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Your search keyword '"Astrophysics - Cosmology and Nongalactic Astrophysics"' showing total 2 results
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2 results on '"Astrophysics - Cosmology and Nongalactic Astrophysics"'

1. Clustering large number of extragalactic spectra of galaxies and quasars through canopies

Author

Asis Kumar Chattopadhyay, Didier Fraix-Burnet, Tuli De, Department of Mathematics (M.Tech and B.Tech unit), Heritage Institute of Technology, Institut de Planétologie et d'Astrophysique de Grenoble (IPAG), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Department of Statistics, University of Calcutta, Centre National d'Études Spatiales [Toulouse] (CNES)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), and Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Statistics and Probability, Clustering high-dimensional data, FOS: Computer and information sciences, Cosmology and Nongalactic Astrophysics (astro-ph.CO), [SDU.ASTR.CO]Sciences of the Universe [physics]/Astrophysics [astro-ph]/Cosmology and Extra-Galactic Astrophysics [astro-ph.CO], FOS: Physical sciences, 01 natural sciences, Measure (mathematics), Statistics - Applications, Data matrix (multivariate statistics), Clustering, 010104 statistics & probability, 0103 physical sciences, Cluster (physics), Applications (stat.AP), 0101 mathematics, Cluster analysis, 010303 astronomy & astrophysics, Instrumentation and Methods for Astrophysics (astro-ph.IM), Mathematics, [STAT.AP]Statistics [stat]/Applications [stat.AP], Quasar, Spectra, Galaxy, [SDU.ASTR.IM]Sciences of the Universe [physics]/Astrophysics [astro-ph]/Instrumentation and Methods for Astrophysic [astro-ph.IM], Data set, Canopy method, ComputingMethodologies_PATTERNRECOGNITION, Large data, Astrophysics - Instrumentation and Methods for Astrophysics, Algorithm, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

International audience; Cluster analysis is the distribution of objects into different groups or more precisely the partitioning of a data set into subsets (clusters) so that the data in subsets share some common trait according to some distance measure. Unlike classi cation, in clustering one has to rst decide the optimum number of clusters and then assign the objects into different clusters. Solution of such problems for a large number of high dimensional data points is quite complicated and most of the existing algorithms will not perform properly. In the present work a new clustering technique applicable to large data set has been used to cluster the spectra of 702248 galaxies and quasars having 1540 points in wavelength range imposed by the instrument. The proposed technique has successfully discovered ve clusters from this 702248X1540 data matrix.

Published
2016
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2. Cosmological model dependence of the galaxy luminosity function: far-infrared results in the Lemaître-Tolman-Bondi model

Author

L. Riguccini, Benjamin Magnelli, Alvaro Iribarrem, Sean February, Marcelo B. Ribeiro, Paola Popesso, E. Le Floc'h, S. Berta, Raanan Nordon, Carlotta Gruppioni, Paola Andreani, Francesca Pozzi, European Southern Observatory (ESO), Observatório do Valongo/UFRJ [Rio de Janeiro], Universidade Federal do Rio de Janeiro (UFRJ), INAF - Osservatorio Astronomico di Bologna (OABO), Istituto Nazionale di Astrofisica (INAF), Département d'Astrophysique (ex SAP) (DAP), Institut de Recherches sur les lois Fondamentales de l'Univers (IRFU), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, A. Iribarrem, P. Andreani, C. Gruppioni, S. February, M. B. Ribeiro, S. Berta, E. Le Floc’h, B. Magnelli, R. Nordon, P. Popesso, F. Pozzi, L. Riguccini, Department of Astronomy, and Faculty of Science

Subjects
Cosmology and Nongalactic Astrophysics (astro-ph.CO), Cosmic microwave background, FOS: Physical sciences, Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, 01 natural sciences, Cosmology, infrared: galaxies, General Relativity and Quantum Cosmology, cosmology: theory, 0103 physical sciences, Galaxy formation and evolution, 010303 astronomy & astrophysics, Astrophysics::Galaxy Astrophysics, Luminous infrared galaxy, Physics, 010308 nuclear & particles physics, infrared: galaxie, Estimator, Astronomy and Astrophysics, Redshift, Galaxy, galaxies: distances and redshift, Supernova, galaxies: luminosity function, Space and Planetary Science, mass function, galaxies: luminosity function, mass function, galaxies: distances and redshifts, galaxies: evolution, [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph], Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

This is the first paper of a series aiming at investigating galaxy formation and evolution in the giant-void class of the Lemaitre-Tolman-Bondi (LTB) models that best fits current cosmological observations. Here we investigate the Luminosity Function (LF) methodology, and how its estimates would be affected by a change on the cosmological model assumed in its computation. Are the current observational constraints on the allowed Cosmology enough to yield robust LF results? We use the far-infrared source catalogues built on the observations performed with the Herschel/PACS instrument, and selected as part of the PACS evolutionary probe (PEP) survey. Schechter profiles are obtained in redshift bins up to z approximately 4, assuming comoving volumes in both the standard model, that is, Friedmann-Lemaitre-Robertson-Walker metric with a perfect fluid energy-momentum tensor, and non-homogeneous LTB dust models, parametrized to fit the current combination of results stemming from the observations of supernovae Ia, the cosmic microwave background, and baryonic acoustic oscillations. We find that the luminosity functions computed assuming both the standard model and LTB void models show in general good agreement. However, the faint-end slope in the void models shows a significant departure from the standard model up to redshift 0.4. We demonstrate that this result is not artificially caused by the used LF estimator which turns out to be robust under the differences in matter-energy density profiles of the models. The differences found in the LF slopes at the faint end are due to variation in the luminosities of the sources, which depend on the geometrical part of the model. It follows that either the standard model is over-estimating the number density of faint sources or the void models are under-estimating it., 23 pages, 11 figures. Accepted for publication in A&A

Published
2013
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