151. Recent results from the Pierre Auger ObservatorySerguei Vorobiov, 2022, published scientific conference contribution abstract (invited lecture) Abstract: Ultra-high-energy cosmic rays (UHECRs) are mostly protons and heavier nuclei arriving on Earth from space and producing particle cascades in the atmosphere, ”extensive air showers”. As of today, the most precise and high-statistics data set of the rare (≤ 1 particle per sq.km per year above 10[sup]19 eV) UHECR events is obtained by the Pierre Auger Observatory, a large area (~3000 sq.km) hybrid detector in Argentina. The Auger Observatory determines the arrival directions and energies of the primary UHECR particles and provides constraints for their masses.
In this talk, I will present and discuss the recent results, including the detailed measurements of the cosmic-ray energy spectrum features, the study of the anisotropies in the UHECR arrival directions at large and intermediate angular scales, the multi-messenger searches, and the inferred cosmic-ray mass composition. Finally, the progress of the current upgrade of the Observatory, "AugerPrime" which is aimed at improving the sensitivity to the mass composition of ultra-high-energy cosmic rays, will be presented.
Keywords: ultra-high-energy cosmic rays, Pierre Auger Observatory, UHECR mass composition, energy spectrum, anisotropies, AugerPrime upgrade
Published in RUNG: 23.12.2022; Views: 1368; Downloads: 7
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153. Multi-messenger studies with the Pierre Auger ObservatoryLukas Zehrer, Andrej Filipčič, Gašper Kukec Mezek, Jon Paul Lundquist, Samo Stanič, Marta Trini, Serguei Vorobiov, Marko Zavrtanik, Danilo Zavrtanik, 2021, published scientific conference contribution Abstract: Over the past decade the multi-messenger astrophysics has emerged as a distinct discipline,
providing unique insights into the properties of high-energy phenomena in the Universe. The
Pierre Auger Observatory, located in Malargüe, Argentina, is the world’s largest cosmic ray
detector sensitive to photons, neutrinos, and hadrons at ultra-high energies. Using its data, stringent
limits on photon and neutrino fluxes at EeV energies have been obtained. The collaboration uses
the excellent angular resolution and the neutrino identification capabilities of the Observatory
for follow-up studies of events detected in gravitational waves or other messengers, through
cooperation with global multi-messenger networks. We present a science motivation together
with an overview of the multi-messenger capabilities and results of the Pierre Auger Observatory.
Keywords: high-energy cosmic phenomena, multi-messenger astrophysical studies, cosmic rays, gamma-rays, neutrinos, Pierre Auger Observatory
Published in RUNG: 06.05.2022; Views: 1494; Downloads: 0
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154. Identification of point sources in gamma rays using U-shaped convolutional neural networks and a data challengeBoris Panes, Christopher Eckner, Luc Hendriks, Sascha Caron, Klaas Dijkstra, Gudlaugur Johannesson, Roberto Ruiz de Austri, Gabrijela Zaharijas, 2021, original scientific article Keywords: gamma rays, astroparticle physics, data analysis
Published in RUNG: 17.02.2022; Views: 1561; Downloads: 7
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155. Gamma rays from fast black-hole windsM. Ajello, L. Baldini, J. Ballet, G. Barbiellini, D. Bastieri, R. Bellazzini, A. Berretta, E. Bissaldi, R. D. Blandford, E. D. Bloom, Gabrijela Zaharijas, 2021, original scientific article Keywords: active galactic nuclei, galactic winds, gamma-rays
Published in RUNG: 17.02.2022; Views: 1757; Downloads: 111
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157. Experimental and Theoretical Photoemission Study of Indole and Its Derivatives in the Gas PhaseO. Plekan, H. Sa'adeh, A. Ciavardini, C. Callegari, G. Cautero, C. Dri, M. Di Fraia, K.C. Prince, R. Richter, R. Sergo, L. Stebel, M. Devetta, D. Faccialà, C. Vozzi, L. Avaldi, P. Bolognesi, M.C Castrovilli, D. Catone, M. Coreno, F. Zuccaro, E. Bernes, G. Fronzoni, D. Toffoli, 2020, original scientific article Keywords: Binding energy, Calculations, Core levels, Electronic structure, Ionization of gases, Ionization potential, Molecular orbitals, Photoelectron spectroscopy, Photoelectrons, Photoemission, Photoionization, Photons, Polycyclic aromatic hydrocarbons, X rays
