The muon deficit problem: a new method to calculate the muon rescaling factors and the Heitler-Matthews beta exponent

Simulations of extensive air showers using current hadronic interaction models predict too small numbers of muons compared to events observed in the air-shower experiments, which is known as the muon-deficit problem. In this work, we present a new method to calculate the factor by which the muon signal obtained via Monte-Carlo simulations must be rescaled to match the data, as well as the beta exponent from the Heitler-Matthews model which governs the number of muons found in an extensive air shower as a function of the mass and the energy of the primary cosmic ray. This method uses the so-called z variable (difference between the total reconstructed and the simulated signals), which is connected to the muon signal and is roughly independent of the zenith angle, but depends on the mass of the primary cosmic ray. Using a mock dataset built from QGSJetII-04, we show that such a method allows us to reproduce the average muon signal from this dataset using Monte-Carlo events generated with the EPOS-LHC hadronic model, with accuracy better than 6%. As a consequence of the good recovery of the muon signal for each primary included in the analysis, also the beta exponent can be obtained with accuracy of less than 1% for the studied system. Detailed simulations show a dependence of the beta exponent on hadronic interaction properties, thus the determination of this parameter is important for understanding the muon deficit problem.Comment: 8 pages, 5 figures, 2 tables, accepted for publication in the proceedings of the 27th European Cosmic Ray Symposiu

Method for calculation of the beta exponent from the Heitler-Matthews model of hadronic air showers

The number of muons in an air shower is a strong indicator of the mass of the primary particle and increases with a small power of the cosmic ray mass by the $\beta$-exponent, $N_{\mu} \sim A^{(1-\beta)}$. This behaviour can be explained in terms of the Heitler-Matthews model of hadronic air showers. In this paper, we present a method for calculating $\beta$ from the Heitler-Matthews model. The method has been successfully verified with a series of simulated events observed by the Pierre Auger Observatory at $10^{19}$ eV. To follow real measurements of the mass composition at this energy, the generated sample consists of a certain fraction of events produced with p, He, N and Fe primary energies. Since hadronic interactions at the highest energies can differ from those observed at energies reached by terrestrial accelerators, we generate a mock data set with $\beta =0.92$ (the canonical value) and $\beta =0.96$ (a more exotic scenario). The method can be applied to measured events to determine the muon signal for each primary particle as well as the muon scaling factor and the $\beta$-exponent. Determining the $\beta$-exponent can effectively constrain the parameters that govern hadronic interactions and help solve the so-called muon problem, where hadronic interaction models predict too few muons relative to observed events. In this paper, we lay the foundation for the future analysis of measured data from the Pierre Auger Observatory with a simulation study.Comment: Proccedings of 38th International Cosmic Ray Conference (ICRC2023

The muon deficit problem: a new method to calculate the muon rescaling factors and the Heitler-Matthews β exponent

Simulations of extensive air showers using current hadronic interaction models predict too small numbers of muons compared to events observed in the air-shower experiments, which is known as the muon-deficit problem. In this work, we present a new method to calculate the factor by which the muon signal obtained via Monte-Carlo simulations must be rescaled to match the data, as well as the exponent from the Heitler-Matthews model which governs the number of muons found in an extensive air shower as a function of the mass and the energy of the primary cosmic ray. This method uses the so-called variable (difference between the total reconstructed and the simulated signals), which is connected to the muon signal and is roughly independent of the zenith angle, but depends on the mass of the primary cosmic ray. Using a mock dataset built from QGSJetII-04, we show that such a method allows us to reproduce the average muon signal from this dataset using Monte-Carlo events generated with the EPOS-LHC hadronic model, with accuracy better than 6%. As a consequence of the good recovery of the muon signal for each primary included in the analysis, also the exponent can be obtained with accuracy of less than 1% for the studied system. Detailed simulations show a dependence of the exponent on hadronic interaction properties, thus the determination of this parameter is important for understanding the muon deficit problem

High-Energy Neutrino Astronomy—Baikal-GVD Neutrino Telescope in Lake Baikal

High-energy neutrino astronomy is a fascinating new field of research, rapidly developing over recent years. It opens a new observation window on the most violent processes in the universe, fitting very well to the concept of multi-messenger astronomy. This may be exemplified by the recent discovery of the high-energy neutrino emissions from the γ-ray loud blazar TXS 0506+056. Constraining astrophysical neutrino fluxes can also help to understand the long-standing mystery of the origin of the ultra-high energy cosmic rays. Astronomical studies of high-energy neutrinos are carried out by large-scale next-generation neutrino telescopes located in different regions of the world, forming a global network of complementary detectors. The Baikal-GVD, being currently the largest neutrino telescope in the Northern Hemisphere and still growing up, is an important constituent of this network. This paper briefly reviews working principles, analysis methods, and some selected results of the Baikal-GVD neutrino telescope

CNN-Based Classifier as an Offline Trigger for the CREDO Experiment

Gamification is known to enhance users’ participation in education and research projects that follow the citizen science paradigm. The Cosmic Ray Extremely Distributed Observatory (CREDO) experiment is designed for the large-scale study of various radiation forms that continuously reach the Earth from space, collectively known as cosmic rays. The CREDO Detector app relies on a network of involved users and is now working worldwide across phones and other CMOS sensor-equipped devices. To broaden the user base and activate current users, CREDO extensively uses the gamification solutions like the periodical Particle Hunters Competition. However, the adverse effect of gamification is that the number of artefacts, i.e., signals unrelated to cosmic ray detection or openly related to cheating, substantially increases. To tag the artefacts appearing in the CREDO database we propose the method based on machine learning. The approach involves training the Convolutional Neural Network (CNN) to recognise the morphological difference between signals and artefacts. As a result we obtain the CNN-based trigger which is able to mimic the signal vs. artefact assignments of human annotators as closely as possible. To enhance the method, the input image signal is adaptively thresholded and then transformed using Daubechies wavelets. In this exploratory study, we use wavelet transforms to amplify distinctive image features. As a result, we obtain a very good recognition ratio of almost 99% for both signal and artefacts. The proposed solution allows eliminating the manual supervision of the competition process

Simulations of Cosmic Ray Ensembles originated nearby the Sun

Cosmic Ray Ensembles (CRE) are yet not observed groups of cosmic rays with a common primary interaction vertex or the same parent particle. One of the processes capable of initiating identifiable CRE is an interaction of an ultra-high energy (UHE) photon with the solar magnetic field which results in an electron pair production and the subsequent synchrotron radiation. The resultant electromagnetic cascade forms a very characteristic line-like front of a very small width ($\sim$ meters), stretching from tens of thousands to even many millions of kilometers. In this contribution we present the results of applying a toy model to simulate detections of such CRE at the ground level with an array of ideal detectors of different dimensions. The adopted approach allows us to assess the CRE detection feasibility for a specific configuration of a detector array. The process of initiation and propagation of an electromagnetic cascade originated from an UHE photon passing near the Sun, as well as the resultant particle distribution on ground, were simulated using the CORSIKA program with the PRESHOWER option, both modified accordingly. The studied scenario results in photons forming a cascade that extends even over tens of millions of kilometers when it arrives at the top of the Earth's atmosphere, and the photon energies span practically the whole cosmic ray energy spectrum. The topology of the signal consists of very extended CRE shapes, and the characteristic, very much elongated disk-shape of the particle distribution on ground illustrates the potential for identification of CRE of this type.Comment: 8 pages, 3 figures. Proceedings of the International Cosmic Rays Conference 2021, 12-23 July, Berlin, German