Astroinformatics of galaxies and quasars: a new general method for photometric redshifts estimation

With the availability of the huge amounts of data produced by current and future large multi-band photometric surveys, photometric redshifts have become a crucial tool for extragalactic astronomy and cosmology. In this paper we present a novel method, called Weak Gated Experts (WGE), which allows to derive photometric redshifts through a combination of data mining techniques. \noindent The WGE, like many other machine learning techniques, is based on the exploitation of a spectroscopic knowledge base composed by sources for which a spectroscopic value of the redshift is available. This method achieves a variance \sigma^2(\Delta z)=2.3x10^{-4} (\sigma^2(\Delta z) =0.08), where \Delta z = z_{phot} - z_{spec}) for the reconstruction of the photometric redshifts for the optical galaxies from the SDSS and for the optical quasars respectively, while the Root Mean Square (RMS) of the \Delta z variable distributions for the two experiments is respectively equal to 0.021 and 0.35. The WGE provides also a mechanism for the estimation of the accuracy of each photometric redshift. We also present and discuss the catalogs obtained for the optical SDSS galaxies, for the optical candidate quasars extracted from the DR7 SDSS photometric dataset {The sample of SDSS sources on which the accuracy of the reconstruction has been assessed is composed of bright sources, for a subset of which spectroscopic redshifts have been measured.}, and for optical SDSS candidate quasars observed by GALEX in the UV range. The WGE method exploits the new technological paradigm provided by the Virtual Observatory and the emerging field of Astroinformatics.Comment: 36 pages, 22 figures and 8 table

The nature of gas and stars in the circumnuclear regions of AGN: a chemical approach

Aim of this communication is to describe the first results of a work-in-progress regarding the chemical properties of gas and stars in the circumnuclear regions of nearby galaxies. Different techniques have been employed to estimate the abundances of chemical elements in the gaseous and stellar components of nuclear surroundings in different classes of galaxies according to the level of activity of the nucleus (normal or passive, star forming galaxies and AGNs).Comment: 19 pages, proceedings of the 1st International Workshop: Astrophysical winds and disk 2009 (Platamonas

Photometric redshifts for Quasars in multi band Surveys

MLPQNA stands for Multi Layer Perceptron with Quasi Newton Algorithm and it is a machine learning method which can be used to cope with regression and classification problems on complex and massive data sets. In this paper we give the formal description of the method and present the results of its application to the evaluation of photometric redshifts for quasars. The data set used for the experiment was obtained by merging four different surveys (SDSS, GALEX, UKIDSS and WISE), thus covering a wide range of wavelengths from the UV to the mid-infrared. The method is able i) to achieve a very high accuracy; ii) to drastically reduce the number of outliers and catastrophic objects; iii) to discriminate among parameters (or features) on the basis of their significance, so that the number of features used for training and analysis can be optimized in order to reduce both the computational demands and the effects of degeneracy. The best experiment, which makes use of a selected combination of parameters drawn from the four surveys, leads, in terms of DeltaZnorm (i.e. (zspec-zphot)/(1+zspec)), to an average of DeltaZnorm = 0.004, a standard deviation sigma = 0.069 and a Median Absolute Deviation MAD = 0.02 over the whole redshift range (i.e. zspec <= 3.6), defined by the 4-survey cross-matched spectroscopic sample. The fraction of catastrophic outliers, i.e. of objects with photo-z deviating more than 2sigma from the spectroscopic value is < 3%, leading to a sigma = 0.035 after their removal, over the same redshift range. The method is made available to the community through the DAMEWARE web application.Comment: 38 pages, Submitted to ApJ in February 2013; Accepted by ApJ in May 201

Steps toward a classifier for the Virtual Observatory. I. Classifying the SDSS photometric archive

Modern photometric multiband digital surveys produce large amounts of data that, in order to be effectively exploited, need automatic tools capable to extract from photometric data an objective classification. We present here a new method for classifying objects in large multi-parametric photometric data bases, consisting of a combination of a clustering algorithm and a cluster agglomeration tool. The generalization capabilities and the potentialities of this approach are tested against the complexity of the Sloan Digital Sky Survey archive, for which an example of application is reported.Comment: To appear in the Proceedings of the "1st Workshop of Astronomy and Astrophysics for Students" - Naples, 19-20 April 200

