussed. This procedure, specifically suited for accompanying the candidate selection method discussed in (D’Abrusco et al. 2008), makes use of specific tools developed under the EuroVO and NVO frameworks for data gathering, pre-processing and mining, while relying on the scaling capabilities of the computing grid. This method allowed us to obtain photometric redshifts with an increased accuracy (up to 30%) with respect to the literature.
978-88-95892-02-3
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/900816
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