In-situ absolute calibration of electric-field amplitude measurements with the LPDA radio detector stations of the Pierre Auger Observatory

With the Auger Engineering Radio Array (AERA) located at the Pierre Auger Observatory, radio emission of extensive air showers is observed. To exploit the physics potential of AERA, electric-field amplitude measurements with the radio detector stations need to be well-calibrated on an absolute level. A convenient tool for far-field calibration campaigns is a flying drone. Here we make use of an octocopter to place a calibrated source at freely chosen positions above the radio detector array. Special emphasis is put on the reconstruction of the octocopter position and its accuracy during the flights. The antenna response pattern of the radio detector stations was measured in a recent calibration campaign. Results of these measurements are presented and compared to simulations. It is found that measurements and simulations are in good agreement.Comment: To be published in the Proceedings of the ARENA2016 conference, Groningen, The Netherland

Combined fit to the spectrum and composition data measured by the Pierre Auger Observatory including magnetic horizon effects

The measurements by the Pierre Auger Observatory of the energy spectrum and mass composition of cosmic rays can be interpreted assuming the presence of two extragalactic source populations, one dominating the flux at energies above a few EeV and the other below. To fit the data ignoring magnetic field effects, the high-energy population needs to accelerate a mixture of nuclei with very hard spectra, at odds with the approximate E$^{-2}$ shape expected from diffusive shock acceleration. The presence of turbulent extragalactic magnetic fields in the region between the closest sources and the Earth can significantly modify the observed CR spectrum with respect to that emitted by the sources, reducing the flux of low-rigidity particles that reach the Earth. We here take into account this magnetic horizon effect in the combined fit of the spectrum and shower depth distributions, exploring the possibility that a spectrum for the high-energy population sources with a shape closer to E$^{-2}$ be able to explain the observations

The dynamic range of the upgraded surface-detector stations of AugerPrime

The detection of ultra-high-energy cosmic rays by means of giant detector arrays is often limited by the saturation of the recorded signals near the impact point of the shower core at the ground, where the particle density dramatically increases. The saturation affects in particular the highest energy events, worsening the systematic uncertainties in the reconstruction of the shower characteristics. The upgrade of the Pierre Auger Observatory, called AugerPrime, includes the installation of an 1-inch Small PhotoMultiplier Tube (SPMT) inside each water-Cherenkov station (WCD) of the surface detector array. The SPMT allows an unambiguous measurement of signals down to about 250m from the shower core, thus reducing the number of events featuring a saturated station to a negligible level. In addition, a 3.8m2 plastic scintillator (Scintillator Surface Detector, SSD) is installed on top of each WCD. The SSD is designed to match the WCD (with SPMT) dynamic range, providing a complementary measurement of the shower components up to the highest energies. In this work, the design and performances of the upgraded AugerPrime surface-detector stations in the extended dynamic range are described, highlighting the accuracy of the measurements. A first analysis employing the unsaturated signals in the event reconstruction is also presented

Extraction of the Muon Signals Recorded with the Surface Detector of the Pierre Auger Observatory Using Recurrent Neural Networks

We present a method based on the use of Recurrent Neural Networks to extract the muon component from the time traces registered with water-Cherenkov detector (WCD) stations of the Surface Detector of the Pierre Auger Observatory. The design of the WCDs does not allow to separate the contribution of muons to the time traces obtained from the WCDs from those of photons, electrons and positrons for all events. Separating the muon and electromagnetic components is crucial for the determination of the nature of the primary cosmic rays and properties of the hadronic interactions at ultra-high energies. We trained a neural network to extract the muon and the electromagnetic components from the WCD traces using a large set of simulated air showers, with around 450 000 simulated events. For training and evaluating the performance of the neural network, simulated events with energies between 1018.5, eV and 1020 eV and zenith angles below 60 degrees were used. We also study the performance of this method on experimental data of the Pierre Auger Observatory and show that our predicted muon lateral distributions agree with the parameterizations obtained by the AGASA collaboration