EnergyFlow

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EnergyFlow is a Python package that computes Energy Flow Polynomials (EFPs) as defined in Ref. [1], implements Energy Flow Networks (EFNs) and Particle Flow Networks (PFNs) as defined in Ref. [2], computes Energy Mover's Distances as defined in Ref. [3], and provides access to some particle physics datasets hosted on Zenodo including the jet datasets in MOD HDF5 format used in Ref. [4].

Installation

To install EnergyFlow with pip, simply execute:

python -m pip install energyflow

Documentation

The documentation is maintained at 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 [1712.07124].

[2] P. T. Komiske, E. M. Metodiev, and J. Thaler, Energy Flow Networks: Deep Sets for Particle Jets, JHEP 01 (2019) 121 [1810.05165].

[3] P. T. Komiske, E. M. Metodiev, and J. Thaler, The Metric Space of Collider Events, Phys. Rev. Lett. 123 (2019) 041801 [1902.02346].

[4] P. T. Komiske, R. Mastandrea, E. M. Metodiev, P. Naik, and J. Thaler, Exploring the Space of Jets with CMS Open Data, Phys. Rev. D 101 (2020) 034009 [1908.08542].

[5] P. T. Komiske, E. M. Metodiev, and J. Thaler, Cutting Multiparticle Correlators Down to Size, Phys. Rev. D 101 (2020) 036019 [1911.04491].

[6] A. Andreassen, P. T. Komiske, E. M. Metodiev, B. Nachman, and J. Thaler, OmniFold: A Method to Simultaneously Unfold All Observables, Phys. Rev. Lett. 124 (2020) 182001 [1911.09107].

[7] P. T. Komiske, E. M. Metodiev, and J. Thaler, The Hidden Geometry of Particle Collisions, JHEP 07 (2020) 006 [2004.04159].

Project links

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Credits

Author: Patrick T. Komiske III

Maintainer: Rikab Gambhir

GitHub Statistics

Data verified by PyPI on Nov 1, 2024
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

GNU General Public License v3 (GPLv3)

Requires

Python >=3.9

Provides Extra

all archs examples generation tests

Tags

CMS Deep Sets EFM EFN EFP EMD Earth Mover Distance Energy Flow Moment Energy Flow Network Energy Flow Polynomial MOD Open Data PFN Particle Flow Network Wasserstein architecture collider correlator energy flow energyflow jets metric multigraph neural network open physics polynomial substructure

Classifiers

Report project as malware

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