Suchergebnisse

The cores of clusters at 0 ? z ? 1 are dominated by quiescent early-type galaxies, whereas the field is dominated by star-forming late-type galaxies. Clusters grow through the accretion of galaxies and groups from the surrounding field, which implies that galaxy properties, notably the star formation ability, are altered as they fall into overdense regions. The critical issues for understanding this evolution are how the truncation of star formation is connected to the morphological transformation and what physical mechanism is responsible for these changes. The GaLAxy Cluster Evolution Survey (GLACE) is conducting a thorough study of the variations in galaxy properties (star formation, AGN activity, and morphology) as a function of environment in a representative and well-studied sample of clusters. To address these questions, the GLACE survey is making a deep panoramic survey of emission line galaxies (ELG), mapping a set of optical lines ([O?ii], [O?iii], Hß andHa/[N?ii] when possible) in several galaxy clusters at z ~ 0.40, 0.63, and 0.86. Using the tunable filters (TF) of the OSIRIS instrument at the 10.4 m GTC telescope, the GLACE survey applies the technique of TF tomography: for each line, a set of images are taken through the OSIRIS TF, each image tuned at a different wavelength (equally spaced), to cover a rest frame velocity range of several thousand km?s-1 centred on the mean cluster redshift, and scanned for the full TF field of view of an 8?arcmin diameter. Here we present the first results of the GLACE project, targeting the Ha/[N?ii] lines in the intermediate-redshift cluster ZwCl?0024.0+1652 at z = 0.395. Two pointings have been performed that cover ~2?×?rvir. We discuss the specific techniques devised to process the TF tomography observations in order to generate the catalogue of cluster Ha emitters, which contains more than 200 sources down to a star formation rate (SFR)??1?M?/yr. An ancillary broadband catalogue is constructed, allowing us to discriminate line interlopers by means of colour diagnostics. The final catalogue contains 174 unique cluster sources. The AGN population is distinguished using different diagnostics and found to be ~37% of the ELG population. The median SFR of the star-forming population is 1.4?M?/yr. We studied the spatial distribution of ELG and confirm the existence of two components in the redshift space. Finally, we exploited the outstanding spectral resolution of the TF, attempting to estimate the cluster mass from ELG dynamics, finding M200?=?(4.1?±?0.2)?×?1014?M? h-1, in agreement with previous weak-lensing estimates. ; Acknowledgements. We acknowledge the support provided by M. Balogh during the preparation of the GLACE proposal to ESO, as well as his useful suggestions for improving the quality of this paper. We also acknowledge the anonymous referee. We acknowledge financial support from Spanish MINECO under grant AYA2014-29517-C03-01, AYA2011-29517-C03-02 and AYA2014-58861-C03. E.J.A. acknowledges support from MINECO under grant AYA2013-40611-P. J.M.R.E. acknowledges support from MINECO under grant AYA2012-39168-C03-01. We acknowledge support from the Faculty of the European Space Astronomy Centre (ESAC). I.R.S. acknowledges support from STFCGT/I001573/1, a European Research Council Advanced Programme Dustygal (321334) and a Royal Society/Wolfson Research Merit Award. J.S.S. acknowledges funding from the European Union Seventh Framework Programme (FP7/2007−2013) under grant agreement No. 267251 "Astronomy Fellowshipsin Italy" (AstroFIt). Based on observations made with the Gran Telescopio Canarias (GTC), installed at the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofsica de Canarias, on the island of La Palma. This publication makes use of data products from the Two Micron All Sky Survey, which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center/California Institute of Technology, by the National Aeronautics and Space Administration and the National Science Foundation

