A Deep learning library for neutrino telescopes
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Updated
May 17, 2024 - Python
A Deep learning library for neutrino telescopes
Quantum Transformers for High Energy Physics Analysis at the Large Hadron Collider
pure-Python HistFactory implementation with tensors and autodiff
ATLAS Run 2 and Run 3 analysis framework for AnalysisTop and AnalysisBase for proton-smashing physics
Jet-finding in the Scikit-HEP ecosystem.
Calculate diffractive vector meson production at high energy
Monte Carlo-based data analysis
PineAPPL + EKO ─➤ fast theories
Pages defining the website of the Scikit-HEP project.
Package to deal with particles, the PDG particle data table, PDGIDs, etc.
Metapackage of Scikit-HEP project data analysis packages for Particle Physics.
Package to parse decay files, describe and convert particle decays between digital representations.
A package for event file analysis and recasting of LHC results
Model manipulation and fitting library based on TensorFlow and optimised for simple and direct manipulation of probability density functions. Its main focus is on scalability, parallelisation and user friendly experience.
A comprehensive programming environment designed to facilitate research and development at the intersection of high-energy physics and machine learning.
Geant4 toolkit for the simulation of the passage of particles through matter - NIM A 506 (2003) 250-303
A project which aims to abstract the analysis pipeline of a Particle Physics Analysis at ATLAS. This repository is a shared effort of University of Sydney, Duke and DESY.
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