Speaker
Meril Reboud
(TUM)
Description
EOS is an open-source software for a variety of computational tasks in flavour physics. Its use cases include theory predictions within the Standard Model (SM) of particle physics and beyond, inference of theory parameters from experimental or theoretical likelihoods, and simulation of pseudo events for a number of signal processes. EOS ensures high performance computations through a C++ backend and ease of usability through a Python frontend.
In this interactive tutorial we provide Jupyter Python notebooks that introduce the basic EOS classes and provide examples for each of the three use cases.
Author
Meril Reboud
(TUM)
