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| Author(s): |
Raul Ribeiro Prado
Total Authors: 1
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| Document type: | Master's Dissertation |
| Press: | São Carlos. |
| Institution: | Universidade de São Paulo (USP). Instituto de Física de São Carlos (IFSC/BT) |
| Defense date: | 2014-02-14 |
| Examining board members: |
Luiz Vitor de Souza Filho;
Carla Brenda Bonifazi;
Ronald Cintra Shellard
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| Advisor: | Luiz Vitor de Souza Filho |
| Abstract | |
The knowledge about high energy cosmic rays composition is fundamental to approach most of the big questions regarding high energy astrophysics. However, from the experimental point of view, to determine the kind of the measured particle in this energy range is still a huge challenge and this task has received special attention from the collaborations responsible for running the experiments in activity. The main difficulty is on the fact that the measurements are made indirectly by the secondary particles cascades formed by the interaction of primary particles with atmosphere atoms, which are called air showers. Among the main experiments in operation, Pierre Auger Observatory has the larger collecting area (3000 km2) and uses a pioneer hybrid detection system, with surface detectors and fluorescence telescopes working simultaneously. The fluorescence telescopes measure the number of particles in the shower as a function of atmospheric depth, which we call longitudinal profiles. Some parameters extracted from these profiles are sensitive to primary composition. In this study, we applied new statistical methods to the data from longitudinal profiles measured by the Pierre Auger Observatory aiming to infer information about the mean mass, in other words, the composition of cosmic rays. The first analysis shown (chapter 4) is based on the known parameter called XMax. The evolution of XMax mean value with energy contains information about primary composition. Unfolding methods have been applied to the XMax distribution in order to minimize experimental bias and to correct detector effects. The second analysis shown is of the multi-parametric type and applies neural networks of the Multilayer Perceptrons class to longitudinal profiles parameters. From this procedure, it is possible to obtain information about average composition and to reconstruct the energy of events. (AU) | |
| FAPESP's process: | 11/15490-8 - High energy cosmic ray composition |
| Grantee: | Raul Ribeiro Prado |
| Support Opportunities: | Scholarships in Brazil - Master |