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

The 2021 Open-Data release by the Pierre Auger Collaboration

The Pierre Auger Observatory is used to study the extensive air-showers produced by cosmic rays above 1017 eV. The Observatory is operated by a Collaboration of about 400 scientists, engineers, technicians and students from more than 90 institutions in 18 countries. The Collaboration is committed to the public release of their data for the purpose of re-use by a wide community including professional scientists, in educational and outreach initiatives, and by citizen scientists. The Open Access Data for 2021 comprises 10% of the samples used for results reported at the Madison ICRC 2019, amounting to over 20000 showers measured with the surface-detector array and over 3000 showers recorded simultaneously by the surface and fluorescence detectors. Data are available in pseudo-raw (JSON) format with summary CSV file containing the reconstructed parameters. A dedicated website is used to host the datasets that are available for download. Their detailed description, along with auxiliary information needed for data analysis, is given. An online event display is also available. Simplified codes derived from those used for published analyses are provided by means of Python notebooks prepared to guide the reader to an understanding of the physics results. Here we describe the Open Access data, discuss the notebooks available and show material accessible to the user at https://opendata.auger.org/

The depth of the shower maximum of air showers measured with AERA

The Auger Engineering Radio Array (AERA) is currently the largest array of radio antennas for the detection of cosmic rays, spanning an area of 17 km2 with 153 radio antennas, measuring in the energy range from 1017.0 to 1019.0 eV. It detects the radio emission of extensive air showers produced by cosmic rays in the 30 − 80 MHz band. The cosmic-ray mass composition is a crucial piece of information in determining the sources of cosmic rays and their acceleration mechanisms. The depth of the shower maximum, Xmax, a probe for mass composition can be determined with a likelihood analysis that compares the measured radio-emission footprint on the ground to an ensemble of footprints from CORSIKA/CoREAS Monte-Carlo air shower simulations. These simulations are also used to determine the resolution of the method and to validate the reconstruction by identifying and correcting for systematic uncertainties. We will present the method for the reconstruction of the depth of the shower maximum, achieving a resolution of up to 15 g/cm2, show compatibility with the independent fluorescence detector reconstruction measured on an event-by-event basis, and show that the data taken over the past seven years with AERA shows a light cosmic-ray mass composition reconstruction in the energy range from 1017.5 to 1018.8 eV

Design, upgrade and characterization of the silicon photomultiplier front-end for the AMIGA detector at the Pierre Auger Observatory

AMIGA (Auger Muons and Infill for the Ground Array) is an upgrade of the Pierre Auger Observatory to complement the study of ultra-high-energy cosmic rays (UHECR) by measuring the muon content of extensive air showers (EAS). It consists of an array of 61 water Cherenkov detectors on a denser spacing in combination with underground scintillation detectors used for muon density measurement. Each detector is composed of three scintillation modules, with 10 m$^2$ detection area per module, buried at 2.3 m depth, resulting in a total detection area of 30 m$^2$. Silicon photomultiplier sensors (SiPM) measure the amount of scintillation light generated by charged particles traversing the modules. In this paper, the design of the front-end electronics to process the signals of those SiPMs and test results from the laboratory and from the Pierre Auger Observatory are described. Compared to our previous prototype, the new electronics shows a higher performance, higher efficiency and lower power consumption, and it has a new acquisition system with increased dynamic range that allows measurements closer to the shower core. The new acquisition system is based on the measurement of the total charge signal that the muonic component of the cosmic ray shower generates in the detector.Comment: 40 pages, 33 figure

Design and implementation of the AMIGA embedded system for data acquisition

The Auger Muon Infill Ground Array (AMIGA) is part of the AugerPrime upgrade of the Pierre Auger Observatory. It consists of particle counters buried 2.3 m underground next to the water-Cherenkov stations that form the 23.5 km$^2$ large infilled array. The reduced distance between detectors in this denser area allows the lowering of the energy threshold for primary cosmic ray reconstruction down to about 10$^{17}$ eV. At the depth of 2.3 m the electromagnetic component of cosmic ray showers is almost entirely absorbed so that the buried scintillators provide an independent and direct measurement of the air showers muon content. This work describes the design and implementation of the AMIGA embedded system, which provides centralized control, data acquisition and environment monitoring to its detectors. The presented system was firstly tested in the engineering array phase ended in 2017, and lately selected as the final design to be installed in all new detectors of the production phase. The system was proven to be robust and reliable and has worked in a stable manner since its first deployment.Comment: Accepted for publication at JINST. Published version, 34 pages, 15 figures, 4 table

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

A search for ultra-high-energy photons at the Pierre Auger Observatory exploiting air-shower Universality

The Pierre Auger Observatory is the most sensitive detector to primary photons with energies above ∼ 0.2 EeV. It measures extensive air showers using a hybrid technique that combines a fluorescence detector (FD) with a ground array of particle detectors (SD). The signatures of a photon-induced air shower are a larger atmospheric depth at the shower maximum (Xmax) and a steeper lateral distribution function, along with a lower number of muons with respect to the bulk of hadron-induced background. Using observables measured by the FD and SD, three photon searches in different energy bands are performed. In particular, between threshold energies of 1–10 EeV, a new analysis technique has been developed by combining the FD-based measurement of Xmax with the SD signal through a parameter related to its muon content, derived from the universality of the air showers. This technique has led to a better photon/hadron separation and, consequently, to a higher search sensitivity, resulting in a tighter upper limit than before. The outcome of this new analysis is presented here, along with previous results in the energy ranges below 1 EeV and above 10 EeV. From the data collected by the Pierre Auger Observatory in about 15 years of operation, the most stringent constraints on the fraction of photons in the cosmic flux are set over almost three decades in energy

A combined fit of energy spectrum, shower depth distribution and arrival directions to constrain astrophysical models of UHECR sources

The combined fit of the measured energy spectrum and distribution of depths of shower maximum of ultra-high-energy cosmic rays is known to constrain the parameters of astrophysical scenarios with homogeneous source distributions. Further measurements show that the cosmic-ray arrival directions agree better with the directions and fluxes of catalogs of starburst galaxies and active galactic nuclei than with isotropy. Here, we present a novel combination of both analyses. For that, a three-dimensional universe model containing a nearby source population and a homogeneous background source distribution is built, and its parameters are adapted using a combined fit of the energy spectrum, depth of shower maximum distribution and energy-dependent arrival directions. The model takes into account a symmetric magnetic field blurring, source evolution and interactions during propagation. We use simulated data, which resemble measurements of the Pierre Auger Observatory, to evaluate the method’s sensitivity. With this, we are able to verify that the source parameters as well as the fraction of events from the nearby source population and the size of the magnetic field blurring are determined correctly, and that the data is described by the fitted model including the catalog sources with their respective fluxes and three-dimensional positions. We demonstrate that by combining all three measurements we reach the sensitivity necessary to discriminate between the catalogs of starburst galaxies and active galactic nuclei