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Register a new userA Template-based $gamma$-ray Reconstruction Method for Air Shower Arrays
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We introduce a new Monte Carlo template-based reconstruction method for air shower arrays, with a focus on shower core and energy reconstruction of $gamma$-ray induced air showers. The algorithm fits an observed lateral amplitude distribution of an extensive air shower against an expected probability distribution using a likelihood approach. A full Monte Carlo air shower simulation in combination with the detector simulation is used to generate the expected probability distributions. The goodness of fit can be used to discriminate between $gamma$-ray and hadron induced air showers. As an example, we apply this method to the High Altitude Water Cherenkov $gamma$-ray Observatory and its recently installed high-energy upgrade. The performance of this method and the applicability to air shower arrays with mixed detector types makes it a promising reconstruction approach for current and future instruments.
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We describe a method of reconstructing air showers induced by cosmic rays using deep learning techniques. We simulate an observatory consisting of ground-based particle detectors with fixed locations on a regular grid. The detectors responses to traversing shower particles are signal amplitudes as a function of time, which provide information on transverse and longitudinal shower properties. In order to take advantage of convolutional network techniques specialized in local pattern recognition, we convert all information to the image-like grid of the detectors. In this way, multiple features, such as arrival times of the first particles and optimized characterizations of time traces, are processed by the network. The reconstruction quality of the cosmic ray arrival direction turns out to be competitive with an analytic reconstruction algorithm. The reconstructed shower direction, energy and shower depth show the expected improvement in resolution for higher cosmic ray energy.
We present an improved method for the precise reconstruction of cosmic ray air showers above $10^{17}$ eV with sparse radio arrays. The method is based on the comparison of predictions for radio pulse shapes by CoREAS simulations to measured pulses. We applied our method to the data of Tunka-Rex, a 1 km$^2$ radio array in Siberia operating in the frequency band of 30-80 MHz. Tunka-Rex is triggered by the air-Cherenkov detector Tunka-133 and by scintillators (Tunka-Grande). The instrument collects air-shower data since 2012. The present paper describes updated data and signal analyses of Tunka-Rex and details of a new method applied. After efficiency cuts, when Tunka-Rex reaches its full efficiency, the energy resolution of about 10% given by the new method has reached the limit of systematic uncertainties due to the calibration uncertainty and shower-to-shower fluctuations. At the same time the shower maximum reconstruction is significantly improved up to an accuracy of 35 g/cm$^2$ compared to the previous method based on the slope of the lateral distribution. We also define and now achieved conditions of the measurements, at which the shower maximum resolution of Tunka-Rex reaches a value of 25 g/cm$^2$ and becomes competitive to optical detectors. To check and validate our reconstruction and efficiency cuts we compare individual events to the reconstruction of Tunka-133. Furthermore, we compare the mean of shower maximum as a function of primary energy to the measurements of other experiments.
Accurate prediction of the radio emission from cosmic ray air showers relies on computationally demanding Monte Carlo simulations such as CoREAS. We aim to expedite this process via a semi-analytical synthesis model while maintaining high accuracy by using simulated radio pulses as templates. We present our key concept for template processing focusing on the development of the particle cascade and its empirical effect on the locally produced radio signal. In this context the universality of the radio emission from small sections of an air shower also becomes important where most previous studies focus on integral quantities observable at far distances.
Despite large progresses in building new detectors and in the analysis techniques, the key questions concerning the origin, acceleration and propagation of Galactic Cosmic Rays are still open. A number of new EAS arrays is in progress. The most ambitious and sensitive project between them is LHAASO, a new generation multi-component experiment to be installed at very high altitude in China (Daocheng, Sichuan province, 4400 m a.s.l.). The experiment will face the open problems through a combined study of photon- and charged particle-induced extensive air showers in the wide energy range 10$^{11}$ - 10$^{18}$ eV. In this paper the status of the experiment will be summarized, the science program presented and the outlook discussed in comparison with leading new projects.
The mass composition of cosmic rays contains important clues about their origin. Accurate measurements are needed to resolve long-standing issues such as the transition from Galactic to extragalactic origin, and the nature of the cutoff observed at the highest energies. Composition can be studied by measuring the atmospheric depth of the shower maximum Xmax of air showers generated by high-energy cosmic rays hitting the Earths atmosphere. We present a new method to reconstruct Xmax based on radio measurements. The radio emission mechanism of air showers is a complex process that creates an asymmetric intensity pattern on the ground. The shape of this pattern strongly depends on the longitudinal development of the shower. We reconstruct Xmax by fitting two-dimensional intensity profiles, simulated with CoREAS, to data from the LOFAR radio telescope. In the dense LOFAR core, air showers are detected by hundreds of antennas simultaneously. The simulations fit the data very well, indicating that the radiation mechanism is now well-understood. The typical uncertainty on the reconstruction of Xmax for LOFAR showers is 17 g/cm^2.
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