Eur. Phys. J. C (2008) 54: 617-644
https://doi.org/10.1140/epjc/s10052-008-0548-z

Regular Article - Theoretical Physics

Measuring supersymmetry

¹ LAPP, IN2P3/CNRS, Université Savoie, 74941, Annecy, France
² SUPA, School of Physics, University of Edinburgh, Edinburgh, EH9 3JZ, Scotland, U.K.
³ LAL, IN2P3/CNRS, Université Paris-Sud, 91898, Orsay, France

^* e-mail: mrauch@ph.ed.ac.uk

Received: 31 October 2007
Revised: 16 January 2008
Published online: 28 February 2008

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 mapping 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.