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A cooperative approach among methods for photometric redshifts estimation: an application to KiDS data

Cavuoti, S. and Tortora, C. and Brescia, M. and Longo, G. and Radovich, M. and Napolitano, N. R. and Amaro, V. and Vellucci, C. and La Barbera, F. and Getman, F. and Grado, A. (2017) A cooperative approach among methods for photometric redshifts estimation: an application to KiDS data. Monthly Notices of the Royal Astronomical Society, 466 (2). pp. 2039-2053. ISSN 0035-8711.

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Photometric redshifts (photo-z) are fundamental in galaxy surveys to address different topics, from gravitational lensing and dark matter distribution to galaxy evolution. The Kilo Degree Survey (KiDS), i.e. the European Southern Observatory (ESO) public survey on the VLT Survey Telescope (VST), provides the unprecedented opportunity to exploit a large galaxy data set with an exceptional image quality and depth in the optical wavebands. Using a KiDS subset of about 25000 galaxies with measured spectroscopic redshifts, we have derived photo-z using (i) three different empirical methods based on supervised machine learning; (ii) the Bayesian photometric redshift model (or BPZ); and (iii) a classical spectral energy distribution (SED) template fitting procedure (le phare). We confirm that, in the regions of the photometric parameter space properly sampled by the spectroscopic templates, machine learning methods provide better redshift estimates, with a lower scatter and a smaller fraction of outliers. SED fitting techniques, however, provide useful information on the galaxy spectral type, which can be effectively used to constrain systematic errors and to better characterize potential catastrophic outliers. Such classification is then used to specialize the training of regression machine learning models, by demonstrating that a hybrid approach, involving SED fitting and machine learning in a single collaborative framework, can be effectively used to improve the accuracy of photo-z estimates.

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Additional Information:© 2016 The Authors. Published by Oxford University Press on behalf of the Royal Astronomical Society. Received: 02 May 2016. Revision Received: 07 December 2016. Accepted: 07 December 2016. The authors would like to thank the anonymous referee for extremely valuable comments and suggestions. Based on data products from observations made with European Southern Observatory (ESO) telescopes at the La Silla Paranal Observatory under programme IDs 177.A-3016, 177.A-3017 and 177.A-3018, and on data products produced by Target/OmegaCEN, Istituto Nazionale di Astro Fisica (INAF)-Osservatorio Astronomico di Capodmonte Napoli (OACN), INAF-Osservatorio Astronomico di Padova (OAPD) and the KiDS production team, on behalf of the KiDS consortium. OmegaCEN and the KiDS production team acknowledge support by NOVA and NWO-M grants. Members of INAF-OAPD and INAF-OACN also acknowledge the support from the Department of Physics & Astronomy, University of Padova, and from the Department of Physics, Univ. Federico II (Naples). CT is supported through an NWO-VICI grant (project number 639.043.308). MB and SC acknowledge financial contribution from the agreement ASI/INAF I/023/12/1. MB acknowledges the PRIN-INAF 2014: ‘Glittering kaleidoscopes in the sky: the multifaceted nature and role of galaxy clusters’. GL acknowledges for partial funding from PRIN-MIUR 2011: The ‘Dark universe and the cosmic evolution of baryons: from present day surveys to Euclid’.
Funding AgencyGrant Number
Nederlandse Onderzoekschool voor de Astronomie (NOVA)UNSPECIFIED
University of PadovaUNSPECIFIED
University of Federico IIUNSPECIFIED
Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO)639.043.308
Agenzia Spaziale Italiana (ASI)I/023/12/1
Istituto Nazionale di Astrofisica (INAF)UNSPECIFIED
Ministero dell'Istruzione, dell'Università e della Ricerca (MIUR)UNSPECIFIED
Subject Keywords:methods: data analysis, catalogues
Issue or Number:2
Record Number:CaltechAUTHORS:20170417-080608577
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Official Citation:A cooperative approach among methods for photometric redshifts estimation: an application to KiDS data Cavuoti, S. Tortora, C. Brescia, M. Longo, G. Radovich, M. Napolitano, N. R. Amaro, V. Vellucci, C. La Barbera, F. Getman, F. Grado, A. 2017/04/11 10.1093/mnras/stw3208 Monthly Notices of the Royal Astronomical Society 2039 - 2053, V.466, IS 2
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:76586
Deposited By: Ruth Sustaita
Deposited On:17 Apr 2017 16:04
Last Modified:03 Oct 2019 17:02

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