Metadata-Version: 2.1
Name: EnergyFlow
Version: 0.12.2
Summary: Python package for the Energy Flow suite of particle physics tools
Home-page: https://energyflow.network
Author: Patrick T. Komiske III
Author-email: pkomiske@mit.edu
License: GPL-3.0
Project-URL: Source Code, https://github.com/pkomiske/EnergyFlow
Project-URL: Issues, https://github.com/pkomiske/EnergyFlow/issues
Description: # EnergyFlow
        ![alt-text](https://travis-ci.org/pkomiske/EnergyFlow.svg?branch=master "Travis-CI Build Status")
        [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/pkomiske/EnergyFlow/master)
        
        EnergyFlow is a Python package that computes Energy Flow Polynomials (EFPs) defined in Ref. [1], implements Energy Flow Networks (EFNs) and Particle Flow Networks (PFNs) defined in Ref. [2], and computes Energy Mover's Distances as defined in Ref. [3].
        
        #### Installation
        
        To install EnergyFlow with pip, simply execute:
        ```sh
        pip install energyflow
        ```
        
        #### Documentation
        
        The documentation is maintained at [https://energyflow.network](https://energyflow.network).
        
        ##### References
        
        [1] P. T. Komiske, E. M. Metodiev, and J. Thaler, _Energy Flow Polynomials: A complete linear basis for jet substructure_, _[JHEP __04__ (2018) 013](https://doi.org/10.1007/JHEP04(2018)013)_ [[1712.07124](https://arxiv.org/abs/1712.07124)].
        
        [2] P. T. Komiske, E. M. Metodiev, and J. Thaler, _Energy Flow Networks: Deep Sets for Particle Jets_, _[JHEP __01__ (2019) 121](https://doi.org/10.1007/JHEP01(2019)121)_ [[1810.05165](https://arxiv.org/abs/1810.05165)].
        
        [3] P. T. Komiske, E. M. Metodiev, and J. Thaler, _The Metric Space of Collider Events_, [1902.02346](https://arxiv.org/abs/1902.02346).
Keywords: energy flow,energyflow,physics,jets,correlator,multigraph,polynomial,EFP,EFN,PFN,EMD,Energy Flow Network,Particle Flor Network,Deep Sets,architecture,neural network,metric,collider
Platform: UNKNOWN
Description-Content-Type: text/markdown
Provides-Extra: examples
Provides-Extra: emd
Provides-Extra: generation
