15–19 Feb 2021
CERN
Europe/Paris timezone

Session

Tutorials and hands-ons

16 Feb 2021, 10:00
virtual (online only) (CERN)

virtual (online only)

CERN

Presentation materials

There are no materials yet.

  1. Jan Heisig (Université catholique de Louvain (UCL)), Jan Heisig (RWTH Aachen University), Andre Lessa (CCNH - Univ. Federal do ABC)
    16/02/2021, 11:00

    An introduction to the SModelS functionalities with a variety of hands-on examples and extensive Q&A.

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  2. Ilaria Brivio (University of Heidelberg)
    17/02/2021, 10:00

    SMEFTsim is a package containing model files for calculations in the Standard Model Effective Field Theory. It can be interfaced to Mathematics via FeynRules and to Monte Carlo event generators.
    This tutorial will present the main features of SMEFTsin and give a practical example of usage in Madgraph5.

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  3. Mr Grégoire Uhlrich
    17/02/2021, 11:00

    MARTY is a C++ computer algebra system specialized for High Energy Physics that can calculate amplitudes, squared amplitudes and Wilson coefficients in a large variety of Beyond the Standard Model (BSM) scenarios up to the one-loop order. It is fully independent of any other framework and its main development guideline is generality, in order to be adapted easily to any type of model. The...

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  4. Mangesh Sonawane (Austrian Academy of Sciences (AT)), Jong Soo Kim
    18/02/2021, 10:00

    This tutorial will guide you through some practical examples to learn how CheckMATE works. In addition to CheckMATE, we will also run some other tools that are useful for collider phenomenology.

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  5. Jack Araz (IPPP - Durham University)
    18/02/2021, 11:00

    A brief tutorial on recasting capabilities of MadAnalysis 5 with an extended Q&A session.

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  6. Kyle Stuart Cranmer (New York University (US))
    18/02/2021, 15:30

    I will review the MadMiner tool, which implements approaches to approximate the fully differential likelihood (or likelihood ratio) including showering and detector effects with machine learning. The techniques are described in three publications “Constraining Effective Field Theories With Machine Learning”, “A Guide to Constraining Effective Field Theories With Machine Learning”, and “Mining...

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  7. Matthew Feickert (Univ. Illinois at Urbana Champaign (US)), Lukas Alexander Heinrich (CERN), Giordon Holtsberg Stark (University of California,Santa Cruz (US))
    18/02/2021, 16:30

    The HistFactory p.d.f. template [CERN-OPEN-2012-016][1] is per-se independent of its implementation in ROOT and sometimes, it’s useful to be able to run statistical analysis outside of ROOT, RooFit, RooStats framework. This tutorial will introduce users (who are generally familiar with hypothesis testing) to the [pyhf][2] python package. Examples using public [HEPData][3] material will be...

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  8. Martin Habedank (Humboldt University of Berlin (DE)), Jonathan Butterworth (UCL)
    19/02/2021, 10:00
  9. Gokhan Unel (University of California Irvine (US))

    The possibility for a complete and unified Analysis Description Language (ADL) has recently been widely discussed in the HEP community. Such a language allows both quick analysis design and easy reinterpretation studies. A runtime interpreted version of the language, born from the unification of the early work, known as LHADA and CutLang, is presently available under the name CutLang V2.
    We...

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