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Clustering-based redshift estimation : application to VIPERS/CFHTLS

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Tojeiro_2016_MNRAS_VIPERSCFHTLS_FinalPubVersion.pdf (3.332Mb)
Date
08/07/2016
Author
Scottez, V.
Mellier, Y.
Granett, B. R.
Moutard, T.
Kilbinger, M.
Scodeggio, M.
Garilli, B.
Bolzonella, M.
de la Torre, S.
Guzzo, L.
Abbas, U.
Adami, C.
Arnouts, S.
Bottini, D.
Branchini, E.
Cappi, A.
Cucciati, O.
Davidzon, I.
Fritz, A.
Franzetti, P.
Iovino, A.
Krywult, J.
Le Brun, V.
Le Fèvre, O.
Maccagni, D.
Małek, K.
Marulli, F.
Polletta, M.
Pollo, A.
Tasca, L. A. M.
Tojeiro, R.
Vergani, D.
Zanichelli, A.
Bel, J.
Coupon, J.
De Lucia, G.
Ilbert, O.
McCracken, H. J.
Moscardini, L.
Keywords
Methods: data analysis
Surveys
Clustering
Galaxies: distances and redshifts
QB Astronomy
QC Physics
3rd-DAS
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Abstract
We explore the accuracy of the clustering-based redshift estimation proposed by Ménard et al. when applied to VIMOS Public Extragalactic Redshift Survey (VIPERS) and Canada–France–Hawaii Telescope Legacy Survey (CFHTLS) real data. This method enables us to reconstruct redshift distributions from measurement of the angular clustering of objects using a set of secure spectroscopic redshifts. We use state-of-the-art spectroscopic measurements with iAB < 22.5 from the VIPERS as reference population to infer the redshift distribution of galaxies from the CFHTLS T0007 release. VIPERS provides a nearly representative sample to a flux limit of iAB < 22.5 at a redshift of >0.5 which allows us to test the accuracy of the clustering-based redshift distributions. We show that this method enables us to reproduce the true mean colour–redshift relation when both populations have the same magnitude limit. We also show that this technique allows the inference of redshift distributions for a population fainter than the reference and we give an estimate of the colour–redshift mapping in this case. This last point is of great interest for future large-redshift surveys which require a complete faint spectroscopic sample.
Citation
Scottez , V , Mellier , Y , Granett , B R , Moutard , T , Kilbinger , M , Scodeggio , M , Garilli , B , Bolzonella , M , de la Torre , S , Guzzo , L , Abbas , U , Adami , C , Arnouts , S , Bottini , D , Branchini , E , Cappi , A , Cucciati , O , Davidzon , I , Fritz , A , Franzetti , P , Iovino , A , Krywult , J , Le Brun , V , Le Fèvre , O , Maccagni , D , Małek , K , Marulli , F , Polletta , M , Pollo , A , Tasca , L A M , Tojeiro , R , Vergani , D , Zanichelli , A , Bel , J , Coupon , J , De Lucia , G , Ilbert , O , McCracken , H J & Moscardini , L 2016 , ' Clustering-based redshift estimation : application to VIPERS/CFHTLS ' , Monthly Notices of the Royal Astronomical Society , vol. 462 , no. 2 , pp. 1683-1696 . https://doi.org/10.1093/mnras/stw1500
Publication
Monthly Notices of the Royal Astronomical Society
Status
Peer reviewed
DOI
https://doi.org/10.1093/mnras/stw1500
ISSN
0035-8711
Type
Journal article
Rights
© 2016 The Authors. Published by Oxford University Press on behalf of the Royal Astronomical Society. This work is made available online in accordance with the publisher’s policies. This is the final published version of the work, which was originally published at: https://dx.doi.org/10.1093/mnras/stw1500
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  • University of St Andrews Research
URL
https://arxiv.org/abs/1605.05501
http://adsabs.harvard.edu/abs/2016MNRAS.462.1683S
URI
http://hdl.handle.net/10023/10555

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