Metapackage of Scikit-HEP project data analysis packages for Particle Physics.
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Updated
Nov 24, 2025 - Python
Metapackage of Scikit-HEP project data analysis packages for Particle Physics.
Package to deal with particles, the PDG particle data table, PDGIDs, etc.
A Deep learning library for neutrino telescopes
A Python package for flavour physics phenomenology in the Standard model and beyond
Error propagation and statistical analysis for Monte Carlo simulations in lattice QCD and statistical mechanics using autograd.
Lightweight Python interface to read Les Houches Event (LHE) files
Repository of Baler, a machine learning based data compression tool
An open-source machine learning framework for global analyses of parton distributions.
Partial Wave Analysis using TensorFlow.
A simple wrapper of ENTERPRISE and ceffyl that allows for new-physics searches in PTA data.
Jet-finding in the Scikit-HEP ecosystem.
Code to compute exact two- and three-neutrino oscillation probabilities using SU(2) and SU(3) expansions
Classification of Higgs boson decays using machine learning. Project for the "Tandem Project" activity at Master degree in Physics.
Pure python statistic tools for high energy physics.
Automating Monte Carlo simulation on hardware accelerators.
Unsupervised anomaly detection in the latent space of high energy physics events with quantum machine learning.
A jet grooming algorithm based on reinforcement learning.
Blender Addon to Bake Particles as Keyframed Objects
PyR@TE 3
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