Conveners
Experience and feedback using reinterpretation material: News from recasting tools
- Marie-Helene Genest (LPSC-Grenoble, CNRS/UGA (FR))
Experience and feedback using reinterpretation material: publication and reuse of ML models
- Sabine Kraml (LPSC Grenoble)
Experience and feedback using reinterpretation material: focus on combinations and global fits
- Are Raklev
MadAnalysis 5 is a framework for phenomenological investigations at particle colliders. Based on a C++ kernel, this program allows to efficiently perform, in a straightforward and user-friendly fashion, sophisticated physics analyses of event files such as those generated by a large class of Monte Carlo (MC) event generators. This talk will focus on recent developments in MadAnalysis'...
We report on new developments in SModelS, in particular the functionality of analyses combination introduced in v2.2.
I present the lessons learned as re-interpreters trying to reuse analyses centred on neural networks in the RIVET framework, using two recent ATLAS analyses -- SUSY and Exotics searches -- as examples. I survey the possible ways that an analysis team can preserve and publicise their neural network for future use, and provide a detailed examination of the ONNX and lwtnn preservation tools,...
I will discuss a recent CheckMATE implementation of ATLAS searches using MVA/BDT and NN methods.
Discussion of technical and conceptual questions around the publication and reuse of ML models for recasting. Time is indicative.
Using GAMBIT, we show that present collider data is not only consistent with low-scale supersymmetry, but permits scenarios where the masses of all six neutralinos and charginos of the MSSM are well below a TeV. We constrain the $\tilde G$-EWMSSM -- the MSSM with an eV-scale gravitino as the lightest supersymmetric particle and the six electroweakinos as the only other light new states --...
The combination of LHC results is of great relevance if we want to obtain a deeper more comprehensive understanding of the data collected by the experiments. In practice, it would allow us to derive stronger limits on Beyond Standard Model (BSM) theories, and to perform searches for dispersed signals, as well searching for deviations from the Standard Model in the observed data. However, the...
