5 resultados para Prague
em Universidad de Alicante
Resumo:
Póster presentado en 19th International Congress of Chemical and Process Engineering, Prague, Czech Republic August 28th-September 1st, 2010.
Resumo:
Póster presentado en 19th International Congress of Chemical and Process Engineering, Prague, Czech Republic August 28th-September 1st, 2010.
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Paper submitted to MML 2013, 6th International Workshop on Machine Learning and Music, Prague, September 23, 2013.
Resumo:
The discovery almost three decades ago of non-nuclear, point-like X-ray sources with X-ray luminosities LX ≥ 3 × 1039 erg s−1 revolutionized the physics of black hole accretion. If of stellar origin, such Ultraluminous X-ray sources (ULXs) would have to accrete at super-Eddington rates in order to reach the observed high X-ray luminosities. Alternatively, ULXs could host sub-Eddington accreting intermediate-mass black holes, which are the long-time sought missing link between stellar and supermassive black holes and the possible seeds of the supermassive black holes that formed in the early Universe. The nature of ULXs can be better investigated in those cases for which a radio counterpart is detected. Radio observations of ULXs have revealed a wide variety of morphologies and source types, from compact and extended jets to radio nebulae and transient behaviours, providing the best observational evidence for the presence of an intermediate-mass black hole in some of them. The high sensitivity of the SKA will allow us to study the faintest ULX radio counterparts in the Local Universe as well as to detect new sources at much larger distances. It will thus perform a leap step in understanding ULXs, their accretion physics, and their possible role as seed black holes in supermassive black hole and galaxy growth.
Resumo:
In a previous work, we introduced a tool for analyzing multiple datasets simultaneously, which has been implemented into ISIS. This tool was used to fit many spectra of X-ray binaries. However, the large number of degrees of freedom and individual datasets raise an issue about a good measure for a simultaneous fit quality. We present three ways to check the goodness of these fits: we investigate the goodness of each fit in all datasets, we define a combined goodness exploiting the logical structure of a simultaneous fit, and we stack the fit residuals of all datasets to detect weak features. These tools are applied to all RXTE-spectra from GRO 1008−57, revealing calibration features that are not detected significantly in any single spectrum. Stacking the residuals from the best-fit model for the Vela X-1 and XTE J1859+083 data evidences fluorescent emission lines that would have gone undetected otherwise.