X-ray view of four high-luminosity Swift/BAT AGN: Unveiling obscuration and reflection with Suzaku

The Swift/BAT nine-month survey observed 153 AGN, all with ultra-hard X-ray BAT fluxes in excess of 10^-11 erg cm^-2 s^-1 and an average redshift of 0.03. Among them, four of the most luminous BAT AGN (44.73 < Log L(BAT) < 45.31) were selected as targets of Suzaku follow-up observations: J2246.0+3941 (3C 452), J0407.4+0339 (3C 105), J0318.7+6828, and J0918.5+0425. The column density, scattered/reflected emission, the properties of the Fe K line, and a possible variability are fully analyzed. For the latter, the spectral properties from Chandra, XMM-Newton and Swift/XRT public observations were compared with the present Suzaku analysis. Of our sample, 3C 452 is the only certain Compton-thick AGN candidate because of i) the high absorption and strong Compton reflection; ii) the lack of variability; iii) the "buried" nature, i.e. the low scattering fraction (<0.5%) and the extremely low relative [OIII] luminosity. In contrast 3C 105 is not reflection-dominated, despite the comparable column density, X-ray luminosity and radio morphology, but shows a strong long-term variability in flux and scattering fraction, consistent with the soft emission being scattered from a distant region (e.g., the narrow emission line region). The sample presents high (>100) X-to-[OIII] luminosity ratios, confirming the [OIII] luminosity to be affected by residual extinction in presence of mild absorption, especially for "buried" AGN such as 3C 452. Three of our targets are powerful FRII radio galaxies, making them the most luminous and absorbed AGN of the BAT Seyfert survey despite the inversely proportional N_H - L_X relation.Comment: A&A paper in press, 17 page

Natural clustering: the modularity approach

We show that modularity, a quantity introduced in the study of networked systems, can be generalized and used in the clustering problem as an indicator for the quality of the solution. The introduction of this measure arises very naturally in the case of clustering algorithms that are rooted in Statistical Mechanics and use the analogy with a physical system.Comment: 11 pages, 5 figure enlarged versio

Redundant variables and Granger causality

We discuss the use of multivariate Granger causality in presence of redundant variables: the application of the standard analysis, in this case, leads to under-estimation of causalities. Using the un-normalized version of the causality index, we quantitatively develop the notions of redundancy and synergy in the frame of causality and propose two approaches to group redundant variables: (i) for a given target, the remaining variables are grouped so as to maximize the total causality and (ii) the whole set of variables is partitioned to maximize the sum of the causalities between subsets. We show the application to a real neurological experiment, aiming to a deeper understanding of the physiological basis of abnormal neuronal oscillations in the migraine brain. The outcome by our approach reveals the change in the informational pattern due to repetitive transcranial magnetic stimulations.Comment: 4 pages, 5 figures. Accepted for publication in Physical Review

Cost functions for pairwise data clustering

Cost functions for non-hierarchical pairwise clustering are introduced, in the probabilistic autoencoder framework, by the request of maximal average similarity between the input and the output of the autoencoder. The partition provided by these cost functions identifies clusters with dense connected regions in data space; differences and similarities with respect to a well known cost function for pairwise clustering are outlined.Comment: 5 pages, 4 figure

A visual analytics approach for the assessment of information quality of performance models—a software review

In this paper we provide a review of the main functionalities of a Visual Analytics Environment (VAE) developed for the assessment of data and information quality in the context of performance evaluation of research organizations. Performing data and information quality tests are necessary procedures to ensure the bibliometric and research performance evaluation analysis of organizations have the necessary robustness. The proposed environment is helpful to guide the user to an Information Quality-aware development of Performance models. This interactive visual analytics environment offers to the user the possibility to produce and compare information quality-aware indicators, exploring and defining correct behavior, identifying anomalous cases from both data quality and information quality perspectives, and supporting the user in forming hypotheses on possible causes for those anomalies. The proposed approach, exploiting visual interactive exploration results in a more efficient process, minimizing the number of cases for which a manual investigation is needed. The illustration on European higher education institutions data demonstrates the use of the presented functionalities and their benefits

Deterministic Annealing as a jet clustering algorithm in hadronic collisions

We show that a general purpose clusterization algorithm, Deterministic Annealing, can be adapted to the problem of jet identification in particle production by high energy collisions. In particular we consider the problem of jet searching in events generated at hadronic colliders. Deterministic Annealing is able to reproduce the results obtained by traditional jet algorithms and to exhibit a higher degree of flexibility.Comment: 13 pages, 6 figure