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3. The VIMOS Integral Field Unit: Data‐Reduction Methods and Quality Assessment

Author

Zanichelli, A., primary, Garilli, B., additional, Scodeggio, M., additional, Franzetti, P., additional, Rizzo, D., additional, Maccagni, D., additional, Merighi, R., additional, Picat, J. P., additional, Le Fèvre, O., additional, Foucaud, S., additional, Bottini, D., additional, Le Brun, V., additional, Scaramella, R., additional, Tresse, L., additional, Vettolani, G., additional, Adami, C., additional, Arnaboldi, M., additional, Arnouts, S., additional, Bardelli, S., additional, Bolzonella, M., additional, Cappi, A., additional, Charlot, S., additional, Ciliegi, P., additional, Contini, T., additional, Gavignaud, I., additional, Guzzo, L., additional, Ilbert, O., additional, Iovino, A., additional, McCracken, H. J., additional, Marano, B., additional, Marinoni, C., additional, Mathez, G., additional, Mazure, A., additional, Meneux, B., additional, Paltani, S., additional, Pellò, R., additional, Pollo, A., additional, Pozzetti, L., additional, Radovich, M., additional, Zamorani, G., additional, and Zucca, E., additional

Published
2005
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4. The VVDS Data‐Reduction Pipeline: Introducing VIPGI, the VIMOS Interactive Pipeline and Graphical Interface

Author

Scodeggio, M., primary, Franzetti, P., additional, Garilli, B., additional, Zanichelli, A., additional, Paltani, S., additional, Maccagni, D., additional, Bottini, D., additional, Le Brun, V., additional, Contini, T., additional, Scaramella, R., additional, Adami, C., additional, Bardelli, S., additional, Zucca, E., additional, Tresse, L., additional, Ilbert, O., additional, Foucaud, S., additional, Iovino, A., additional, Merighi, R., additional, Zamorani, G., additional, Gavignaud, I., additional, Rizzo, D., additional, McCracken, H. J., additional, Le Fèvre, O., additional, Picat, J. P., additional, Vettolani, G., additional, Arnaboldi, M., additional, Arnouts, S., additional, Bolzonella, M., additional, Cappi, A., additional, Charlot, S., additional, Ciliegi, P., additional, Guzzo, L., additional, Marano, B., additional, Marinoni, C., additional, Mathez, G., additional, Mazure, A., additional, Meneux, B., additional, Pellò, R., additional, Pollo, A., additional, Pozzetti, L., additional, and Radovich, M., additional

Published
2005
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5. The Very Large Telescope Visible Multi‐Object Spectrograph Mask Preparation Software

Author

Bottini, D., primary, Garilli, B., additional, Maccagni, D., additional, Tresse, L., additional, Le Brun, V., additional, Le Fèvre, O., additional, Picat, J. P., additional, Scaramella, R., additional, Scodeggio, M., additional, Vettolani, G., additional, Zanichelli, A., additional, Adami, C., additional, Arnaboldi, M., additional, Arnouts, S., additional, Bardelli, S., additional, Bolzonella, M., additional, Cappi, A., additional, Charlot, S., additional, Ciliegi, P., additional, Contini, T., additional, Foucaud, S., additional, Franzetti, P., additional, Guzzo, L., additional, Ilbert, O., additional, Iovino, A., additional, McCracken, H. J., additional, Marano, B., additional, Marinoni, C., additional, Mathez, G., additional, Mazure, A., additional, Meneux, B., additional, Merighi, R., additional, Paltani, S., additional, Pollo, A., additional, Pozzetti, L., additional, Radovich, M., additional, Zamorani, G., additional, and Zucca, E., additional

Published
2005
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7. THE NONLINEAR BIASING OF THE zCOSMOS GALAXIES UP TO z ∼ 1 FROM THE 10k SAMPLEBased on observations obtained at the European Southern Observatory (ESO) Very Large Telescope (VLT), Paranal, Chile, as part of the Large Program 175.A-0839 (the zCOSMOS Spectroscopic Redshift Survey).

