No abstract

We report on the status of efforts to improve the reinterpretation of searches and measurements at the LHC in terms of models for new physics, in the context of the LHC Reinterpretation Forum. We detail current experimental offerings in direct searches for new particles, measurements, technical implementations and Open Data, and provide a set of recommendations for further improving the presentation of LHC results in order to better enable reinterpretation in the future. We also provide a brief description of existing software reinterpretation frameworks and recent global analyses of new physics that make use of the current data.

The MadAnalysis 5 framework can be used to assess the potential of various LHC analyses for unraveling any specific new physics signal. We present an extension of the LHC reinterpretation capabilities of the programme allowing for the inclusion of theoretical and systematical uncertainties on the signal in the reinterpretation procedure. We have implemented extra methods dedicated to the extrapolation of the impact of a given analysis to higher luminosities, including various options for the treatment of the errors. As an application, we study three classes of new physics models. We first focus on a simplified model in which the Standard Model is supplemented by a gluino and a neutralino. We show that uncertainties could in particular degrade the bounds by several hundreds of GeV when considering 3000/fb of future LHC data. We next investigate another supersymmetry-inspired simplified model, in which the Standard Model is extended by a first generation squark species and a neutralino. We reach similar conclusions. Finally, we study a class of s-channel dark matter setups and compare the expectation for two types of scenarios differing in the details of the implementation of the mediation between the dark and Standard Model sectors.

Searching for heavy vector bosons Z , predicted in models inspired by Grand Unification Theories, is among the challenging objectives of the LHC. The ATLAS and CMS collaborations have looked for Z bosons assuming that they can decay only into Standard Model channels, and have set exclusion limits by investigating dilepton, dijet and, to a smaller extent, top-antitop final states. In this work we explore possible loopholes in these Z searches, by studying supersymmetric as well as leptophobic scenarios. We demonstrate the existence of realizations in which the Z boson automatically evades the typical bounds derived from the analyses of the Drell-Yan invariant-mass spectrum. Dileptonic final states can in contrast only originate from supersymmetric Z decays and are thus accompanied by additional effects. This feature is analyzed in the context of judiciously chosen benchmark configurations, for which visible signals could be expected in future LHC data with a 4σ − 7σ significance. Our results should hence motivate an extension of the current Z search program to account for supersymmetric and leptophobic models.

We introduce a new simplified fast detector simulator in the MadAnalysis 5 platform. The Python-like interpreter of the programme has been augmented by new commands allowing for a detector parametrisation through smearing and efficiency functions. On run time, an associated C++ code is automatically generated and executed to produce reconstructed-level events. In addition, we have extended the MadAnalysis 5 recasting infrastructure to support our detector emulator, and we provide predefined LHC detector configurations. We have compared predictions obtained with our approach to those resulting from the usage of the Delphes 3 software, both for Standard Model processes and a few new physics signals. Results generally agree to a level of about 10% or better, the largest differences in the predictions stemming from the different strategies that are followed to model specific detector effects. Equipped with these new functionalities, MadAnalysis 5 now offers a new user-friendly way to include detector effects when analysing collider events, the simulation of the detector and the analysis being both handled either through a set of intuitive Python commands or directly within the C++ core of the platform.