Metadata-Version: 2.1
Name: smelli
Version: 2.2.0
Summary: A Python package providing a global likelihood function in the space of dimension-6 Wilson coefficients of the Standard Model Effective Field Theory (SMEFT)
Home-page: UNKNOWN
Author: Jason Aebischer <jason.aebischer@tum.de>, Jacky Kumar <jacky.kumar@umontreal.ca>, Peter Stangl <peter.stangl@lapth.cnrs.fr>, David M. Straub <david.straub@tum.de>
License: MIT
Description: <a href="https://travis-ci.org/smelli/smelli">![Build Status](https://travis-ci.org/smelli/smelli.svg?branch=master)</a> [![Coverage Status](https://coveralls.io/repos/github/smelli/smelli/badge.svg)](https://coveralls.io/github/smelli/smelli)
        
        # smelli – a global likelihood for precision constraints
        
        `smelli` is a Python package providing a global likelihood function in the
        space of dimension-six Wilson coefficients in the Standard Model Effective
        Field Theory (SMEFT). The likelihood includes contributions from
        quark and lepton flavour physics, electroweak precision tests, and other
        precision observables.
        
        The package is based on [flavio](https://github.com/flav-io/flavio) for the
        calculation of observables and statistical treatment and
        [wilson](https://github.com/wilson-eft/wilson) for the running, translation,
        and matching of Wilson coefficients.
        
        ## Installation
        
        The package requires Python version 3.6 or above. It can be installed with
        
        ```bash
        python3 -m pip install smelli --user
        ```
        
        
        ## Documentation
        
        A brief user manual can be found in the paper cited below.
        
        ## Citation
        
        If you use `smelli` in a scientific publication, please cite
        
        >  J. Aebischer, J. Kumar, P. Stangl, and D. M. Straub
        >
        > "A Global Likelihood for Precision Constraints and Flavour Anomalies"
        >
        >  [arXiv:1810.07698 [hep-ph]](https://arxiv.org/abs/1810.07698)
        
        Please also cite the publications on [flavio](https://arxiv.org/abs/1810.08132) and [wilson](https://arxiv.org/abs/1804.05033), which are the pillars `smelli` is  built on.
        
        ## Bugs and feature requests
        
        Please submit bugs and feature requests using
        [Github's issue system](https://github.com/smelli/smelli/issues).
        
        ## Contributing
        
        The aim of the package is to provide a likelihood in the
        space of dimension-6 SMEFT Wilson coefficients using all
        relevant available experimental measurements. If you want
        to contribute additional observables, the easiest way is
        to implement the observable in [flavio](https://github.com/flav-io/flavio). Observables
        implemented there can be added to the likelihood simply
        by adding a corresponding entry in one of the
        [observable YAML files](https://github.com/smelli/smelli/tree/master/smelli/data/yaml).
        
        Alternatively, also observables computed in any other standalone Python package can be incorporated in principle as long as it adheres to the [WCxf standard](https://wcxf.github.io).
        If you want to follow this route, please open an [issue](https://github.com/smelli/smelli/issues) to start the discussion on how to integrate it.
        
        ## Contributors
        
        In alphabetical order:
        
        - Jason Aebischer
        - Matthew Kirk
        - Jacky Kumar
        - Peter Stangl
        - David M. Straub
        
        ## License
        
        smelli is released under the MIT license.
        
Platform: UNKNOWN
Description-Content-Type: text/markdown
Provides-Extra: testing
