Search the repository

A+ | A- | | SLO | ENG

Abstract: The Telescope Array (TA) is the largest ultra-high energy cosmic ray (UHECR) observatory in the Northern Hemisphere. Together with the TA Low Energy Extension (TALE), TA×4, and TALE infill detector, the TA measures the properties of UHECR-induced extensive air showers (EAS) in the energy region from 10^15 eV to over 10^20 eV. Each of these uses a hybrid system with an array of scintillators to sample the footprint of the EAS at the Earth’s surface along with telescopes that measure the fluorescence and Cherenkov light from the EAS. The statistics at the highest energies are being enhanced with the TA×4 detector, half completed but still under construction, which will quadruple the surface detector area with telescopes. The TALE infill surface detectors were recently deployed to further lower the hybrid energy threshold of TALE. We present the status of the experiment and recent results on the energy spectrum, mass composition, and anisotropy, including new features in the energy spectrum at about 10^19.2 eV and in the UHECR arrival direction anisotropy.
Keywords: Telescope Array, TALE, low energy extension, TAx4, indirect detection, hybrid detection, ground array, surface detection, fluorescence detection, cerenkov light, ultra-high energy, cosmic rays, energy spectrum, composition, anisotropy
Published in RUNG: 10.10.2023; Views: 619; Downloads: 6
Full text (26,81 MB)
This document has many files! More...

Abstract: The TA×4 experiment aims to better understand the origin and nature of ultra-high energy cosmic rays (UHECRs) by expanding the observation area of the Telescope Array (TA) experiment by a factor of 4. This expansion will increase the statistics of UHECR events with energies greater than 10^19.5 eV. The SD, which means the additionally deployed surface detectors (SD) for the TA×4 experiment, has been collecting data since 2019, and the analysis of this data is currently underway. In this presentation, we will report comparisons between the Monte Carlo simulation and the data obtained by the TA×4 SD array and highlight the agreement between the two. We will also report on the UHECR energy spectrum observed by the TA×4 SD array from October 2019 to September 2022.
Keywords: Telescope Array, TAx4, indirect detection, surface detection, ground array, ultra-high energy, cosmic rays, energy spectrum
Published in RUNG: 09.10.2023; Views: 615; Downloads: 7
Full text (1,51 MB)
This document has many files! More...

Abstract: The TA×4 project is an extension of the Telescope Array (TA) experiment, aimed at clarifying the origin of the highest energy cosmic rays. It has deployed 4 fluorescence detectors (FDs) and 130 surface detectors (SDs) at the northeast lobe of the original TA array and 8 FDs and 127 SDs at the southeast lobe of the original TA array, expanding the detection area about four times larger than the TA experiment. This expansion enables us to sample larger data. The TA×4 has been collecting data to obtain solid evidence of the excess of events in the arrival direction distribution, known as the TA hotspot, reported in 2014 by the TA experiment. The north and south observations began in 2018 and 2019, respectively, and are ongoing except for a hiatus from February to June 2020 due to the COVID-19 pandemic. In this presentation, we will report the details of TA×4 FD monocular analysis.
Keywords: Telescope Array, TAx4, indirect detection, hybrid detection, ground array, fluorescence detection, ultra-high energy, cosmic rays, energy spectrum, composition
Published in RUNG: 09.10.2023; Views: 623; Downloads: 6
Full text (3,20 MB)
This document has many files! More...

Abstract: We report on the cosmic ray mass composition measured by the Telescope Array Low-energy Extension (TALE) hybrid detector. The TALE detector consists of a Fluorescence Detector (FD) station with 10 FD telescopes located at the TA Middle Drum FD Station (itself made up of 14 FD telescopes), and a Surface Detector (SD) array of scintillation counters. The SD array consists of 40 counters with 400 m spacing and 40 counters with 600 m spacing. The FD station, with a total of 24 telescopes, overlooks the SD array and provides sky coverage with an elevation angle range of 3∘ to 59∘. In this contribution, we will present the latest result of the cosmic ray mass composition measurement in the energy range from 10^16.5 eV to 10^18.5 eV using almost 5 years of TALE hybrid data.
Keywords: Telescope Array, TALE, low energy extension, indirect detection, hybrid detection, ground array, infill array, fluorescence detection, cerenkov light, ultra-high energy, cosmic rays, composition
Published in RUNG: 09.10.2023; Views: 601; Downloads: 6
Full text (1,94 MB)
This document has many files! More...

Abstract: We present a method based on the use of Recurrent Neural Networks to extract the muon component from the time traces registered with water-Cherenkov detector (WCD) stations of the Surface Detector of the Pierre Auger Observatory. The design of the WCDs does not allow to separate the contribution of muons to the time traces obtained from the WCDs from those of photons, electrons and positrons for all events. Separating the muon and electromagnetic components is crucial for the determination of the nature of the primary cosmic rays and properties of the hadronic interactions at ultra-high energies. We trained a neural network to extract the muon and the electromagnetic components from the WCD traces using a large set of simulated air showers, with around 450 000 simulated events. For training and evaluating the performance of the neural network, simulated events with energies between 10^18.5 eV and 10^20 eV and zenith angles below 60 degrees were used. We also study the performance of this method on experimental data of the Pierre Auger Observatory and show that our predicted muon lateral distributions agree with the parameterizations obtained by the AGASA collaboration.
Keywords: Pierre Auger Observatory, indirect detection, surface detection, ground array, ultra-high energy, cosmic rays, muons, machine learning, recurrent neural network
Published in RUNG: 04.10.2023; Views: 676; Downloads: 6
Full text (1,08 MB)
This document has many files! More...