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Belver, D., Blanco, A., Cabanelas, P., Diaz, J., Fonte, P., Garzon, J. A., et al. (2012). Analysis of the space-time microstructure of cosmic ray air showers using the HADES RPC TOF wall. J. Instrum., 7, P10007–9pp.
Abstract: Cosmic rays have been studied, since they were discovered one century ago, with a very broad spectrum of detectors and techniques. However, never the properties of the extended air showers (EAS) induced by high energy primary cosmic rays had been analysed at the Earth surface with a high granularity detector and a time resolution at the 0.1 ns scale. The commissioning of the timing RPC (Resistive Plate Chambers) time of flight wall of the HADES spectrometer with cosmic rays, at the GSI (Darmstadt, Germany), opened up that opportunity. During the last months of 2009, more than 500 millions of cosmic ray events were recorded by a stack of two RPC modules, of about 1.25 m(2) each, able to measure swarms of up to similar to 100 particles with a time resolution better than 100 ps. In this document it is demonstrated how such a relative small two-plane, high-granularity timing RPC setup may provide significant information about the properties of the shower and hence about the primary cosmic ray properties.
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Pierre Auger Collaboration(Abreu, P. et al), & Pastor, S. (2013). Techniques for measuring aerosol attenuation using the Central Laser Facility at the Pierre Auger Observatory. J. Instrum., 8, P04009–28pp.
Abstract: The Pierre Auger Observatory in Malargue, Argentina, is designed to study the properties of ultra-high energy cosmic rays with energies above 10(18) eV. It is a hybrid facility that employs a Fluorescence Detector to perform nearly calorimetric measurements of Extensive Air Shower energies. To obtain reliable calorimetric information from the FD, the atmospheric conditions at the observatory need to be continuously monitored during data acquisition. In particular, light attenuation due to aerosols is an important atmospheric correction. The aerosol concentration is highly variable, so that the aerosol attenuation needs to be evaluated hourly. We use light from the Central Laser Facility, located near the center of the observatory site, having an optical signature comparable to that of the highest energy showers detected by the FD. This paper presents two procedures developed to retrieve the aerosol attenuation of fluorescence light from CLF laser shots. Cross checks between the two methods demonstrate that results from both analyses are compatible, and that the uncertainties are well understood. The measurements of the aerosol attenuation provided by the two procedures are currently used at the Pierre Auger Observatory to reconstruct air shower data.
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ATLAS Collaboration(Aad, G. et al), Alvarez Piqueras, D., Barranco Navarro, L., Cabrera Urban, S., Castillo Gimenez, V., Cerda Alberich, L., et al. (2016). Beam-induced and cosmic-ray backgrounds observed in the ATLAS detector during the LHC 2012 proton-proton running period. J. Instrum., 11, P05013–78pp.
Abstract: This paper discusses various observations on beam-induced and cosmic-ray backgrounds in the ATLAS detector during the LHC 2012 proton-proton run. Building on published results based on 2011 data, the correlations between background and residual pressure of the beam vacuum are revisited. Ghost charge evolution over 2012 and its role for backgrounds are evaluated. New methods to monitor ghost charge with beam-gas rates are presented and observations of LHC abort gap population by ghost charge are discussed in detail. Fake jets from colliding bunches and from ghost charge are analysed with improved methods, showing that ghost charge in individual radio-frequency buckets of the LHC can be resolved. Some results of two short periods of dedicated cosmic-ray background data-taking are shown; in particular cosmic-ray muon induced fake jet rates are compared to Monte Carlo simulations and to the fake jet rates from beam background. A thorough analysis of a particular LHC fill, where abnormally high background was observed, is presented. Correlations between backgrounds and beam intensity losses in special fills with very high beta* are studied.
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Rasco, B. C., Brewer, N. T., Yokoyama, R., Grzywacz, R., Rykaczewski, K. P., Tolosa-Delgado, A., et al. (2018). The ORNL analysis technique for extracting beta-delayed multi-neutron branching ratios with BRIKEN. Nucl. Instrum. Methods Phys. Res. A, 911, 79–86.
Abstract: Many choices are available in order to evaluate large radioactive decay networks. There are many parameters that influence the calculated beta-decay delayed single and multi-neutron emission branching fractions. We describe assumptions about the decay model, background, and other parameters and their influence on beta-decay delayed multi-neutron emission analysis. An analysis technique, the ORNL BRIKEN analysis procedure, for determining beta-delayed multi-neutron branching ratios in beta-neutron precursors produced by means of heavy-ion fragmentation is presented. The technique is based on estimating the initial activities of zero, one, and two neutrons occurring in coincidence with an ion-implant and beta trigger. The technique allows one to extract beta-delayed multi-neutron decay branching ratios measured with the He-3 BRIKEN neutron counter. As an example, two analyses of the beta-neutron emitter Cu-77 based on different a priori assumptions are presented along with comparisons to literature values.
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Panes, B., Eckner, C., Hendriks, L., Caron, S., Dijkstra, K., Johannesson, G., et al. (2021). Identification of point sources in gamma rays using U-shaped convolutional neural networks and a data challenge. Astron. Astrophys., 656, A62–18pp.
Abstract: Context. At GeV energies, the sky is dominated by the interstellar emission from the Galaxy. With limited statistics and spatial resolution, accurately separating point sources is therefore challenging. Aims. Here we present the first application of deep learning based algorithms to automatically detect and classify point sources from gamma-ray data. For concreteness we refer to this approach as AutoSourceID. Methods. To detect point sources, we utilized U-shaped convolutional networks for image segmentation and k-means for source clustering and localization. We also explored the Centroid-Net algorithm, which is designed to find and count objects. Using two algorithms allows for a cross check of the results, while a combination of their results can be used to improve performance. The training data are based on 9.5 years of exposure from The Fermi Large Area Telescope (Fermi-LAT) and we used source properties of active galactic nuclei (AGNs) and pulsars (PSRs) from the fourth Fermi-LAT source catalog in addition to several models of background interstellar emission. The results of the localization algorithm are fed into a classification neural network that is trained to separate the three general source classes (AGNs, PSRs, and FAKE sources). Results. We compared our localization algorithms qualitatively with traditional methods and find them to have similar detection thresholds. We also demonstrate the robustness of our source localization algorithms to modifications in the interstellar emission models, which presents a clear advantage over traditional methods. The classification network is able to discriminate between the three classes with typical accuracy of similar to 70%, as long as balanced data sets are used in classification training. We published online our training data sets and analysis scripts and invite the community to join the data challenge aimed to improve the localization and classification of gamma-ray point sources.
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