دانلود رایگان مقاله بازسازی تراکم موآن بارش هوا با استفاده از شمارنده سگمنت

Abstract

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.

6. Conclusions

We introduced two different methods to reconstruct the lateral distribution function of air shower muons: the profile and the integrated likelihoods. Both likelihoods extend a previous approach by considering the detector timing. Although we applied the likelihoods to a specific cosmic ray detector, they can be used for any kind of segmented particle counters with time resolution. We found an optimal distance of 450 m to measure the shower size parameter in a triangular array with 750 m between detectors. The new likelihoods improve the reconstruction in two aspects. Firstly, by raising the number of muons a detector can handle before saturating, more events can be reconstructed. The recovery is more significant close to 10 EeV, the upper limit of the considered energy range, a region where events are usually scarce. Secondly, we reduced the statistical fluctuations of the parameter that measures the shower size from 1 EeV upwards. This decrease allows for a more powerful discrimination between different primary masses based on the number of muons. By comparing to an ideal muon counter, we established that the resolutions achieved with the new likelihoods are close to the lower bound given the detector size and spacing. We also showed that the approximations introduced for the profile and integrated likelihoods do not bias the reconstructed shower size parameter and kept the coverage of its 1σ confidence interval close to the expected Gaussian nominal value. The shower size parameters reconstructed with the integrated and the profile likelihoods are very similar. Nevertheless the profile likelihood is the preferred reconstruction method given the much shorter time it takes to process the data. The correspondence between the profile and the integrated likelihood results, shows the robustness of these techniques to reconstruct the muon lateral distribution with an array of segmented counters.