Gamma-ray burst observations with new generation imaging atmospheric Cerenkov Telescopes in the FERMI era

After the launch and successful beginning of operations of the FERMI satellite, the topics related to high-energy observations of gamma-ray bursts have obtained a considerable attention by the scientific community. Undoubtedly, the diagnostic power of high-energy observations in constraining the emission processes and the physical conditions of gamma-ray burst is relevant. We briefly discuss how gamma-ray burst observations with ground-based imaging array Cerenkov telescopes, in the GeV-TeV range, can compete and cooperate with FERMI observations, in the MeV-GeV range, to allow researchers to obtain a more detailed and complete picture of the prompt and afterglow phases of gamma-ray bursts.Comment: 9 pages, two figures. Proceeding for the 6th "Science with the New Generation of High Energy Gamma-Ray Experiments" worksho

Blazar Flaring Patterns (B-FlaP): Classifying Blazar Candidates of Uncertain type in the third Fermi-LAT catalog by Artificial Neural Networks

The Fermi Large Area Telescope (LAT) is currently the most important facility for investigating the GeV $\gamma$-ray sky. With Fermi LAT more than three thousand $\gamma$-ray sources have been discovered so far. 1144 ($\sim40\%$) of the sources are active galaxies of the blazar class, and 573 ($\sim20\%$) are listed as Blazar Candidate of Uncertain type (BCU), or sources without a conclusive classification. We use the Empirical Cumulative Distribution Functions (ECDF) and the Artificial Neural Networks (ANN) for a fast method of screening and classification for BCUs based on data collected at $\gamma$-ray energies only, when rigorous multiwavelength analysis is not available. Based on our method, we classify 342 BCUs as BL Lacs and 154 as FSRQs, while 77 objects remain uncertain. Moreover, radio analysis and direct observations in ground-based optical observatories are used as counterparts to the statistical classifications to validate the method. This approach is of interest because of the increasing number of unclassified sources in Fermi catalogs and because blazars and in particular their subclass High Synchrotron Peak (HSP) objects are the main targets of atmospheric Cherenkov telescopes.Comment: 18 pages, 17 figures, accepted for publication on MNRA

Many-core applications to online track reconstruction in HEP experiments

Interest in parallel architectures applied to real time selections is growing in High Energy Physics (HEP) experiments. In this paper we describe performance measurements of Graphic Processing Units (GPUs) and Intel Many Integrated Core architecture (MIC) when applied to a typical HEP online task: the selection of events based on the trajectories of charged particles. We use as benchmark a scaled-up version of the algorithm used at CDF experiment at Tevatron for online track reconstruction - the SVT algorithm - as a realistic test-case for low-latency trigger systems using new computing architectures for LHC experiment. We examine the complexity/performance trade-off in porting existing serial algorithms to many-core devices. Measurements of both data processing and data transfer latency are shown, considering different I/O strategies to/from the parallel devices.Comment: Proceedings for the 20th International Conference on Computing in High Energy and Nuclear Physics (CHEP); missing acks adde