Energy estimation of cosmic rays with the Engineering Radio Array of the Pierre Auger Observatory

A. Aab et al. (Pierre Auger Collaboration)

Phys. Rev. D 93, 122005 – Published 14 June 2016

Abstract

The Auger Engineering Radio Array (AERA) is part of the Pierre Auger Observatory and is used to detect the radio emission of cosmic-ray air showers. These observations are compared to the data of the surface detector stations of the Observatory, which provide well-calibrated information on the cosmic-ray energies and arrival directions. The response of the radio stations in the 30–80 MHz regime has been thoroughly calibrated to enable the reconstruction of the incoming electric field. For the latter, the energy deposit per area is determined from the radio pulses at each observer position and is interpolated using a two-dimensional function that takes into account signal asymmetries due to interference between the geomagnetic and charge-excess emission components. The spatial integral over the signal distribution gives a direct measurement of the energy transferred from the primary cosmic ray into radio emission in the AERA frequency range. We measure 15.8 MeV of radiation energy for a 1 EeV air shower arriving perpendicularly to the geomagnetic field. This radiation energy—corrected for geometrical effects—is used as a cosmic-ray energy estimator. Performing an absolute energy calibration against the surface-detector information, we observe that this radio-energy estimator scales quadratically with the cosmic-ray energy as expected for coherent emission. We find an energy resolution of the radio reconstruction of 22% for the data set and 17% for a high-quality subset containing only events with at least five radio stations with signal.

Received 27 August 2015

DOI:https://doi.org/10.1103/PhysRevD.93.122005

Physics Subject Headings (PhySH)

Cosmic ray composition & spectra Cosmic ray sources Extrasolar neutrino astronomy

Gravitation, Cosmology & Astrophysics

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Measurement of the Radiation Energy in the Radio Signal of Extensive Air Showers as a Universal Estimator of Cosmic-Ray Energy

A. Aab et al. (Pierre Auger Collaboration)

Phys. Rev. Lett. 116, 241101 (2016)

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Vol. 93, Iss. 12 — 15 June 2016

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Images

Figure 1
Reconstructed electric-field trace of one of the measured cosmic-ray radio events. An upsampling by a factor of 5 was applied. The shown Hilbert envelope (dashed line) is the square root of the quadratic sum of the Hilbert envelopes of the three polarization components.
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Figure 2
Polarization map of a single event. The axis coordinates are in the shower plane where the $x$ axis corresponds to the direction of the Lorentz force ( $\vec{v} \times \vec{B}$ ) and the $y$ axis perpendicular to that and to the shower axis [ $\vec{v} \times (\vec{v} \times \vec{B})$ ]. The SD shower core is at the coordinate origin. The measured polarizations are shown as the black arrows. The gray arrows are the model expectations, and the red and blue arrows are the geomagnetic and the charge-excess components, respectively. The definition of $β$ is described in the text. The air-shower properties of this event are energy of 0.9 EeV and arriving from a zenith angle of 36° and from 27° south of west. For the emission model of Eq. (2), the optimal value of the relative charge-excess strength is $a = 0.18$ .
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Figure 3
Lateral signal distribution of a single cosmic-ray event. The air-shower properties of this event are energy of 0.75 EeV and arriving at a zenith angle of 37° and from 44° west of south. Left: The energy fluence in the shower plane. The measurements are indicated as circles where the color shows the energy fluence. Gray squares are stations with signal below threshold and the red cross marks a station that is rejected due to a mismatch in the signal polarization. The background map shows the LDF parametrization. The coordinate origin is the reconstructed core position of the radio LDF fit. Note the lack of color contrast between the infill color of the data points and the background. This is indicative of the agreement between the data and the model. Right: Representation of the same data as a function of distance from the shower axis. The colored and black squares are the measured energy fluences and gray squares are the stations with signal below threshold. For the three data points with the highest energy fluence, the one-dimensional projection of the two-dimensional LDF onto lines connecting the radio-core position with the corresponding radio detector positions is illustrated with colored lines. This demonstrates the azimuthal asymmetry and complexity of the two-dimensional lateral distribution function. The inset shows the azimuthal direction of the three LDF projections. The distribution of the residuals (data versus fit) is shown as well.
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Figure 4
Skymap of the 126 selected events. Green solid circles denote air showers with at least five stations with signal and open circles denote air showers with less than five stations with signal. The red star denotes the direction of the magnetic-field axis at AERA. All measured events are at least 20° away from the magnetic-field axis. Therefore, the geomagnetic emission gives the dominant contribution to the radiation energy for all events.
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Figure 5
(Top) The radio-energy estimator $S_{radio}$ as a function of the cosmic-ray energy $E_{CR}$ measured with the surface detector. A power law is fitted to the data using a likelihood approach which takes all uncertainties and detection efficiencies into account. Green solid circles denote air showers where the core position has been determined in the radio LDF fit, i.e., all air showers with at least five stations with signal. Open circles denote events with less than five stations with signal and use the SD core position. (Bottom) Relative energy resolution: The energy of the radio detector is obtained using the fit in the left-hand figure. The left histogram contains all air showers, and the right histogram contains the air showers with at least five stations with signal (green solid circles). The expected distribution is shown as a gray shaded area which is computed from the fitted probability model that describes the fluctuations.
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