hep is the mono repository holding all of go-hep.org/x/hep packages and tools
High Energy Physics (HEP) autoencoder for CERN ATLAs to compress hadron jet event data from 4 to 3 variables
High energy physics, python-based, neural-network framework
EQST-GP stands for Extended Quantum String Theory with Gluon Plasma It is a unified theory that aims to describe all the fundamental forces in the universe (gravity, electromagnetism, strong nuclear, and weak nuclear) within a single framework. Numerical codes/ datasets generated during this study Code as an interactive extension active simulation
UArizona Honors Thesis project: ttbar background estimation analysis for the ATLAS experiment. Tucson, AZ
A deep neural network for tagging triplets of jets from hadronic top decay.
Higgs to two tau lepton analysis based on NanoAOD-like samples from the CERN Open Data portal. Used as a simple payload in our hsf-training-cicd module.
CERN analysis of Multi Anode PMTs
Analysis of radiation data to classify particles from space
Webpage for github.com/hsf-training/hsf-training-cms-analysis
Signal Optimization of Leptoquark, CMS-CERN
This repository contains analysis work using CutLang on ATLAS 13 TeV Open Data. It includes BSM physics studies, custom analysis definitions, documentation, and visualization tools for exploring particle physics datasets.
🌌 Unify fundamental forces with EQST-GP, a theory integrating quantum string concepts and gluon plasma to explain dark matter and energy.
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