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The existence of correlations between nuclear properties of galaxies, such as the mass of their central black holes, and larger scale features, like the bulge mass and luminosity, represent a fundamental constraint on galaxy evolution. Although the actual reasons for these relations have not yet been identified, it is widely believed that they could stem from a connection between the processes that lead to black hole growth and stellar mass assembly. The problem of understanding how the processes of nuclear activity and star formation can affect each other became known to the literature as the Starburst-AGN connection. Despite years of investigation, the physical mechanisms which lie at the basis of this relation are known only in part. In this work, we analyze the problem of star formation and nuclear activity in a large sample of galaxies. We study the relations between the properties of the nuclear environments and of their host galaxies. We find that the mass of the stellar component within the galaxies of our sample is a critical parameter, that we have to consider in an evolutionary sequence, which provides further insight in the connection between AGN and star formation processes., Comment: 13 pages, 10 figures, accepted for publication on MNRAS. Reference to the mass derivation procedure corrected

In this paper we present the Clustering-Labels-Score Patterns Spotter (CLaSPS), a new methodology for the determination of correlations among astronomical observables in complex datasets, based on the application of distinct unsupervised clustering techniques. The novelty in CLaSPS is the criterion used for the selection of the optimal clusterings, based on a quantitative measure of the degree of correlation between the cluster memberships and the distribution of a set of observables, the labels, not employed for the clustering. In this paper we discuss the applications of CLaSPS to two simple astronomical datasets, both composed of extragalactic sources with photometric observations at different wavelengths from large area surveys. The first dataset, CSC+, is composed of optical quasars spectroscopically selected in the SDSS data, observed in the X-rays by Chandra and with multi-wavelength observations in the near-infrared, optical and ultraviolet spectral intervals. One of the results of the application of CLaSPS to the CSC+ is the re-identification of a well-known correlation between the alphaOX parameter and the near ultraviolet color, in a subset of CSC+ sources with relatively small values of the near-ultraviolet colors. The other dataset consists of a sample of blazars for which photometric observations in the optical, mid and near infrared are available, complemented for a subset of the sources, by Fermi gamma-ray data. The main results of the application of CLaSPS to such datasets have been the discovery of a strong correlation between the multi-wavelength color distribution of blazars and their optical spectral classification in BL Lacs and Flat Spectrum Radio Quasars and a peculiar pattern followed by blazars in the WISE mid-infrared colors space. This pattern and its physical interpretation have been discussed in details in other papers by one of the authors., Comment: 18 pages, 9 figures, accepted for publication in ApJ

The identification of low-energy counterparts for gamma-ray sources is one of the biggest challenge in modern gamma-ray astronomy. Recently, we developed and successfully applied a new association method to recognize gamma-ray blazar candidates that could be possible counterparts for the unidentified gamma-ray sources above 100 MeV in the second Fermi Large Area Telescope (LAT) catalog (2FGL). This method is based on the Infrared (IR) colors of the recent Wide-Field Infrared Survey Explorer (WISE) all-sky survey. In this letter we applied our new association method to the case of unidentified INTEGRAL sources (UISs) listed in the fourth soft gamma-ray source catalog (4IC). Only 86 UISs out of the 113 can be analyzed, due to the sky coverage of the WISE Preliminary data release. Among these 86 UISs, we found that 18 appear to have a gamma-ray blazar candidate within their positional error region. Finally, we analyzed the SWIFT archival data available for 10 out these 18 gamma-ray blazar candidates, and we found that 7 out of 10 are clearly detected in soft X-rays and/or in the optical-ultraviolet band. We cannot confirm the associations between the UISs and the selected gamma-ray blazar candidates due to the discrepancies between the INTEGRAL and the soft X-ray spectra. However, the discovery of the soft X-ray counterparts for the selected gamma-ray blazar candidates adds an important clue to help understand their origin and to confirm their blazar nature., Comment: 13 pages, 4 figures, 1 table, accepted for publication on the Astrophysical Journal Letters

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 Journal

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 press

Blazars constitute the most enigmatic class of extragalactic gamma-ray sources, and their observational features have been ascribed to a relativistic jet closely aligned to the line of sight. They are generally divided in two main classes: the BL Lac objects (BL Lacs) and the Flat Spectrum Radio Quasars (FSRQs). In the case of BL Lacs the double bumped spectral energy distribution (SED) is generally described by the Synchrotron Self Compton (SSC) emission, while for the FSRQs it is interpreted as due to External Compton (EC) emission. Recently, we showed that in the [3.4]-[4.6]-[12] micron color- color diagram the blazar population covers a distinct region (i.e., the WISE blazar Strip, WBS), clearly separated from the other extragalactic sources that are dominated by thermal emission. In this paper we investigate the relation between the infrared and gamma-ray emission for a subset of confirmed blazars from the literature, associated with Fermi sources, for which WISE archival observations are available. This sample is a proper subset of the sample of sources used previously, and the availability of Fermi data is critical to constrain the models on the emission mechanisms for the blazars. We found that the selected blazars also lie on the WISE blazar Strip covering a narrower region of the infrared color-color planes than the overall blazars population. We then found an evident correlation between the IR and gamma-ray spectral indices expected in the SSC and EC frameworks. Finally, we determined the ratio between their gamma-ray and infrared fluxes, a surrogate of the ratio of powers between the inverse Compton and the synchrotron SED components, and used such parameter to test different emitting scenarios blazars., Comment: 15 pages, 14 figure, accepted for publication in ApJ, to appear in 2012 March 20 edition

