Particle theory

Abstract:

Over the last two decades, various experiments have measured muon densities in extensive air showers over several orders of magnitude in primary energy. While some experiments observed differences in the muon densities between simulated and experimentally measured air showers, others reported no discrepancies. We will present an update of the meta-analysis of muon measurements from nine air shower experiments, covering shower energies between a few PeV and tens of EeV and muon threshold energies from a few 100 MeV to about 10GeV. In order to compare measurements from different experiments, their energy scale was cross-calibrated and the experimental data has been compared using a universal reference scale based on air shower simulations. Above 10 PeV, we find a muon excess with respect to simulations for all hadronic interaction models, which is increasing with shower energy. For EPOS-LHC and QGSJet-II.04 the significance of the slope of the increase is analyzed in detail under different assumptions of the individual experimental uncertainties.

Abstract:

The immensity of the string landscape and the difficulty of identifying solutions that match the observed features of particle physics have raised serious questions about the predictive power of string theory. Modern methods of optimisation and search can, however, significantly improve the prospects of constructing the standard model in string theory. In this paper we scrutinise a corner of the heterotic string landscape consisting of compactifications on Calabi-Yau three-folds with monad bundles and show that genetic algorithms can be successfully used to generate anomaly-free supersymmetric (Formula presented.) GUTs with three families of fermions that have the right ingredients to accommodate the standard model. We compare this method with reinforcement learning and find that the two methods have similar efficacy but somewhat complementary characteristics.