Mining Knowledge in Astrophysical Massive Data Sets

Modern scientific data mainly consist of huge datasets gathered by a very large number of techniques and stored in very diversified and often incompatible data repositories. More in general, in the e-science environment, it is considered as a critical and urgent requirement to integrate services across distributed, heterogeneous, dynamic "virtual organizations" formed by different resources within a single enterprise. In the last decade, Astronomy has become an immensely data rich field due to the evolution of detectors (plates to digital to mosaics), telescopes and space instruments. The Virtual Observatory approach consists into the federation under common standards of all astronomical archives available worldwide, as well as data analysis, data mining and data exploration applications. The main drive behind such effort being that once the infrastructure will be completed, it will allow a new type of multi-wavelength, multi-epoch science which can only be barely imagined. Data Mining, or Knowledge Discovery in Databases, while being the main methodology to extract the scientific information contained in such MDS (Massive Data Sets), poses crucial problems since it has to orchestrate complex problems posed by transparent access to different computing environments, scalability of algorithms, reusability of resources, etc. In the present paper we summarize the present status of the MDS in the Virtual Observatory and what is currently done and planned to bring advanced Data Mining methodologies in the case of the DAME (DAta Mining & Exploration) project.Comment: Pages 845-849 1rs International Conference on Frontiers in Diagnostics Technologie

DAME: A distributed data mining and exploration framework within the virtual observatory

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 platformindependent tool perfectly compliant with modern KDD (Knowledge Discovery in Databases) requirements and Information & Communication Technology trends

Nuclear activity and star formation properties of Seyfert 2 galaxies

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 Astrophysic

Radio weak BL Lac objects in the Fermi era

The existence of “radio weak BL Lac objects” (RWBLs) has been an open question, still unsolved, since the discovery that quasars could be radio-quiet or radio-loud. Recently several groups identified RWBL candidates, mostly found while searching for low energy counterparts of the unidentified/ unassociated gamma-ray sources listed in the Fermi catalogs. Confirming RWBLs is a challenging task since they could be confused with white dwarfs or weak emission line quasars when there are not sufficient data to precisely draw their broad band spectral energy distribution and their classification is mainly based on a featureless optical spectra. Motivated by the recent discovery that Fermi BL Lacs appear to have very peculiar mid-IR emission, we show that it is possible to distinguish between WDs, WELQs and BL Lacs using the [3.4]-[4.6]-[12]μm color-color plot built using the WISE magnitudes when the optical spectrum is available. On the basis of this analysis, we identify WISE J064459.38+603131 and WISE J141046.00+740511.2 as the first two genuine RWBLs, both potentially associated with Fermi sources. Finally, to strengthen our identification of these objects as true RWBLs, we present multifrequency observations for these two candidates to show that their spectral behavior is indeed consistent with those of the BL Lac population.Facultad de Ciencias Astronómicas y Geofísica

The Fornax Deep Survey with VST. II. Fornax A: a two-phase assembly caught on act

As part of the Fornax Deep Survey with the ESO VLT Survey Telescope, we present new $g$ and $r$ bands mosaics of the SW group of the Fornax cluster. It covers an area of $3 \times 2$ square degrees around the central galaxy NGC1316. The deep photometry, the high spatial resolution of OmegaCam and the large covered area allow us to study the galaxy structure, to trace stellar halo formation and look at the galaxy environment. We map the surface brightness profile out to 33arcmin ($\sim 200$kpc $\sim15R_e$) from the galaxy centre, down to $\mu_g \sim 31$ mag arcsec$^{-2}$ and $\mu_r \sim 29$ mag arcsec$^{-2}$. This allow us to estimate the scales of the main components dominating the light distribution, which are the central spheroid, inside 5.5 arcmin ($\sim33$ kpc), and the outer stellar envelope. Data analysis suggests that we are catching in act the second phase of the mass assembly in this galaxy, since the accretion of smaller satellites is going on in both components. The outer envelope of NGC1316 still hosts the remnants of the accreted satellite galaxies that are forming the stellar halo. We discuss the possible formation scenarios for NGC1316, by comparing the observed properties (morphology, colors, gas content, kinematics and dynamics) with predictions from cosmological simulations of galaxy formation. We find that {\it i)} the central spheroid could result from at least one merging event, it could be a pre-existing early-type disk galaxy with a lower mass companion, and {\it ii)} the stellar envelope comes from the gradual accretion of small satellites.Comment: Accepeted for publication in Ap