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 published

Nowadays, many scientific areas share the same broad requirements of being able to deal with massive and distributed datasets while, when possible, being integrated with services and applications. In order to solve the growing gap between the incremental generation of data and our understanding of it, it is required to know how to access, retrieve, analyze, mine and integrate data from disparate sources. One of the fundamental aspects of any new generation of data mining software tool or package which really wants to become a service for the community is the possibility to use it within complex workflows which each user can fine tune in order to match the specific demands of his scientific goal. These workflows need often to access different resources (data, providers, computing facilities and packages) and require a strict interoperability on (at least) the client side. The project DAME (DAta Mining & Exploration) arises from these requirements by providing a distributed WEB-based data mining infrastructure specialized on Massive Data Sets exploration with Soft Computing methods. Originally designed to deal with astrophysical use cases, where first scientific application examples have demonstrated its effectiveness, the DAME Suite results as a multi-disciplinary platform-independent tool perfectly compliant with modern KDD (Knowledge Discovery in Databases) requirements and Information & Communication Technology trends., Comment: 20 pages, INGRID 2010 - 5th International Workshop on Distributed Cooperative Laboratories: "Instrumenting" the Grid, May 12-14, 2010, Poznan, Poland; Volume Remote Instrumentation for eScience and Related Aspects, 2011, F. Davoli et al. (eds.), SPRINGER NY

Astronomical data are gathered through a very large number of heterogeneous techniques and stored in very diversified and often incompatible data repositories. Moreover in the e-science environment, it is needed to integrate services across distributed, heterogeneous, dynamic "virtual organizations" formed by different resources within a single enterprise and/or external resource sharing and service provider relationships. The DAME/VONeural project, run jointly by the University Federico II, INAF (National Institute of Astrophysics) Astronomical Observatories of Napoli and the California Institute of Technology, aims at creating a single, sustainable, distributed e-infrastructure for data mining and exploration in massive data sets, to be offered to the astronomical (but not only) community as a web application. The framework makes use of distributed computing environments (e.g. S.Co.P.E.) and matches the international IVOA standards and requirements. The integration process is technically challenging due to the need of achieving a specific quality of service when running on top of different native platforms. In these terms, the result of the DAME/VO-Neural project effort will be a service-oriented architecture, obtained by using appropriate standards and incorporating Grid paradigms and restful Web services frameworks where needed, that will have as main target the integration of interdisciplinary distributed systems within and across organizational domains., Comment: 10 pages, Proceedings of the Final Workshop of the Grid Projects of the Italian National Operational Programme 2000-2006 Call 1575; Edited by Cometa Consortium, 2009, ISBN: 978-88-95892-02-3

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)

In order to characterize the amount of recent or ongoing stellar formation in the circumnuclear region of active galaxies on a statistically sound basis, we have studied the stellar component of the nuclear spectra in three different samples of galaxies, namely Seyfert 2 galaxies (hereafter S2G), star-forming galaxies (SFG) and passive normal galaxies (NG), i.e., no emission lines observed, using Sloan Digital Sky Survey data (SDSS) (Adelman-McCarthy, 2008). The stellar component of the observed spectra has been extracted using STARLIGHT (Cid Fernandes et al., 2004), which fits an observed spectrum with a model (template) spectrum obtained by combining a library of pre-defined simple stellar populations spectra, with distinct ages and metallicities. The resulting template spectra for the different samples of galaxies have been compared to determine the features of the stellar emission component and to evaluate the presence and intensity of the star formation in the nuclear regions of different families of galaxies. From a first qualitative analysis it results that the shape of the Spectral Energy Distribution (SED) of S2G and NG is very similar, while that of SFG is characterized by a strong blue excess. The presence of the 4000 A break in the spectra of S2G and NG together with the lack of a strong blue continuum clearly indicate the absence of ongoing star formation in the circumnuclear regions of S2G and obviously of NG. Anyway traces of a recent star formation history are evident in the spectra of S2G galaxies, which show a 4000 A break systematically shallower than in NG., Comment: Proceeding of the VII Serbian Conference on Spectral Line Shapes in Astrophysics

