Journal
EXPERIMENTAL ASTRONOMY
Volume 39, Issue 1, Pages 45-71Publisher
SPRINGER
DOI: 10.1007/s10686-015-9443-4
Keywords
Techniques: photometric; Galaxies: distances and redshifts; Galaxies: photometry; Cosmology: observations; Methods: data analysis
Categories
Funding
- 7th European Framework Programme for Research Grant, VIALACTEA - The Milky Way as a Star Formation Engine [FP7-SPACE-2013-1]
- Project F.A.R.O. III Tornata (University Federico II of Naples)
- PRIN-MIUR
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Photometric redshifts (photo-z) are crucial to the scientific exploitation of modern panchromatic digital surveys. In this paper we present PhotoRApToR (Photometric Research Application To Redshift): a Java/C++ based desktop application capable to solve non-linear regression and multi-variate classification problems, in particular specialized for photo-z estimation. It embeds a machine learning algorithm, namely a multi-layer neural network trained by the Quasi Newton learning rule, and special tools dedicated to pre- and post-processing data. PhotoRApToR has been successfully tested on several scientific cases. The application is available for free download from the DAME Program web site.
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