Speaker
Dr
Remi Lafaye
(LAPP Annecy)
Description
If supersymmetry (or similar complex models) is found at the LHC,
the goal for all colliders over the coming decades will be to extract
its fundamental parameters from the measurements. Dedicated
state-of-the-art tools will be necessary to link a wealth of
measurements to an e.g. 20-dimensional MSSM parameter space.
Starting from a general log-likelihood function of this high-dimensional
parameter space we show how we can find the
best-fit parameter values and determine their errors. Beyond a single
best-fit point we illustrate how distinct secondary minima
occur in complex parameter spaces and how unnatural solutions can be
subsequently distinguished. In cases where there are flat dimensions in
the likelihood we comment on the benefits and limitations of
marginalizing over additional dimensions.
Authors
Dr
Dirk Zerwas
(LAL Orsay)
Dr
Michael Rauch
(University of Edinburgh)
Dr
Remi Lafaye
(LAPP Annecy)
Dr
Tilman Plehn
(University of Edinburgh)