Identification of the infrared non-thermal emission in Blazars

Blazars constitute the most interesting and enigmatic class of extragalactic gamma-ray sources dominated by non-thermal emission. In this Letter, we show how the WISE infrared data make possible to identify a distinct region of the [3.4]-[4.6]-[12] micron color-color diagram where the sources dominated by the the thermal radiation are separated from those dominated by non-thermal emission, in particular the blazar population. This infrared non-thermal region delineated as the WISE Blazar Strip (WBS), it is a powerful new diagnostic tool when the full WISE survey data is released. The WBS can be used to extract new blazar candidates, to identify those of uncertain type and also to search for the counterparts of unidentified gamma-ray sources. We show one example of the value of the use of the WBS identifying the TeV source VER J 0648+152, recently discovered by VERITAS.Comment: 5 pages, 4 figures, Astrophysical Journal publishe

Unidentifed gamma-ray sources: hunting gamma-ray blazars

One of the main scientific objectives of the ongoing Fermi mission is unveiling the nature of the unidentified gamma-ray sources (UGSs). Despite the large improvements of Fermi in the localization of gamma-ray sources with respect to the past gamma-ray missions, about one third of the Fermi-detected objects are still not associated to low energy counterparts. Recently, using the Wide-Field Infrared Survey Explorer (WISE) survey, we discovered that blazars, the rarest class of Active Galactic Nuclei and the largest population of gamma-ray sources, can be recognized and separated from other extragalactic sources on the basis of their infrared (IR) colors. Based on this result, we designed an association method for the gamma-ray sources to reognize if there is a blazar candidate within the positional uncertainty region of a generic gamma-ray source. With this new IR diagnostic tool, we searched for gamma-ray blazar candidates associated to the UGS sample of the second Fermi gamma-ray catalog (2FGL). We found that our method associates at least one gamma-ray blazar candidate as a counterpart each of 156 out of 313 UGSs analyzed. These new low-energy candidates have the same IR properties as the blazars associated to gamma-ray sources in the 2FGL catalog.Comment: 24 pages, 4 figures, Accepted for publication on the Astrophysical Journa

The WISE gamma-ray strip parametrization: the nature of the gamma-ray Active Galactic Nuclei of Uncertain type

Despite the large number of discoveries made recently by Fermi, the origins of the so called unidentified gamma-ray sources remain unknown. The large number of these sources suggests that among them there could be a population that significantly contributes to the isotropic gamma-ray background and is therefore crucial to understand their nature. The first step toward a complete comprehension of the unidentified gamma-ray source population is to identify those that can be associated with blazars, the most numerous class of extragalactic sources in the gamma-ray sky. Recently, we discovered that blazars can be recognized and separated from other extragalactic sources using the infrared (IR) WISE satellite colors. The blazar population delineates a remarkable and distinctive region of the IR color-color space, the WISE blazar strip. In particular, the subregion delineated by the gamma-ray emitting blazars is even narrower and we named it as the WISE Gamma-ray Strip (WGS). In this paper we parametrize the WGS on the basis of a single parameter s that we then use to determine if gamma-ray Active Galactic Nuclei of the uncertain type (AGUs) detected by Fermi are consistent with the WGS and so can be considered blazar candidates. We find that 54 AGUs out of a set 60 analyzed have IR colors consistent with the WGS; only 6 AGUs are outliers. This result implies that a very high percentage (i.e., in this sample about 90%) of the AGUs detected by Fermi are indeed blazar candidates.Comment: 22 pages, 13 figures, Astrophysical Journal in pres

Low-mass X-ray binaries and globular clusters streamers and ARCS in NGC 4278

We report significant inhomogeneities in the projected two-dimensional spatial distributions of low-mass X-ray binaries (LMXBs) and globular clusters (GCs) of the intermediate mass elliptical galaxy NGC 4278. In the inner region of NGC 4278, a significant arc-like excess of LMXBs extending south of the center at ∼50″ in the western side of the galaxy can be associated with a similar overdensity of the spatial distribution of red GCs from Brassington et al. Using a recent catalog of GCs produced by Usher et al. and covering the whole field of the NGC 4278 galaxy, we have discovered two other significant density structures outside the D 25 isophote to the W and E of the center of NGC 4278, associated with an overdensity and an underdensity, respectively. We discuss the nature of these structures in the context of the similar spatial inhomogeneities discovered in the LMXBs and GCs populations of NGC 4649 and NGC 4261, respectively. These features suggest streamers from disrupted and accreted dwarf companions.Peer reviewe