4,666 research outputs found

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

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    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

    R. F. testing of the third generation defense communication satellite

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    The approach taken to test a completed DSCS communications satellite on a system level is described. Areas to be described are measuring RF isolation of separate communications subsystems and a test method which insures that one RF subsystem does not interfere with another. In addition, the method of complying with MIL-STD-1541 in the area of demonstrating safety of electroexplosive devices in an RF field is discussed

    Infrared Colors of the gamma-ray detected blazars

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    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 editio

    A charging model for three-axis stabilized spacecraft

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    A charging model was developed for geosynchronous, three-axis stabilized spacecraft when under the influence of a geomagnetic substorm. The differential charging potentials between the thermally coated or blanketed outer surfaces and metallic structure of a spacecraft were determined when the spacecraft was immersed in a dense plasma cloud of energetic particles. The spacecraft-to-environment interaction was determined by representing the charged particle environment by equivalent current source forcing functions and by representing the spacecraft by its electrically equivalent circuit with respect to the plasma charging phenomenon. The charging model included a sun/earth/spacecraft orbit model that simulated the sum illumination conditions of the spacecraft outer surfaces throughout the orbital flight on a diurnal as well as a seasonal basis. Transient and steady-state numerical results for a three-axis stabilized spacecraft are presented

    The Long Term Optical Variability of the BL Lac object S5 0716+714: Evidence for a Precessing Jet

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    We present the historic light curve of the BL Lac object S5 0716+714, spanning the time interval from 1953 to 2003, built using Asiago archive plates and our recent CCD observations, together with literature data. The source shows an evident long term variability, over which well known short term variations are superposed. In particular, in the period from 1961 to 1983 the mean brightness of S5 0716+714 remained significantly fainter than that observed after 1994. Assuming a constant variation rate of the mean magnitude we can estimate a value of about 0.11 magnitude/year. The simultaneous occurrence of decreasing ejection velocities of superluminal moving components in the jet reported by Bach et al. (2005) suggests that both phenomena are related to the change of the direction of the jet to the line of sight from about 5 to 0.7 degrees for an approximately constant bulk Lorentz factor of about 12. A simple explanation is that of a precessing relativistic jet, which should presently be close to the smallest orientation angle. One can therefore expect in the next ten years a decrease of the mean brightness of about 1 magnitude.Comment: to appear on The Astronomical Journal, 17 pages, 7 figures. Fig.2 is given as a separated jpg fil

    Focusing on the extended X-ray emission in 3C 459 with a Chandra follow-up observation

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    6 pages, 4 figures. Reproduced with permission from Astronomy & Astrophysics. © 2019 ESO.Aims. We investigated the X-ray emission properties of the powerful radio galaxy 3C 459 revealed by a recent Chandra follow-up observation carried out in October 2014 with a 62 ks exposure. Methods. We performed an X-ray spectral analysis from a few selected regions on an image obtained from this observation and also compared the X-ray image with a 4.9 GHz VLA radio map available in the literature. Results. The dominant contribution comes from the radio core but significant X-ray emission is detected at larger angular separations from it, surrounding both radio jets and lobes. According to a scenario in which the extended X-ray emission is due to a plasma collisionally heated by jet-driven shocks and not magnetically dominated, we estimated its temperature to be ∼0.8 keV. This hot gas cocoon could be responsible for the radio depolarization observed in 3C 459, as recently proposed also for 3C 171 and 3C 305. On the other hand, our spectral analysis and the presence of an oxygen K edge, blueshifted at 1.23 keV, cannot exclude the possibility that the X-ray radiation originating from the inner regions of the radio galaxy could be intercepted by some outflow of absorbing material intervening along the line of sight, as already found in some BAL quasars.Peer reviewe

    Variable selection via penalized regression and the genetic algorithm using information complexity, with applications for high-dimensional -omics data

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    This dissertation is a collection of examples, algorithms, and techniques for researchers interested in selecting influential variables from statistical regression models. Chapters 1, 2, and 3 provide background information that will be used throughout the remaining chapters, on topics including but not limited to information complexity, model selection, covariance estimation, stepwise variable selection, penalized regression, and especially the genetic algorithm (GA) approach to variable subsetting. In chapter 4, we fully develop the framework for performing GA subset selection in logistic regression models. We present advantages of this approach against stepwise and elastic net regularized regression in selecting variables from a classical set of ICU data. We further compare these results to an entirely new procedure for variable selection developed explicitly for this dissertation, called the post hoc adjustment of measured effects (PHAME). In chapter 5, we reproduce many of the same results from chapter 4 for the first time in a multinomial logistic regression setting. The utility and convenience of the PHAME procedure is demonstrated on a set of cancer genomic data. Chapter 6 marks a departure from supervised learning problems as we shift our focus to unsupervised problems involving mixture distributions of count data from epidemiologic fields. We start off by reintroducing Minimum Hellinger Distance estimation alongside model selection techniques as a worthy alternative to the EM algorithm for generating mixtures of Poisson distributions. We also create for the first time a GA that derives mixtures of negative binomial distributions. The work from chapter 6 is incorporated into chapters 7 and 8, where we conclude the dissertation with a novel analysis of mixtures of count data regression models. We provide algorithms based on single and multi-target genetic algorithms which solve the mixture of penalized count data regression models problem, and demonstrate the usefulness of this technique on HIV count data that were used in a previous study published by Gray, Massaro, et al. (2015) as well as on time-to-event data taken from the cancer genomic data sets from earlier
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