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Register a new userTracing protons through the Galactic magnetic field: a clue for charge composition of ultra-high energy cosmic rays
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We reconstruct the trajectories of ultra-high energy cosmic rays (UHECR) - observed by the AGASA experiment - in the Galactic magnetic field assuming that all particles have the same charge. We then study correlations between the reconstructed events and BL Lacs. The correlations have significance below 10^{-3} in the case of particles with charge +1. In the case of charge -1 the correlations are absent. We interpret this as evidence that protons are present in the flux of UHECR. Observed correlation provides an independent evidence that BL Lacs emit UHECR.
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Deflection of ultra high energy cosmic rays (UHECRs) by the Galactic magnetic field (GMF) may be sufficiently strong to hinder identification of the UHECR source distribution. A common method for determining the effect of GMF models on source identification efforts is backtracking cosmic rays. We present the public numerical tool CRT for propagating charged particles through Galactic magnetic field models by numerically integrating the relativistic equation of motion. It is capable of both forward- and back-tracking particles with varying compositions through pre-defined and custom user-created magnetic fields. These particles are injected from various types of sources specified and distributed according to the user. Here, we present a description of some source and magnetic field model implementations, as well as validation of the integration routines.
The propagation trajectories of ultra-high-energy cosmic rays (UHECRs) are inevitably affected by Galactic magnetic field (GMF). Because of the inevitability, the importance of the studies of the propagation in GMF have increased to interpret the results of recent UHECR experiments. This article reviews the effects of GMF to the propagation and arrival directions of UHECRs and introduces recent studies to constrain UHECR sources.
We present a method to correct for deflections of ultra-high energy cosmic rays in the galactic magnetic field. We perform these corrections by simulating the expected arrival directions of protons using a parameterization of the field derived from Faraday rotation and synchrotron emission measurements. To evaluate the method we introduce a simulated astrophysical scenario and two observables designed for testing cosmic ray deflections. We show that protons can be identified by taking advantage of the galactic magnetic field pattern. Consequently, cosmic ray deflection in the galactic field can be verified experimentally. The method also enables searches for directional correlations of cosmic rays with source candidates.
A new family of parameters intended for composition studies in cosmic ray surface array detectors is proposed. The application of this technique to different array layout designs has been analyzed. The parameters make exclusive use of surface data combining the information from the total signal at each triggered detector and the array geometry. They are sensitive to the combined effects of the different muon and electromagnetic components on the lateral distribution function of proton and iron initiated showers at any given primary energy. Analytical and numerical studies have been performed in order to assess the reliability, stability and optimization of these parameters. Experimental uncertainties, the underestimation of the muon component in the shower simulation codes, intrinsic fluctuations and reconstruction errors are considered and discussed in a quantitative way. The potential discrimination power of these parameters, under realistic experimental conditions, is compared on a simplified, albeit quantitative way, with that expected from other surface and fluorescence estimators.
We analyze here the possibility of studying mass composition in the Auger data sample using neural networks as a diagnostic tool. Extensive air showers were simulated using the AIRES code, for the two hadronic interaction models in current use: QGSJet and Sibyll. Both, photon and hadron primaries were simulated and used to generate events. The output parameters from the ground array were simulated for the typical instrumental and environmental conditions at the Malargue Auger site using the code SAMPLE. Besides photons, hydrogen, helium, carbon, oxygen, magnesium, silicon, calcium and iron nuclei were also simulated. We show that Principal Components Analysis alone is enough to separate individual photon from hadron events, but the same technique cannot be applied to the classification of hadronic events. The latter requires the use of a more robust diagnostic. We show that neural networks are potentially powerful enough to discriminate proton from iron events almost on an event-by-event basis. However, in the case of a more realistic multi-component mixture of primary nuclei, only a statistical estimate of the average mass can be reliably obtained. Although hybrid events are not explicitly simulated, we show that, whenever hybrid information in the form of $X_{max}$ is introduced in the training procedure of the neural networks, a considerable improvement can be achieved in mass discrimination analysis.
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