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The issue of how epistemic uncertainties affect the outcome of Monte Carlo simulation is discussed by means of a concrete use case: the simulation of the longitudinal energy deposition profile of low energy protons. A variety of electromagnetic and hadronic physics models is investigated, and their effects are analyzed. Possible systematic effects are highlighted. The results identify requirements for experimental measurements capable of reducing epistemic uncertainties in the simulation.
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The assessment of the reliability of Monte Carlo simulations is discussed, with emphasis on uncertainty quantification and the related impact on experimental results. Methods and techniques to account for epistemic uncertainties, i.e. for intrinsic knowledge gaps in physics modeling, are discussed with the support of applications to concrete experimental scenarios. Ongoing projects regarding the investigation of epistemic uncertainties in the Geant4 simulation toolkit are reported.
The Scikit-HEP project is a community-driven and community-oriented effort with the aim of providing Particle Physics at large with a Python scientific toolset containing core and common tools. The project builds on five pillars that embrace the major topics involved in a physicists analysis work: datasets, data aggregations, modelling, simulation and visualisation. The vision is to build a user and developer community engaging collaboration across experiments, to emulate scikit-learns unified interface with Astropys embrace of third-party packages, and to improve discoverability of relevant tools.
A number of methods have been proposed recently which exploit multiple highly-correlated interpretations of events, or of jets within an event. For example, Qjets reclusters a jet multiple times and telescoping jets uses multiple cone sizes. Previous work has employed these methods in pseudo-experimental analyses and found that, with a simplified statistical treatment, they give sizable improvements over traditional methods. In this paper, the improvement gain from multiple event interpretations is explored with methods much closer to those used in real experiments. To this end, we derive a generalized extended maximum likelihood procedure. We study the significance improvement in Higgs to bb with both this method and the simplified method from previous analysis. With either method, we find that using multiple jet radii can provide substantial benefit over a single radius. Another concern we address is that multiple event interpretations might be exploiting similar information to that already present in the standard kinematic variables. By examining correlations between kinematic variables commonly used in LHC analyses and invariant masses obtained with multiple jet reconstructions, we find that using multiple radii is still helpful even on top of standard kinematic variables when combined with boosted decision trees. These results suggest that including multiple event interpretations in a realistic search for Higgs to bb would give additional sensitivity over traditional approaches.
In this note we summarize the status of the standard SANC modules (in the EW and QCD sectors of the Neutral Current branch - version 1.20 and the Charged Current branch - version 1.20). A
We present a high-energy neutrino event generator, called LeptonInjector, alongside an event weighter, called LeptonWeighter. Both are designed for large-volume Cherenkov neutrino telescopes such as IceCube. The neutrino event generator allows for quick and flexible simulation of neutrino events within and around the detector volume, and implements the leading Standard Model neutrino interaction processes relevant for neutrino observatories: neutrino-nucleon deep-inelastic scattering and neutrino-electron annihilation. In this paper, we discuss the event generation algorithm, the weighting algorithm, and the main functions of the publicly available code, with examples.
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