The Pierre Auger Observatory Open Data

The Pierre Auger Collaboration has embraced the concept of open access to their research data since its foundation, with the aim of giving access to the widest possible community. A gradual process of release began as early as 2007 when 1% of the cosmic-ray data was made public, along with 100% of the space-weather information. In February 2021, a portal was released containing 10% of cosmic-ray data collected from 2004 to 2018, during Phase I of the Observatory. The Portal included detailed documentation about the detection and reconstruction procedures, analysis codes that can be easily used and modified and, additionally, visualization tools. Since then the Portal has been updated and extended. In 2023, a catalog of the 100 highest-energy cosmic-ray events examined in depth has been included. A specific section dedicated to educational use has been developed with the expectation that these data will be explored by a wide and diverse community including professional and citizen-scientists, and used for educational and outreach initiatives. This paper describes the context, the spirit and the technical implementation of the release of data by the largest cosmic-ray detector ever built, and anticipates its future developments.Comment: 19 pages, 8 figure

A Search for Photons with Energies Above 2 × 1017^{17} eV Using Hybrid Data from the Low-Energy Extensions of the Pierre Auger Observatory

Ultra-high-energy photons with energies exceeding 10$^{17}$ eV offer a wealth of connections to different aspects of cosmic-ray astrophysics as well as to gamma-ray and neutrino astronomy. The recent observations of photons with energies in the 10$^{15}$ eV range further motivate searches for even higher-energy photons. In this paper, we present a search for photons with energies exceeding 2 × 10$^{17}$ eV using about 5.5 yr of hybrid data from the low-energy extensions of the Pierre Auger Observatory. The upper limits on the integral photon flux derived here are the most stringent ones to date in the energy region between 10$^{17}$ and 10$^{18}$ eV

A Search for Photons with Energies above 2 × 1017eV Using Hybrid Data from the Low-Energy Extensions of the Pierre Auger Observatory

Ultra-high-energy photons with energies exceeding 1017 eV offer a wealth of connections to different aspects of cosmic-ray astrophysics as well as to gamma-ray and neutrino astronomy. The recent observations of photons with energies in the 1015 eV range further motivate searches for even higher-energy photons. In this paper, we present a search for photons with energies exceeding 2 × 1017 eV using about 5.5 yr of hybrid data from the low-energy extensions of the Pierre Auger Observatory. The upper limits on the integral photon flux derived here are the most stringent ones to date in the energy region between 1017 and 1018 eV

Radio Measurements of the Depth of Air-Shower Maximum at the Pierre Auger Observatory

The Auger Engineering Radio Array (AERA), part of the Pierre Auger Observatory, is currently the largest array of radio antenna stations deployed for the detection of cosmic rays, spanning an area of $17$ km$^2$ with 153 radio stations. It detects the radio emission of extensive air showers produced by cosmic rays in the $30-80$ MHz band. Here, we report the AERA measurements of the depth of the shower maximum ($X_\text{max}$), a probe for mass composition, at cosmic-ray energies between $10^{17.5}$ to $10^{18.8}$ eV, which show agreement with earlier measurements with the fluorescence technique at the Pierre Auger Observatory. We show advancements in the method for radio $X_\text{max}$ reconstruction by comparison to dedicated sets of CORSIKA/CoREAS air-shower simulations, including steps of reconstruction-bias identification and correction, which is of particular importance for irregular or sparse radio arrays. Using the largest set of radio air-shower measurements to date, we show the radio $X_\text{max}$ resolution as a function of energy, reaching a resolution better than $15$ g cm$^{-2}$ at the highest energies, demonstrating that radio $X_\text{max}$ measurements are competitive with the established high-precision fluorescence technique. In addition, we developed a procedure for performing an extensive data-driven study of systematic uncertainties, including the effects of acceptance bias, reconstruction bias, and the investigation of possible residual biases. These results have been cross-checked with air showers measured independently with both the radio and fluorescence techniques, a setup unique to the Pierre Auger Observatory.Comment: Submitted to Phys. Rev.

