12–15 Dec 2022
CERN
Europe/Paris timezone

Session

Experience and feedback using reinterpretation material

12 Dec 2022, 14:55
4/3-006 - TH Conference Room (CERN)

4/3-006 - TH Conference Room

CERN

110
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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

Presentation materials

There are no materials yet.

  1. Jack Y. Araz (IPPP - Durham University)
    12/12/2022, 14:55

    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'...

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  2. Iñaki Lara Perez
    12/12/2022, 15:15

    The use of the combination of information from independent signal regions in statistical tests in high energy physics gives stronger and more robust limits that single-binned analysis. We present the implementation of multi-binned analysis in CheckMATE based on a PYHF implementation of simplified likelihoods. This methods turns out to be superior to the usual limits calculated by CheckMATE...

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  3. Wolfgang Waltenberger (Austrian Academy of Sciences (AT))
    12/12/2022, 15:35

    We report on new developments in SModelS, in particular the functionality of analyses combination introduced in v2.2.

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  4. Sabine Kraml (LPSC Grenoble)
    12/12/2022, 16:30
  5. Dan Guest (Humboldt University of Berlin (DE))
    12/12/2022, 16:40
  6. Tomasz Procter (University of Glasgow (GB))
    12/12/2022, 17:00

    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,...

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  7. Krzysztof Rolbiecki (Warsaw University)
    12/12/2022, 17:20

    I will discuss a recent CheckMATE implementation of ATLAS searches using MVA/BDT and NN methods.

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  8. Jennifer Ngadiuba (FNAL)
    12/12/2022, 17:40
  9. All
    12/12/2022, 17:55

    Discussion of technical and conceptual questions around the publication and reuse of ML models for recasting. Time is indicative.

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  10. Ilaria Brivio (University of Zurich)
    14/12/2022, 10:00
  11. Jaco ter Hoeve
    14/12/2022, 10:25

    Theoretical interpretations of particle physics data, such as the determination of the Wilson coefficients of the Standard Model Effective Field Theory (SMEFT), often involve the inference of multiple parameters from a global dataset. Optimizing such interpretations requires the identification of observables that exhibit the highest possible sensitivity to the underlying theory parameters. In...

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  12. Tilman Plehn
    14/12/2022, 10:45
  13. Tomasz Procter (University of Glasgow (GB))
    14/12/2022, 11:05

    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 --...

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  14. James David Yellen (University of Glasgow (GB))
    14/12/2022, 11:25

    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...

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  15. Iñaki Lara Perez (Warsaw University)
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