Speaker
Ayan Paul
(INFN, Sezione di Roma)
Description
With new data, and hopes for observation of new physics, well on the way with the LHC Run II it is necessary to have computational tools at hand that will link experimental observables to model parameters through a global fit done within a rigorous statistical framework. We present SusyFit, a Markov Chain Monte Carlo based Bayesian Analysis tool that can perform global fits with electroweak precision data, flavour observables and Higgs observables to build constraints on model parameters. Built in a modular structure for easy user customization, the code comes with the SM, SUSY, THDM, Dimension 6 basis for Higgs Physics and other models implemented both at the model and observable levels. The code is paralellized and can easily be deployed both on multicore personal computers and on clusters. SusyFit is built up as a common platform for the use by both theorist and experimentalists keeping an eye on statistical rigour, a large and varied physics menu and highly flexible end user customizability.
Primary author
Ayan Paul
(INFN, Sezione di Roma)
Co-author
. SusyFit
(Susyfit Collaboration)