Ground observations of a space laser for the assessment of its in-orbit performance

The wind mission Aeolus of the European Space Agency was a groundbreaking achievement for Earth observation. Between 2018 and 2023, the space-borne lidar instrument ALADIN onboard the Aeolus satellite measured atmospheric wind profiles with global coverage which contributed to improving the accuracy of numerical weather prediction. The precision of the wind observations, however, declined over the course of the mission due to a progressive loss of the atmospheric backscatter signal. The analysis of the root cause was supported by the Pierre Auger Observatory in Argentina whose fluorescence detector registered the ultraviolet laser pulses emitted from the instrument in space, thereby offering an estimation of the laser energy at the exit of the instrument for several days in 2019, 2020 and 2021. The reconstruction of the laser beam not only allowed for an independent assessment of the Aeolus performance, but also helped to improve the accuracy in the determination of the laser beam's ground track on single pulse level. The results presented in this paper set a precedent for the monitoring of space lasers by ground-based telescopes and open new possibilities for the calibration of cosmic-ray observatories.Comment: 10 pages, 10 figure

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

The Pierre Auger Observatory, at present the largest cosmic-ray observatory ever built, is instrumented with a ground array of 1600 water-Cherenkov detectors, known as the Surface Detector (SD). The SD samples the secondary particle content (mostly photons, electrons, positrons and muons) of extensive air showers initiated by cosmic rays with energies ranging from $10^{17}~$eV up to more than $10^{20}~$eV. Measuring the independent contribution of the muon component to the total registered signal is crucial to enhance the capability of the Observatory to estimate the mass of the cosmic rays on an event-by-event basis. However, with the current design of the SD, it is difficult to straightforwardly separate the contributions of muons to the SD time traces from those of photons, electrons and positrons. In this paper, we present a method aimed at extracting the muon component of the time traces registered with each individual detector of the SD using Recurrent Neural Networks. We derive the performances of the method by training the neural network on simulations, in which the muon and the electromagnetic components of the traces are known. We conclude this work showing the performance of this method on experimental data of the Pierre Auger Observatory. We find that our predictions agree with the parameterizations obtained by the AGASA collaboration to describe the lateral distributions of the electromagnetic and muonic components of extensive air showers.Comment: 23 pages, 15 figures. Version accepted for publication in JINS

Deep-learning based reconstruction of the shower maximum Xmax using the water-Cherenkov detectors of the Pierre Auger Observatory

The atmospheric depth of the air shower maximum Xmax is an observable commonly used for the determination of the nuclear mass composition of ultra-high energy cosmic rays. Direct measurements of Xmax are performed using observations of the longitudinal shower development with fluorescence telescopes. At the same time, several methods have been proposed for an indirect estimation of Xmax from the characteristics of the shower particles registered with surface detector arrays. In this paper, we present a deep neural network (DNN) for the estimation of Xmax. The reconstruction relies on the signals induced by shower particles in the ground based water-Cherenkov detectors of the Pierre Auger Observatory. The network architecture features recurrent long short-term memory layers to process the temporal structure of signals and hexagonal convolutions to exploit the symmetry of the surface detector array. We evaluate the performance of the network using air showers simulated with three different hadronic interaction models. Thereafter, we account for long-term detector effects and calibrate the reconstructed Xmax using fluorescence measurements. Finally, we show that the event-by-event resolution in the reconstruction of the shower maximum improves with increasing shower energy and reaches less than 25 g/cm2 at energies above 2×1019 eV

Demonstrating Agreement between Radio and Fluorescence Measurements of the Depth of Maximum of Extensive Air Showers at the Pierre Auger Observatory

We show, for the first time, radio measurements of the depth of shower maximum ($X_\text{max}$) of air showers induced by cosmic rays that are compared to measurements of the established fluorescence method at the same location. Using measurements at the Pierre Auger Observatory we show full compatibility between our radio and the previously published fluorescence data set, and between a subset of air showers observed simultaneously with both radio and fluorescence techniques, a measurement setup unique to the Pierre Auger Observatory. Furthermore, we show radio $X_\text{max}$ resolution as a function of energy and demonstrate the ability to make competitive high-resolution $X_\text{max}$ measurements with even a sparse radio array. With this, we show that the radio technique is capable of cosmic-ray mass composition studies, both at Auger and at other experiments.Comment: Submitted to Phys. Rev. Let