Author

Kovač, K., Porciani, C., Lilly, S. J., Marinoni, C., Guzzo, L., Cucciati, O., Zamorani, G., Iovino, A., Oesch, P., Bolzonella, M., Peng, Y., Meneux, B., Zucca, E., Bardelli, S., Carollo, C. M., Contini, T., Kneib, J.-P., Fèvre, O. Le, Mainieri, V., and Renzini, A.

Published
2011
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8. The DEEP2 Galaxy Redshift Survey: Design, Observations, Data Reduction, and Redshifts

Author

Newman, Jeffrey A., Cooper, Michael C., Davis, Marc, Faber, S. M., Coil, Alison L., Guhathakurta, Puragra, Koo, David C., Phillips, Andrew C., Conroy, Charlie, Dutton, Aaron A., Finkbeiner, Douglas, Gerke, Brian F., Rosario, David J., Weiner, Benjamin J., Willmer, C. N. A., Yan, Renbin, Harker, Justin J., Kassin, Susan A., Konidaris, N. P., Lai, Kamson, Madgwick, Darren S., Noeske, K. G., Wirth, Gregory D., Connolly, A. J., Kaiser, N., Kirby, Evan N., Lemaux, Brian C., Lin, Lihwai, Lotz, Jennifer M., Luppino, G. A., Marinoni, C., Matthews, Daniel J., Metevier, Anne, and Schiavon, Ricardo P.

Subjects
cosmology: observations, galaxies: distances and redshifts, galaxies: evolution, galaxies: fundamental parameters, galaxies: high-redshift, galaxies: statistics, large-scale structure of universe, methods: data analysis, surveys
Abstract

We describe the design and data analysis of the DEEP2 Galaxy Redshift Survey, the densest and largest high-precision redshift survey of galaxies at z ~ 1 completed to date. The survey was designed to conduct a comprehensive census of massive galaxies, their properties, environments, and large-scale structure down to absolute magnitude MB = –20 at z ~ 1 via ~90 nights of observation on the Keck telescope. The survey covers an area of 2.8 deg2 divided into four separate fields observed to a limiting apparent magnitude of R AB = 24.1. Objects with z lesssim 0.7 are readily identifiable using BRI photometry and rejected in three of the four DEEP2 fields, allowing galaxies with z > 0.7 to be targeted ~2.5 times more efficiently than in a purely magnitude-limited sample. Approximately 60% of eligible targets are chosen for spectroscopy, yielding nearly 53,000 spectra and more than 38,000 reliable redshift measurements. Most of the targets that fail to yield secure redshifts are blue objects that lie beyond z ~ 1.45, where the [O II] 3727 Å doublet lies in the infrared. The DEIMOS 1200 line mm–1 grating used for the survey delivers high spectral resolution (R ~ 6000), accurate and secure redshifts, and unique internal kinematic information. Extensive ancillary data are available in the DEEP2 fields, particularly in the Extended Groth Strip, which has evolved into one of the richest multiwavelength regions on the sky. This paper is intended as a handbook for users of the DEEP2 Data Release 4, which includes all DEEP2 spectra and redshifts, as well as for the DEEP2 DEIMOS data reduction pipelines. Extensive details are provided on object selection, mask design, biases in target selection and redshift measurements, the spec2d two-dimensional data-reduction pipeline, the spec1d automated redshift pipeline, and the zspec visual redshift verification process, along with examples of instrumental signatures or other artifacts that in some cases remain after data reduction. Redshift errors and catastrophic failure rates are assessed through more than 2000 objects with duplicate observations. Sky subtraction is essentially photon-limited even under bright OH sky lines; we describe the strategies that permitted this, based on high image stability, accurate wavelength solutions, and powerful B-spline modeling methods. We also investigate the impact of targets that appear to be single objects in ground-based targeting imaging but prove to be composite in Hubble Space Telescope data; they constitute several percent of targets at z ~ 1, approaching ~5%-10% at z > 1.5. Summary data are given that demonstrate the superiority of DEEP2 over other deep high-precision redshift surveys at z ~ 1 in terms of redshift accuracy, sample number density, and amount of spectral information. We also provide an overview of the scientific highlights of the DEEP2 survey thus far., Astronomy