Published in RUNG: 21.01.2022; Views: 1867; Downloads: 0
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158. Testing effects of Lorentz invariance violation in the propagation of astroparticles with the Pierre Auger ObservatoryP. Abreu, Andrej Filipčič, Jon Paul Lundquist, Samo Stanič, Serguei Vorobiov, Danilo Zavrtanik, Marko Zavrtanik, Lukas Zehrer, 2022, original scientific article Keywords: cosmic ray experiments, ultra high energy, cosmic rays, physics of the early universe, Pierre Auger Observatory, Lorentz invariance violation effects
Published in RUNG: 18.01.2022; Views: 1648; Downloads: 38
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159. Application of machine learning techniques for cosmic ray event classification and implementation of a real-time ultra-high energy photon search with the surface detector of the Pierre Auger Observatory : dissertationLukas Zehrer, 2021, doctoral dissertation Abstract: Despite their discovery already more than a century ago, Cosmic Rays (CRs) still did not divulge all their properties yet. Theories about the origin of ultra-high energy (UHE, > 10^18 eV) CRs predict accompanying primary photons. The existence of UHE photons can be investigated with the world’s largest ground-based experiment for detection of CR-induced extensive air showers (EAS), the Pierre Auger Observatory, which offers an unprecedented exposure to rare UHE cosmic particles.
The discovery of photons in the UHE regime would open a new observational window to the Universe, improve our understanding of the origin of CRs, and potentially uncloak new physics beyond the standard model.
The novelty of the presented work is the development of a "real-time" photon candidate event stream to a global network of observatories, the Astrophysical Multimessenger Observatory Network (AMON). The stream classifies CR events observed by the Auger surface detector (SD) array as regards their probability to be photon nominees, by feeding to advanced machine learning (ML) methods observational air shower parameters of individual CR events combined in a multivariate analysis (MVA).
The described straightforward classification procedure further increases the Pierre Auger Observatory’s endeavour to contribute to the global effort of multi-messenger (MM) studies of the highest energy astrophysical phenomena, by supplying AMON partner observatories the possibility to follow-up detected UHE events, live or in their archival data.
Keywords: astroparticle physics, ultra-high energy cosmic rays, ultra-high energy photons, extensive air showers, Pierre Auger Observatory, multi-messenger, AMON, machine learning, multivariate analysis, dissertations
Published in RUNG: 27.10.2021; Views: 2841; Downloads: 150
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160. Localisation and classification of gamma ray sources using neural networksChris van den Oetelaar, Saptashwa Bhattacharyya, Boris Panes, Sascha Caron, Gabrijela Zaharijas, Roberto Ruiz de Austri, Guõlaugur Jóhannesson, 2021, published scientific conference contribution Abstract: With limited statistics and spatial resolution of current detectors, accurately localising and separating gamma-ray point sources from the dominating interstellar emission in the GeV energy range is challenging. Motivated by the challenges of the traditional methods used for the gamma-ray source detection, here we demonstrate the application of deep learning based algorithms to automatically detect and classify point sources, which can be applied directly to the binned Fermi-LAT data and potentially be generalised to other wavelengths. For the point source detection task, we use popular deep neural network structure U-NET, together with image segmentation, for precise localisation of sources, various clustering algorithms were tested on the segmented images. The training samples are based on the source properties of AGNs and PSRs from the latest Fermi-LAT source catalog, in addition to the background interstellar emission. Finally, we have created a more
complex but robust training data generation exploiting full detector potential, increasing spatial resolution at the highest energies.
Keywords: gamma-rays, deep learning, computer vision
Published in RUNG: 01.10.2021; Views: 1696; Downloads: 42
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