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Register a new userA Method for Constraining Cosmic Magnetic Field Models Using Ultra-High Energy Cosmic Rays: The Field Scan Method
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The Galactic magnetic field, locally observed to be on the order of a few $mu$G, is sufficiently strong to induce deflections in the arrival directions of ultra-high energy cosmic rays. We present a method that establishes measures of self-consistency for hypothesis sets comprised of cosmic magnetic field models and ultra-high energy cosmic ray composition and source distributions. The method uses two independent procedures to compare the backtracked velocity vectors outside the magnetic field model to the distribution of backtracked velocity directions of many isotropic observations with the same primary energies. This allows for an estimate of the statistical consistency between the observed data and simulated isotropic observations. Inconsistency with the isotropic expectation of source correlation in both procedures is interpreted as the hypothesis set providing a self-consistent description of GMF and UHECR properties for the cosmic ray observations.
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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.
We propose a novel approach for observing cosmic rays at ultra-high energy ($>10^{18}$~eV) by repurposing the existing network of smartphones as a ground detector array. Extensive air showers generated by cosmic rays produce muons and high-energy photons, which can be detected by the CMOS sensors of smartphone cameras. The small size and low efficiency of each sensor is compensated by the large number of active phones. We show that if user adoption targets are met, such a network will have significant observing power at the highest energies.
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.
We estimate the effective area available for cosmic-ray detection with a network of smartphones under optimistic conditions. To measure cosmic-ray air showers with a minimally-adequate precision and a detection area similar to existing ground-based detectors, the fraction of participating users needs to unrealistically large. We conclude that the prospects of cosmic-ray research using smartphones are very limited.
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