Mining the SDSS archive. I. Photometric redshifts in the nearby universe

We present a supervised neural network approach to the determination of photometric redshifts. The method was tuned to match the characteristics of the Sloan Digital Sky Survey and it exploits the spectroscopic redshifts provided by this unique survey. In order to train, validate and test the networks we used two galaxy samples drawn from the SDSS spectroscopic dataset: the general galaxy sample (GG) and the luminous red galaxies subsample (LRG). The method consists of a two steps approach. In the first step, objects are classified in nearby (z<0.25) and distant (0.25<z<0.50). In the second step two different networks are separately trained on objects belonging to the two redshift ranges. Using a standard MLP operated in a Bayesian framework, the optimal architectures were found to require 1 hidden layer of 24 (24) and 24 (25) neurons for the GG (LRG) sample. The presence of systematic deviations was then corrected by interpolating the resulting redshifts. The final results on the GG dataset give a robust sigma_z = 0.0208 over the redshift range [0.01, 0.48] and sigma_z = 0.0197 and sigma_z = 0.0238 for the nearby and distant samples respectively. For the LRG subsample we find a robust sigma_z = 0.0164 over the whole range, and sigma_z = 0.0160, sigma_z = 0.0183 for the nearby and distant samples respectively. After training, the networks have been applied to all objects in the SDSS Table GALAXY matching the same selection criteria adopted to build the base of knowledge, and photometric redshifts for ca. 30 million galaxies having z<0.5 were derived. A catalogue containing photometric redshifts for the LRG subsample was also produced.Comment: 45 pages, 14 figures, accepted for publication is the Astrophysical Journa

A universal ultraviolet-optical colour-colour-magnitude relation of galaxies

Although the optical colour-magnitude diagram of galaxies allows one to select red sequence objects, neither can it be used for galaxy classification without additional observational data such as spectra or high-resolution images, nor to identify blue galaxies at unknown redshifts. We show that adding the near ultraviolet colour to the optical CMD reveals a tight relation in the three-dimensional colour-colour-magnitude space smoothly continuing from the "blue cloud" to the "red sequence". We found that 98 per cent of 225,000 low-redshift (Z<0.27) galaxies follow a smooth surface g-r=F(M,NUV-r) with a standard deviation of 0.03-0.07 mag making it the tightest known galaxy photometric relation. There is a strong correlation between morphological types and integrated NUV-r colours. Rare galaxy classes such as E+A or tidally stripped systems become outliers that occupy distinct regions in the 3D parameter space. Using stellar population models for galaxies with different SFHs, we show that (a) the (NUV-r, g-r) distribution is formed by objects having constant and exponentially declining SFR with different characteristic timescales; (b) colour evolution for exponentially declining models goes along the relation suggesting its weak evolution up-to a redshift of 0.9; (c) galaxies with truncated SFHs have very short transition phase offset from the relation thus explaining the rareness of E+A galaxies. This relation can be used as a powerful galaxy classification tool when morphology remains unresolved. Its mathematical consequence is the photometric redshift estimates from 3 broad-band photometric points. This approach works better than most existing photometric redshift techniques applied to multi-colour datasets. Therefore, the relation can be used as an efficient selection technique for galaxies at intermediate redshifts (0.3<Z<0.8) using optical imaging surveys.Comment: 15 pages, 10 figures, accepted to MNRAS. This is an updated version that addresses referee's remarks. All relations have been recomputed using Petrosian magnitudes. The best-fitting relations in the electronic form are available at the project web-page: http://specphot.sai.msu.ru/galaxies

Astroinformatics based search for globular clusters in the Fornax Deep Survey

In the last years, Astroinformatics has become a well-defined paradigm for many fields of Astronomy. In this work, we demonstrate the potential of a multidisciplinary approach to identify globular clusters (GCs) in the Fornax cluster of galaxies taking advantage of multiband photometry produced by the VLT Survey Telescope using automatic self-adaptive methodologies. The data analysed in this work consist of deep, multiband, partially overlapping images centred on the core of the Fornax cluster. In this work, we use a Neural Gas model, a pure clustering machine learning methodology, to approach the GC detection, while a novel feature selection method (ΦLAB) is exploited to perform the parameter space analysis and optimization. We demonstrate that the use of an Astroinformatics-based methodology is able to provide GC samples that are comparable, in terms of purity and completeness with those obtained using single-band HST data and two approaches based, respectively, on a morpho-photometric and a Principal Component Analysis using the same data discussed in this work

Radio weak BL Lac objects in the Fermi era

The existence of “radio weak BL Lac objects” (RWBLs) has been an open question, still unsolved, since the discovery that quasars could be radio-quiet or radio-loud. Recently several groups identified RWBL candidates, mostly found while searching for low energy counterparts of the unidentified/ unassociated gamma-ray sources listed in the Fermi catalogs. Confirming RWBLs is a challenging task since they could be confused with white dwarfs or weak emission line quasars when there are not sufficient data to precisely draw their broad band spectral energy distribution and their classification is mainly based on a featureless optical spectra. Motivated by the recent discovery that Fermi BL Lacs appear to have very peculiar mid-IR emission, we show that it is possible to distinguish between WDs, WELQs and BL Lacs using the [3.4]-[4.6]-[12]μm color-color plot built using the WISE magnitudes when the optical spectrum is available. On the basis of this analysis, we identify WISE J064459.38+603131 and WISE J141046.00+740511.2 as the first two genuine RWBLs, both potentially associated with Fermi sources. Finally, to strengthen our identification of these objects as true RWBLs, we present multifrequency observations for these two candidates to show that their spectral behavior is indeed consistent with those of the BL Lac population.Facultad de Ciencias Astronómicas y Geofísica