Experiments with using quantum machine learning algorithms to solve Higgs boson tagging problems in particle physics.
This project uses pipenv to manage dependencies. Install pipenv, and then run source install.sh once (note: due to an error in numpythia, if installation hangs, enter CTRL+C to continue). On each subsequent new session, instead run source setup.sh.
The samples represent a binary classification problem. The two classes are 'higgs' and 'qcd', representing jets from either a Higgs decay or QCD background. The feature set is kinematic data from the jet (specifically: pt, eta, phi, mass, ee2, ee3, and d2 (see energy correlators for more information on these last few variables)).