Sánchez-Portal, Miguel et. al. ; The cores of clusters at 0 ≲ z ≲ 1 are dominated by quiescent early-type galaxies, whereas the field is dominated by star-forming late-type galaxies. Clusters grow through the accretion of galaxies and groups from the surrounding field, which implies that galaxy properties, notably the star formation ability, are altered as they fall into overdense regions. The critical issues for understanding this evolution are how the truncation of star formation is connected to the morphological transformation and what physical mechanism is responsible for these changes. The GaLAxy Cluster Evolution Survey (GLACE) is conducting a thorough study of the variations in galaxy properties (star formation, AGN activity, and morphology) as a function of environment in a representative and well-studied sample of clusters. To address these questions, the GLACE survey is making a deep panoramic survey of emission line galaxies (ELG), mapping a set of optical lines ([O ii], [O iii], Hβ andHα/[N ii] when possible) in several galaxy clusters at z ~ 0.40, 0.63, and 0.86. Using the tunable filters (TF) of the OSIRIS instrument at the 10.4 m GTC telescope, the GLACE survey applies the technique of TF tomography: for each line, a set of images are taken through the OSIRIS TF, each image tuned at a different wavelength (equally spaced), to cover a rest frame velocity range of several thousand km s-1 centred on the mean cluster redshift, and scanned for the full TF field of view of an 8 arcmin diameter. Here we present the first results of the GLACE project, targeting the Hα/[N ii] lines in the intermediate-redshift cluster ZwCl 0024.0+1652 at z = 0.395. Two pointings have been performed that cover ~2 × rvir. We discuss the specific techniques devised to process the TF tomography observations in order to generate the catalogue of cluster Hα emitters, which contains more than 200 sources down to a star formation rate (SFR) ≲1 M⊙/yr. An ancillary broadband catalogue is constructed, allowing us to discriminate line interlopers by means of colour diagnostics. The final catalogue contains 174 unique cluster sources. The AGN population is distinguished using different diagnostics and found to be ~37% of the ELG population. The median SFR of the star-forming population is 1.4 M⊙/yr. We studied the spatial distribution of ELG and confirm the existence of two components in the redshift space. Finally, we exploited the outstanding spectral resolution of the TF, attempting to estimate the cluster mass from ELG dynamics, finding M200 = (4.1 ± 0.2) × 1014 M⊙ h-1, in agreement with previous weak-lensing estimates. ; We acknowledge financial support from Spanish MINECO under grant AYA2014-29517-C03-01, AYA2011-29517-C03-02 and AYA2014-58861-C03. E.J.A. acknowledges support from MINECO under grant AYA2013-40611-P. J.M.R.E. acknowledges support from MINECO under grant AYA2012-39168-C03-01. We acknowledge support from the Faculty of the European Space Astronomy Centre (ESAC). I.R.S. acknowledges support from STFC GT/I001573/1, a European Research Council Advanced Programme Dustygal (321334) and a Royal Society/Wolfson Research Merit Award. J.S.S. acknowledges funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement No. 267251 "Astronomy Fellowships in Italy" (AstroFIt). ; Peer Reviewed

Context. The accurate classification of hundreds of thousands of galaxies observed in modern deep surveys is imperative if we want to understand the universe and its evolution. Aims. Here, we report the use of machine learning techniques to classify early- and late-type galaxies in the OTELO and COSMOS databases using optical and infrared photometry and available shape parameters: either the Sérsic index or the concentration index. Methods. We used three classification methods for the OTELO database: (1) u? -? r color separation, (2) linear discriminant analysis using u? -? r and a shape parameter classification, and (3) a deep neural network using the r magnitude, several colors, and a shape parameter. We analyzed the performance of each method by sample bootstrapping and tested the performance of our neural network architecture using COSMOS data. Results. The accuracy achieved by the deep neural network is greater than that of the other classification methods, and it can also operate with missing data. Our neural network architecture is able to classify both OTELO and COSMOS datasets regardless of small differences in the photometric bands used in each catalog. Conclusions. In this study we show that the use of deep neural networks is a robust method to mine the cataloged data. © ESO 2020. ; This work was supported by the project Evolution of Galaxies, of reference AYA2014-58861-C3-1-P and AYA2017-88007-C3-1-P, within the "Programa estatal de fomento de la investigacion cientifica y tecnica de excelencia del Plan Estatal de Investigacion Cientifica y Tecnica y de Innovacion (2013-2016)" of the "Agencia Estatal de Investigacion del Ministerio de Ciencia, Innovacion y Universidades", and co-financed by the FEDER "Fondo Europeo de Desarrollo Regional". JAD is grateful for the support from the UNAM-DGAPA-PASPA 2019 program, the UNAM-CIC, the Canary Islands CIE: Tricontinental Atlantic Campus 2017, and the kind hospitality of the IAC. MP acknowledges financial supports from the Ethiopian Space Science and Technology Institute (ESSTI) under the Ethiopian Ministry of Innovation and Technology (MoIT), and from the Spanish Ministry of Economy and Competitiveness (MINECO) through projects AYA2013-42227-P and AYA2016-76682C3-1-P. APG, MSP and RPM were supported by the PNAYA project: AYA2017-88007-C3-2-P. MC and APG are also funded by Spanish State Research Agency grant MDM-2017-0737 (Unidad de Excelencia Maria de Maeztu CAB). EJA acknowledges support from the Spanish Government Ministerio de Ciencia, Innovacion y Universidades though grant PGC2018-095049-B-C21. M.P. and E.J.A. also acknowledge support from the State Agency for Research of the Spanish MCIU through the Center of Excellence Severo Ochoa award for the Instituto de Astrofisica de Andalucia (SEV-2017-0709). JG receives support through the project AyA2018-RTI-096188-B-100. MALL acknowledges support from the Carlsberg Foundation via a Semper Ardens grant (CF15-0384). JIGS receives support through the Proyecto Puente 52.JU25.64661 (2018) funded by Sodercan S.A. and the Universidad de Cantabria, and PGC2018-099705-B-100 funded by the Ministerio de Ciencia, Innovacion y Universidades. Based on observations made with the Gran Telescopio Canarias (GTC), installed in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofisica de Canarias, in the island of La Palma. This work is (partly) based on data obtained with the instrument OSIRIS, built by a Consortium led by the Instituto de Astrofisica de Canarias in collaboration with the Instituto de Astronomia of the Universidad Autonoma de Mexico. OSIRIS was funded by GRANTECAN and the National Plan of Astronomy and Astrophysics of the Spanish Government.