Parallel processing of radio signals and detector arrays in CORSIKA 8

This contribution describes some recent advances in the parallelization of the generation and processing of radio signals emitted by particle showers in CORSIKA 8. CORSIKA 8 is a Monte Carlo simulation framework for modeling ultra-high energy particle cascades in astroparticle physics. The aspects associated with the generation and processing of radio signals in antennas arrays are reviewed, focusing on the key design opportunities and constraints for deployment of multiple threads on such calculations. The audience is also introduced to Gyges, a lightweight, header-only and flexible multithread self-adaptive scheduler written compliant with C++17 and C++20, which is used to distribute and manage the worker computer threads during the parallel calculations. Finally, performance and scalability measurements are provided and the integration into CORSIKA 8 is commented

Hadron cascades in CORSIKA 8

We present characteristics of hadronic cascades from interactions of cosmic rays in the atmosphere, simulated by the novel CORSIKA 8 framework. The simulated spectra of secondaries, such as pions, kaons, baryons and muons, are compared with the cascade equations solvers MCEq in air shower mode, and full 3D air shower Monte Carlo simulations using the legacy CORSIKA 7. A novel capability of CORSIKA 8 is the simulation of cascades in media other than air, widening the scope of potential applications. We demonstrate this by simulating cosmic ray showers in the Mars atmosphere, as well as simulating a shower traversing from air into water. The CORSIKA 8 framework demonstrates good accuracy and robustness in comparison with previous results, in particular in those relevant for the production of muons in air showers. Furthermore, the impact of forward ρ$^{0}$ production on air showers is studied and illustrated

In-situ estimation of ice crystal properties at the South Pole using LED calibration data from the IceCube Neutrino Observatory

The IceCube Neutrino Observatory instruments about 1 km3 of deep, glacial ice at the geographic South Pole using 5160 photomultipliers to detect Cherenkov light emitted by charged relativistic particles. A unexpected light propagation effect observed by the experiment is an anisotropic attenuation, which is aligned with the local flow direction of the ice. Birefringent light propagation has been examined as a possible explanation for this effect. The predictions of a first-principles birefringence model developed for this purpose, in particular curved light trajectories resulting from asymmetric diffusion, provide a qualitatively good match to the main features of the data. This in turn allows us to deduce ice crystal properties. Since the wavelength of the detected light is short compared to the crystal size, these crystal properties do not only include the crystal orientation fabric, but also the average crystal size and shape, as a function of depth. By adding small empirical corrections to this first-principles model, a quantitatively accurate description of the optical properties of the IceCube glacial ice is obtained. In this paper, we present the experimental signature of ice optical anisotropy observed in IceCube LED calibration data, the theory and parametrization of the birefringence effect, the fitting procedures of these parameterizations to experimental data as well as the inferred crystal properties.</p

Recent neutrino oscillation results with the IceCube experiment

The IceCube South Pole Neutrino Observatory is a Cherenkov detector instrumented in a cubic kilometer of ice at the South Pole. IceCube’s primary scientific goal is the detection of TeV neutrino emissions from astrophysical sources. At the lower center of the IceCube array, there is a subdetector called DeepCore, which has a denser configuration that makes it possible to lower the energy threshold of IceCube and observe GeV-scale neutrinos, opening the window to atmospheric neutrino oscillations studies. Advances in physics sensitivity have recently been achieved by employing Convolutional Neural Networks to reconstruct neutrino interactions in the DeepCore detector. In this contribution, the recent IceCube result from the atmospheric muon neutrino disappearance analysis using the CNN-reconstructed neutrino sample are presented and compared to the existing worldwide measurements

Angular dependence of the atmospheric neutrino flux with IceCube data

IceCube Neutrino Observatory, the cubic kilometer detector embedded in ice of the geographic South Pole, is capable of detecting particles from several GeV up to PeV energies enabling precise neutrino spectrum measurement. The diffuse neutrino flux can be subdivided into three components: astrophysical, from extraterrestrial sources; conventional, from pion and kaon decays in atmospheric Cosmic Ray cascades; and the yet undetected prompt component from the decay of charmed hadrons. A particular focus of this work is to test the predicted angular dependence of the atmospheric neutrino flux using an unfolding method. Unfolding is a set of methods aimed at determining a value from related quantities in a model-independent way, eliminating the influence of several assumptions made in the process. In this work, we unfold the muon neutrino energy spectrum and employ a novel technique for rebinning the observable space to ensure sufficient event numbers within the low statistic region at the highest energies. We present the unfolded energy and zenith angle spectrum reconstructed from IceCube data and compare the result with model expectations and previous measurements