Speaker
Description
𝙷𝙴𝙿𝚏𝚒𝚝 is a flexible open-source tool which, given the Standard Model or any of its extensions, allows to i) fit the model parameters to a given set of experimental observables; ii) obtain predictions for observables. 𝙷𝙴𝙿𝚏𝚒𝚝 can be used either in Monte Carlo mode, to perform a Bayesian Markov Chain Monte Carlo analysis of a given model, or as a library, to obtain predictions of observables for a given point in the parameter space of the model, allowing 𝙷𝙴𝙿𝚏𝚒𝚝 to be used in any statistical framework. In the present version, around a thousand observables have been implemented in the Standard Model and in several new physics scenarios. In this talk, I will describe the general structure of the code as well as some of the models and observables implemented, with especial focus on the capabilities for studies within the framework of the dimension-6 SMEFT.
