Minuit is a program implementing a function minimisation algorithm written at CERN more than 50 years ago. It is still used by almost all statistical analysis in High Energy Physics to find optimal likelihood and best parameter values. A new version, Minuit2, has been re-implemented the original algorithm in C++ a few years ago and it is provided as a ROOT library or a standalone C++ module. It is also available as a Python package, IMinuit.
This new version has been recently improved by adding some new features. These include support for external gradients and hessian, allowing the use of Automatic Differentiation techniques or parallel computation of the gradients and the addition of new minimisation algorithms such as BFGS and Fumili. We will present an overview of the new implementation showing the new added features and we will as well present a comparison with other existing minimisation packages, available in C++ or in the Python scientific ecosystem.
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