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Abstract 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 by the Pierre Auger Observatory from 2004 to 2018, during the first phase of operation of the Observatory. The Open Data Portal includes 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 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. 

We present measurements of the atmospheric depth of the shower maximum $X_{\max }$, inferred for the first time on an event-by-event level using the surface detector of the Pierre Auger Observatory. Using deep learning, we were able to extend measurements of the $X_{\max }$distributions up to energies of 100 EeV ( ${10}^{20}\mathrm{eV}$), not yet revealed by current measurements, providing new insights into the mass composition of cosmic rays at extreme energies. Gaining a 10-fold increase in statistics compared to the fluorescence detector data, we find evidence that the rate of change of the average $X_{\max }$with the logarithm of energy features three breaks at $6.5\pm 0.6\left(\mathrm{stat}\right)\pm 1\left(\mathrm{syst}\right)\mathrm{EeV}$, $11\pm 2\left(\mathrm{stat}\right)\pm 1\left(\mathrm{syst}\right)\mathrm{EeV}$, and $31\pm 5\left(\mathrm{stat}\right)\pm 3\left(\mathrm{syst}\right)\mathrm{EeV}$, in the vicinity to the three prominent features (ankle, instep, suppression) of the cosmic-ray flux. The energy evolution of the mean and standard deviation of the measured $X_{\max }$distributions indicates that the mass composition becomes increasingly heavier and purer, thus being incompatible with a large fraction of light nuclei between 50 and 100 EeV. Published by the American Physical Society2025 

We report an investigation of the mass composition of cosmic rays with energies from 3 to 100 EeV ( $1\mathrm{EeV}={10}^{18}\mathrm{eV}$) using the distributions of the depth of shower maximum $X_{\max }$. The analysis relies on $\sim 50,000$events recorded by the surface detector of the Pierre Auger Observatory and a deep-learning-based reconstruction algorithm. Above energies of 5 EeV, the dataset offers a 10-fold increase in statistics with respect to fluorescence measurements at the Observatory. After cross-calibration using the fluorescence detector, this enables the first measurement of the evolution of the mean and the standard deviation of the $X_{\max }$distributions up to 100 EeV. Our findings are threefold: (i) The evolution of the mean logarithmic mass toward a heavier composition with increasing energy can be confirmed and is extended to 100 EeV. (ii) The evolution of the fluctuations of $X_{\max }$toward a heavier and purer composition with increasing energy can be confirmed with high statistics. We report a rather heavy composition and small fluctuations in $X_{\max }$at the highest energies. (iii) We find indications for a characteristic structure beyond a constant change in the mean logarithmic mass, featuring three breaks that are observed in proximity to the ankle, instep, and suppression features in the energy spectrum. Published by the American Physical Society2025 

Abstract Results are presented for the measurement of large-scale anisotropies in the arrival directions of ultra–high-energy cosmic rays detected at the Pierre Auger Observatory during 19 yr of operation, prior to AugerPrime, the upgrade of the observatory. The 3D dipole amplitude and direction are reconstructed above 4 EeV in four energy bins. Besides the established dipolar anisotropy in R.A. above 8 EeV, the Fourier amplitude of the 8–16 EeV energy bin is now also above the 5σdiscovery level. No time variation of the dipole moment above 8 EeV is found, setting an upper limit to the rate of change of such variations of 0.3% yr⁻¹at the 95% confidence level. Additionally, the results for the angular power spectrum are shown, demonstrating no other statistically significant multipoles. The results for the equatorial dipole component down to 0.03 EeV are presented, using for the first time a data set obtained with a trigger that has been optimized for lower energies. Finally, model predictions are discussed and compared with observations, based on two source emission scenarios obtained in the combined fit of spectrum and composition above 0.6 EeV. 

The Pierre Auger Observatory is the most sensitive instrument to detect photons with energies above $10^{17}\mathrm{eV}$. It measures extensive air showers generated by ultrahigh energy cosmic rays using a hybrid technique that exploits the combination of a fluorescence detector with a ground array of particle detectors. The signatures of a photon-induced air shower are a larger atmospheric depth of the shower maximum ( $X_{\max }$) and a steeper lateral distribution function, along with a lower number of muons with respect to the bulk of hadron-induced cascades. In this work, a new analysis technique in the energy interval between 1 and 30 EeV ( $1\mathrm{EeV}=10^{18}\mathrm{eV}$) has been developed by combining the fluorescence detector-based measurement of $X_{\max }$with the specific features of the surface detector signal through a parameter related to the air shower muon content, derived from the universality of the air shower development. No evidence of a statistically significant signal due to photon primaries was found using data collected in about 12 years of operation. Thus, upper bounds to the integral photon flux have been set using a detailed calculation of the detector exposure, in combination with a data-driven background estimation. The derived 95% confidence level upper limits are 0.0403, 0.01113, 0.0035, 0.0023, and $0.0021{\mathrm{km}}^{-2}{\mathrm{sr}}^{-1}{\mathrm{yr}}^{-1}$above 1, 2, 3, 5, and 10 EeV, respectively, leading to the most stringent upper limits on the photon flux in the EeV range. Compared with past results, the upper limits were improved by about 40% for the lowest energy threshold and by a factor 3 above 3 EeV, where no candidates were found and the expected background is negligible. The presented limits can be used to probe the assumptions on chemical composition of ultrahigh energy cosmic rays and allow for the constraint of the mass and lifetime phase space of super-heavy dark matter particles. Published by the American Physical Society2024 

