Volume 576, April 2015
|Number of page(s)||15|
|Published online||17 March 2015|
High redshift galaxies in the ALHAMBRA survey
I. Selection method and number counts based on redshift PDFs⋆
Centro de Estudios de Física del Cosmos de Aragón, Plaza San Juan 1, planta
2 Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, 05508-090 São Paulo, Brazil
3 Instituto de Astrofísica de Andalucía (IAA-CSIC), Glorieta de la astronomía s/n, 18008 Granada, Spain
4 Instituto de Física de Cantabria, Avenida de los Castros s/n, 39005 Santander, Spain
5 Unidad Asociada Observatori Astronomic (IFCA-UV), C/ Catedrático José Beltrán 2, 46980 Paterna, Spain
6 GEPI, Paris Observatory, 77 av. Denfert Rochereau, 75014 Paris, France
7 Instituto de Astrofísica de Canarias, Vía Láctea s/n, La Laguna, 38200 Tenerife, Spain
8 Departamento de Astrofísica, Facultad de Física, Universidad de la Laguna, 38200 La Laguna, Spain
9 Institute for Astronomy, University of Edinburgh, Royal Observatory, Blackford Hill, Edinburgh EH9 3HJ, UK
10 European Southern Observatory, Karl-Schwarzschild-Str. 2, 85748 Garching, Germany
11 Observatório Nacional, COAA, Rua General José Cristino 77, 20921-400 Rio de Janeiro, Brazil
12 Department of Theoretical Physics, University of the Basque Country UPV/EHU, Bilbao, Spain
13 Departamento de Física Atómica, Molecular y Nuclear, Facultad de Física, Universidad de Sevilla, 41012 Sevilla, Spain
14 Institut de Ciències de l’Espai (ICE-CSIC), Facultat de Ciències, Campus UAB, 08193 Bellaterra, Spain
15 Departamento de Astronomía, Ponticia Universidad Católica, Santiago, Chile
16 Departament d’Astronomia i Astrofísica, Universitat de València, 46100 Burjassot, Spain
Received: 20 November 2014
Accepted: 20 January 2015
Context. Most observational results on the high redshift restframe UV-bright galaxies are based on samples pinpointed using the so-called dropout technique or Ly-α selection. However, the availability of multifilter data now allows the dropout selections to be replaced by direct methods based on photometric redshifts. In this paper we present the methodology to select and study the population of high redshift galaxies in the ALHAMBRA survey data.
Aims. Our aim is to develop a less biased methodology than the traditional dropout technique to study the high redshift galaxies in ALHAMBRA and other multifilter data. Thanks to the wide area ALHAMBRA covers, we especially aim at contributing to the study of the brightest, least frequent, high redshift galaxies.
Methods. The methodology is based on redshift probability distribution functions (zPDFs). It is shown how a clean galaxy sample can be obtained by selecting the galaxies with high integrated probability of being within a given redshift interval. However, reaching both a complete and clean sample with this method is challenging. Hence, a method to derive statistical properties by summing the zPDFs of all the galaxies in the redshift bin of interest is introduced.
Results. Using this methodology we derive the galaxy rest frame UV number counts in five redshift bins centred at z = 2.5,3.0,3.5,4.0, and 4.5, being complete up to the limiting magnitude at mUV(AB) = 24, where mUV refers to the first ALHAMBRA filter redwards of the Ly-α line. With the wide field ALHAMBRA data we especially contribute to the study of the brightest ends of these counts, accurately sampling the surface densities down to mUV(AB) = 21–22.
Conclusions. We show that using the zPDFs it is easy to select a very clean sample of high redshift galaxies. We also show that it is better to do statistical analysis of the properties of galaxies using a probabilistic approach, which takes into account both the incompleteness and contamination issues in a natural way.
Key words: galaxies: evolution / galaxies: distances and redshifts / galaxies: high-redshift / galaxies: statistics
© ESO, 2015
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.