Published
2013
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9. The Very Large Telescope Visible Multi‐Object Spectrograph Mask Preparation Software

Author

G. Mathez, G. Vettolani, Magda Arnaboldi, A. Pollo, C. Adami, Alain Mazure, S. Paltani, Roberto Scaramella, D. Maccagni, A. Cappi, B. Garilli, V. Le Brun, O. Ilbert, R. Merighi, T. Contini, E. Zucca, S. Bardelli, M. Bolzonella, Stephane Charlot, H. J. McCracken, A. Iovino, J. P. Picat, L. Tresse, D. Bottini, B. Meneux, Stephane Arnouts, Bruno Marano, Sylvie Foucaud, Lucia Pozzetti, Christian Marinoni, P. Franzetti, O. Le Fevre, Paolo Ciliegi, Mario Radovich, A. Zanichelli, Marco Scodeggio, Luigi Guzzo, G. Zamorani, Laboratoire d'Astrophysique de Marseille (LAM), Aix Marseille Université (AMU)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), INAF - Osservatorio Astronomico di Capodimonte (OAC), Istituto Nazionale di Astrofisica (INAF), Alma Mater Studiorum Università di Bologna [Bologna] (UNIBO), Institut d'Astrophysique de Paris (IAP), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Max-Planck-Institut für Astrophysik (MPA), Max-Planck-Gesellschaft, Services communs OMP (UMS 831), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Aix Marseille Université (AMU)-Centre National d'Études Spatiales [Toulouse] (CNES), Università di Bologna, Dipartimento di Astronomia, Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS), Bottini D., Garilli B., Maccagni D., Tresse L., Le Brun V., Le Fèvre O., Picat J. P., Scaramella R., Scodeggio M., Vettolani G., Zanichelli A., Adami C., Arnaboldi M., Arnouts S., Bardelli S., Bolzonella M., Cappi A., Charlot S., Ciliegi P., Contini T., Foucaud S., Franzetti P., Guzzo L., Ilbert O., Iovino A., McCracken H. J., Marano B., Marinoni C., Mathez G., Mazure A., Meneux B., Merighi R., Paltani S., Pollo A., Pozzetti L., Radovich M., Zamorani G., and Zucca E.

Subjects
Physics, Very Large Telescope, Single exposure, [SDU.ASTR]Sciences of the Universe [physics]/Astrophysics [astro-ph], 010308 nuclear & particles physics, business.industry, Software tool, Instrumentation: Spectrographs, Techniques: Spectroscopic, Astronomy and Astrophysics, Object (computer science), 01 natural sciences, Multiplexing, Software, Optics, Space and Planetary Science, Observatory, Methods: Numerical, 0103 physical sciences, business, 010303 astronomy & astrophysics, Spectrograph, Remote sensing
Abstract

VIMOS (Visible Multi-Object Spectrograph) is a multiobject imaging spectrograph installed at the VLT (Very large Telescope) at the ESO (European Southern Observatory) Paranal Observatory that is especially suited for survey work. VIMOS is characterized by its very high multiplexing factor: it is possible to take up to 800 spectra with 10" long slits in a single exposure. To fully exploit its multiplexing potential, we designed and implemented a dedicated software tool: the VIMOS Mask Preparation Software (VMMPS), which allows the astronomer to select the objects to be spectroscopically observed, and provides for automatic slit positioning and slit number maximization within the instrumental constraints. The output of VMMPS is used to manufacture the slit masks to be mounted in the instrument for spectroscopic observations.

Published
2005
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