Abstract The flux of ultra-high energy cosmic rays reaching Earth above the ankle energy (5 EeV) can be described as a mixture of nuclei injected by extragalactic sources with very hard spectra and a low rigidity cutoff.Extragalactic magnetic fields existing between the Earth and the closest sources can affect the observed CR spectrum by reducing the flux of low-rigidity particles reaching Earth. We perform a combined fit of the spectrum and distributions of depth of shower maximum measured with the Pierre Auger Observatory including the effect of this magnetic horizon in the propagation of UHECRs in the intergalactic space.We find that, within a specific range of the various experimental and phenomenological systematics, the magnetic horizon effect can be relevant for turbulent magnetic field strengths in the local neighbourhood in which the closest sources lieof order B_rms≃ (50–100) nG (20 Mpc/d_s)( 100 kpc/L_coh)^1/2, with d_sthe typical intersource separation and L_cohthe magnetic field coherence length. When this is the case,the inferred slope of the source spectrum becomes softer and can be closer to the expectations of diffusive shock acceleration, i.e., ∝ E^-2.An additional cosmic-ray population with higher source density and softer spectra, presumably also extragalactic and dominating the cosmic-ray flux at EeV energies, is also required to reproduce the overall spectrum and composition results for all energies down to 0.6 EeV. 

We test the predictions of hadronic interaction models regarding the depth of maximum of air-shower profiles, $X_{\max }$, and ground-particle signals in water-Cherenkov detectors at 1000 m from the shower core, $S\left(1000\right)$, using the data from the fluorescence and surface detectors of the Pierre Auger Observatory. The test consists of fitting the measured two-dimensional ( $S\left(1000\right)$, $X_{\max }$) distributions using templates for simulated air showers produced with hadronic interaction models pos-, et--04, 2.3d and leaving the scales of predicted $X_{\max }$and the signals from hadronic component at ground as free-fit parameters. The method relies on the assumption that the mass composition remains the same at all zenith angles, while the longitudinal shower development and attenuation of ground signal depend on the mass composition in a correlated way. The analysis was applied to 2239 events detected by both the fluorescence and surface detectors of the Pierre Auger Observatory with energies between ${10}^{18.5}\mathrm{eV}$to ${10}^{19.0}\mathrm{eV}$and zenith angles below 60°. We found, that within the assumptions of the method, the best description of the data is achieved if the predictions of the hadronic interaction models are shifted to deeper $X_{\max }$values and larger hadronic signals at all zenith angles. Given the magnitude of the shifts and the data sample size, the statistical significance of the improvement of data description using the modifications considered in the paper is larger than $5\sigma$even for any linear combination of experimental systematic uncertainties. Published by the American Physical Society2024 

A<sc>bstract</sc> A measurement is performed of Higgs bosons produced with high transverse momentum (p_T) via vector boson or gluon fusion in proton-proton collisions. The result is based on a data set with a center-of-mass energy of 13 TeV collected in 2016–2018 with the CMS detector at the LHC and corresponds to an integrated luminosity of 138 fb⁻¹. The decay of a high-p_THiggs boson to a boosted bottom quark-antiquark pair is selected using large-radius jets and employing jet substructure and heavy-flavor taggers based on machine learning techniques. Independent regions targeting the vector boson and gluon fusion mechanisms are defined based on the topology of two quark-initiated jets with large pseudorapidity separation. The signal strengths for both processes are extracted simultaneously by performing a maximum likelihood fit to data in the large-radius jet mass distribution. The observed signal strengths relative to the standard model expectation are$$ {4.9}_{-1.6}^{+1.9} $$ ${4.9}_{-1.6}^{+1.9}$and$$ {1.6}_{-1.5}^{+1.7} $$ ${1.6}_{-1.5}^{+1.7}$for the vector boson and gluon fusion mechanisms, respectively. A differential cross section measurement is also reported in the simplified template cross section framework. 

Abstract Computing demands for large scientific experiments, such as the CMS experiment at the CERN LHC, will increase dramatically in the next decades. To complement the future performance increases of software running on central processing units (CPUs), explorations of coprocessor usage in data processing hold great potential and interest. Coprocessors are a class of computer processors that supplement CPUs, often improving the execution of certain functions due to architectural design choices. We explore the approach of Services for Optimized Network Inference on Coprocessors (SONIC) and study the deployment of this as-a-service approach in large-scale data processing. In the studies, we take a data processing workflow of the CMS experiment and run the main workflow on CPUs, while offloading several machine learning (ML) inference tasks onto either remote or local coprocessors, specifically graphics processing units (GPUs). With experiments performed at Google Cloud, the Purdue Tier-2 computing center, and combinations of the two, we demonstrate the acceleration of these ML algorithms individually on coprocessors and the corresponding throughput improvement for the entire workflow. This approach can be easily generalized to different types of coprocessors and deployed on local CPUs without decreasing the throughput performance. We emphasize that the SONIC approach enables high coprocessor usage and enables the portability to run workflows on different types of coprocessors.