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Measuring supersymmetry

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Abstract

If new physics is found at the LHC (and the ILC) the reconstruction of the underlying theory should not be biased by assumptions about high-scale models. For the map** of many measurements onto high-dimensional parameter spaces we introduce SFitter with its new weighted Markov chain technique. SFitter constructs an exclusive likelihood map, determines the best-fitting parameter point and produces a ranked list of the most likely parameter points. Using the example of the TeV-scale supersymmetric Lagrangian we show how a high-dimensional likelihood map will generally include degeneracies and strong correlations. SFitter allows us to study such model-parameter spaces employing Bayesian as well as frequentist constructions. We illustrate in detail how it should be possible to analyze high-dimensional new-physics parameter spaces like the TeV-scale MSSM at the LHC. A combination of LHC and ILC measurements might well be able to completely cover highly complex TeV-scale parameter spaces.

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Authors and Affiliations

  1. LAPP, IN2P3/CNRS, Université Savoie, 74941, Annecy, France

    R. Lafaye

  2. SUPA, School of Physics, University of Edinburgh, Edinburgh, EH9 3JZ, Scotland, U.K.

    T. Plehn & M. Rauch

  3. LAL, IN2P3/CNRS, Université Paris-Sud, 91898, Orsay, France

    D. Zerwas

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  1. R. Lafaye
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Correspondence to M. Rauch.

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Lafaye, R., Plehn, T., Rauch, M. et al. Measuring supersymmetry. Eur. Phys. J. C 54, 617–644 (2008). https://doi.org/10.1140/epjc/s10052-008-0548-z

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