No Arabic abstract
Hadron generation models are indispensable for the simulation and calibration of particle physics detectors. The models used by the Geant4 simulation tool kit are compared with inclusive spectra of secondary protons and pions from the interactions with beryllium nuclei of +8.9 GeV/c protons and pions, and of -8.0 GeV/c pions. We report on significant disagreements between data and model predictions especially in the polar-angle distributions of secondary protons and pions.
We report on the comparison of production characteristics of secondary protons and charged pions in the interactions of protons and charged pions with momentum between 3 GeV/c and 15 GeV/c with beryllium, copper, and tantalum nuclei, with simulations by the FLUKA and Geant4 Monte Carlo tool kits. Overall production cross-sections are reasonably well reproduced, within factors of two. In more detail, there are areas with poor agreement that are unsatisfactory and call for modelling improvements. Overall, the current FLUKA simulation fares better than the current Geant4 simulation.
The so-called LSND anomaly, a 3.8 sigma excess of anti-nu_e events interpreted as originating from anti-nu_mu -> anti-nu_e oscillation, gave rise to many theoretical speculations. The MiniBooNE Collaboration reported inconsistency of this interpretation with the findings from their search for nu_mu -> nu_e oscillations. Yet the origin of the LSND anomaly was never clarified. A critical issue is the prediction of the background anti-nu_e flux that was used in the analysis of the LSND experiment. For this, decisive input comes from pion spectra measured with the HARP large-angle spectrometer under conditions that closely resemble the LSND situation: a proton beam with 800 MeV kinetic energy hitting a water target.
The Monte Carlo models ARIADNE, HERWIG and LEPTO are compared to deep-inelastic scattering data measured at the ep-collider HERA.
We examine the exclusion limits set by the CDF and D0 experiments on the Standard Model Higgs boson mass from their searches at the Tevatron in the light of large theoretical uncertainties on the signal and background cross sections. We show that when these uncertainties are consistently taken into account, the sensitivity of the experiments becomes significantly lower and the currently excluded mass range $M_H=158$-175 GeV would be entirely reopened. The necessary luminosity required to recover the current sensitivity is found to be a factor of two higher than the present one.
One of the most effective approaches to improving the performance of a machine-learning model is to acquire additional training data. To do so, a model owner may seek to acquire relevant training data from a data owner. Before procuring the data, the model owner needs to appraise the data. However, the data owner generally does not want to share the data until after an agreement is reached. The resulting Catch-22 prevents efficient data markets from forming. To address this problem, we develop data appraisal methods that do not require data sharing by using secure multi-party computation. Specifically, we study methods that: (1) compute parameter gradient norms, (2) perform model fine-tuning, and (3) compute influence functions. Our experiments show that influence functions provide an appealing trade-off between high-quality appraisal and required computation.