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Register a new userReconstruction of air shower muon densities using segmented counters with time resolution
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Despite the significant experimental effort made in the last decades, the origin of the ultra-high energy cosmic rays is still largely unknown. Key astrophysical information to identify where these energetic particles come from is provided by their chemical composition. It is well known that a very sensitive tracer of the primary particle type is the muon content of the showers generated by the interaction of the cosmic rays with air molecules. We introduce a likelihood function to reconstruct particle densities using segmented detectors with time resolution. As an example of this general method, we fit the muon distribution at ground level using an array of counters like AMIGA, one of the Pierre Auger Observatory detectors. For this particular case we compare the reconstruction performance against a previous method. With the new technique, more events can be reconstructed than before. In addition the statistical uncertainty of the measured number of muons is reduced, allowing for a better discrimination of the cosmic ray primary mass.
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Despite the significant experimental effort made in the last decades, the origin of the ultra high energy cosmic rays is still unknown. The chemical composition of these energetic particles carries key astrophysical information to identify where they come from. It is well known that the muon content of the showers generated by the interaction of the cosmic rays with air molecules, is very sensitive to the primary particle type. Therefore, the measurement of the number of muons at ground level is an essential tool to infer the cosmic ray mass composition. We introduce a novel method to reconstruct the lateral distribution of muons with an array of counters buried underground like AMIGA, one of the Pierre Auger Observatory detector systems. The reconstruction builds on a previous method we recently presented by considering the detector time resolution. With the new method more events can be reconstructed than with the previous one. In addition the statistical uncertainty of the measured number of muons is reduced, allowing for a better primary mass discrimination.
Although the origin of ultra high energy cosmic rays is still unknown, significant progress has been achieved in last decades with the construction of large arrays that are currently taking data. One of the most important pieces of information comes from the chemical composition of primary particles. It is well known that the muon content of air showers generated by the interaction of cosmic rays with the atmosphere is rather sensitive to primary mass. Therefore, the measurement of the number of muons at ground level is an essential ingredient to infer the cosmic ray mass composition. In this work we present a new method for reconstructing the muon lateral distribution function with an array of segmented counters. The energy range from .4 to 2.5 EeV is considered. For a triangular array spaced at 750 m we found that 450 m is the optimal distance to evaluate the number of muons. The corresponding statistical and systematic uncertainties of the new and of a previous reconstruction methods are compared. Since the statistical uncertainty of the new reconstruction is less than in the original one, the power to discriminate between heavy and light cosmic ray primaries is enhanced. The detector dynamic range is also extended in the new reconstruction, so events falling closer to a detector can be included in composition studies.
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.
The Auger Engineering Radio Array (AERA) is situated in the Argentinian Pampa Amarilla, a location far away from large human settlements. Nevertheless, a strong background of pulsed radio-frequency interference (RFI) exists on site, which not only makes radio self-triggering challenging but also poses a problem for an efficient and pure reconstruction of air-shower measurements. We present how our standard event reconstruction exploits several strategies to identify and suppress pulsed noise, and quantify the efficiency and purity of our algorithms. These strategies can be employed by any experiment taking radio data in the presence of pulsed RFI.
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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