CERN’s experiments are committed to publishing their data in a form that is accessible to all, both for research purposes and for education. For example, the ATLAS experiment provides Jupyter notebook exercises based on live-analysing reduced forms of the real collider data.
But particle-physics researchers also use simulations of data as a crucial tool for testing theories and for understanding the background processes that new physics effects have to be isolated from. For this we use Monte Carlo (MC) event-generator codes, which are statistical implementations of the fundamental physics theory that sample real-looking events from the predicted particle types and kinematics. These are not yet represented in open-data exercises.
In this project we will develop new tools and exercises for extending open-data analysis resources to include MC event simulations. It will both reduce the entry barriers to outreach with open data and enable more engaging exercises with hypothetical new-physics models.