We present a systematic study of the sub-sample of Shakhbazyan groups (SHKs) covered by the Sloan Digital Sky Survey Data Release--5 (SDSS-5). SHKs probe an environment with characteristics which are intermediate between those of loose and very compact groups. Surprisingly, we found that several groups identifying algorithms (e.g. Berlind et al. 2006, Tago et al. 2008) miss this type of structures. Using the SDSS-5 spectroscopic data and the photometric redshifts derived in D'Abrusco et al. 2007, we identified possible group members in photometric redshift space and derived, for each group, several individual properties. We also combined pointed and stacked Rosat All Sky Survey data to investigate the X-ray luminosities of these systems. Our study confirms that the majority of groups are physical entities with richness in the range 3--13 galaxies, and properties ranging between those of loose and compact groups. We confirm that SHK groups are richer in early-type galaxies than the surrounding environment and the field, as expected from the morphology-density relation and from the selection of groups of red galaxies. Furthermore, our work supports the existence of two sub-classes of structures, the first one being formed by compact and isolated groups and the second formed by extended structures. We suggest that while the first class of objects dwells in less dense regions like the outer parts of clusters or the field, possibly sharing the properties of Hickson Compact Groups, the more extended structures represent a mixture of [core+halo] configurations and cores of rich clusters. X-ray luminosities for SHKs are generally consistent with these results and with the expectations for the L_X-sigma_v relation, but also suggest the velocity dispersions reported in literature are underestimated for some of the richest systems., Comment: 20 pages, 14 figures, 4 tables. Accepted for publication by MNRAS

S.Co.P.E. is one of the four projects funded by the Italian Government in order to provide Southern Italy with a distributed computing infrastructure for fundamental science. Beside being aimed at building the infrastructure, S.Co.P.E. is also actively pursuing research in several areas among which astrophysics and observational cosmology. We shortly summarize the most significant results obtained in the first two years of the project and related to the development of middleware and Data Mining tools for the Virtual Observatory.

VO-Neural is the natural evolution of the Astroneural project which was started in 1994 with the aim to implement a suite of neural tools for data mining in astronomical massive data sets. At a difference with its ancestor, which was implemented under Matlab, VO-Neural is written in C++, object oriented, and it is specifically tailored to work in distributed computing architectures. We discuss the current status of implementation of VO-Neural, present an application to the classification of Active Galactic Nuclei, and outline the ongoing work to improve the functionalities of the package., Comment: Contributed, Data Centre Alliance Workshops: GRID and the Virtual Observatory, April 9-11 Munich, to appear in Mem. SAIt

We present a method for the photometric selection of candidate quasars in multiband surveys. The method makes use of a priori knowledge derived from a subsample of spectroscopic confirmed QSOs to map the parameter space. The disentanglement of QSOs candidates and stars is performed in the colour space through the combined use of two algorithms, the Probabilistic Principal Surfaces and the Negative Entropy clustering, which are for the first time used in an astronomical context. Both methods have been implemented in the VONeural package on the Astrogrid VO platform. Even though they belong to the class of the unsupervised clustering tools, the performances of the method are optimized by using the available sample of confirmed quasars and it is therefore possible to learn from any improvement in the available "base of knowledge". The method has been applied and tested on both optical and optical plus near infrared data extracted from the visible SDSS and infrared UKIDSS-LAS public databases. In all cases, the experiments lead to high values of both efficiency and completeness, comparable if not better than the methods already known in the literature. A catalogue of optical candidate QSOs extracted from the SDSS DR7 Legacy photometric dataset has been produced and is publicly available at the URL voneural.na.infn.it/qso.html., Comment: 75 pages, 43 figure, 7 tables, accepted for publication in MNRAS

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 2006

We present a new analysis of the Sloan Digital Sky Survey data aimed at producing a detailed map of the nearby (z < 0.5) universe. Using neural networks trained on the available spectroscopic base of knowledge we derived distance estimates for about 30 million galaxies distributed over ca. 8,000 sq. deg. We also used unsupervised clustering tools developed in the framework of the VO-Tech project, to investigate the possibility to understand the nature of each object present in the field and, in particular, to produce a list of candidate AGNs and QSOs., Comment: 3 pages, 1 figure. To appear in Nucl Phys. B, in the proceedings of the NOW-2006 (Neutrino Oscillation Workshop - 2006), R. Fogli et al. eds

In the framework of the European VO-Tech project, we are implementing new machine learning methods specifically tailored to match the needs of astronomical data mining. In this paper, we shortly present the methods and discuss an application to the Sloan Digital Sky Survey public data set. In particular, we discuss some preliminary results on the 3-D taxonomy of the nearby (z < 0.5) universe. Using neural networks trained on the available spectroscopic base of knowledge we derived distance estimates for ca. 30 million galaxies distributed over 8,000 sq. deg. We also use unsupervised clustering tools to investigate whether it is possible to characterize in broad morphological bins the nature of each object and produce a reliable list of candidate AGNs and QSOs., Comment: 7 pages, 5 figures. To appear in the proceedings of the Astronomical Data Analysis -IV workshop held in Marseille in 2006. J.L. Starck et al. eds

Current experiments collecting high statistics in ultra-high energy cosmic rays (UHECRs) are opening a new window on the universe. In this work we discuss a large scale structure model for the UHECR origin which evaluates the expected anisotropy in the UHECR arrival distribution starting from a given astronomical catalogue of the local universe. The model takes into account the main selection effects in the catalogue and the UHECR propagation effects. By applying this method to the IRAS PSCz catalogue, we derive the minimum statistics needed to significatively reject the hypothesis that UHECRs trace the baryonic distribution in the universe, in particular providing a forecast for the Auger experiment., Comment: 21 pages, 14 figures. Reference added, minor changes, matches published version