A Jupyter-based Interface Integrated with ROOT for ATLAS Open Data Analysis

The ATLAS Open Data project aims to release real data collected from proton–proton collisions at the LHC to the public. These data can then be used for teaching, outreach, science communication and public engagement, as well as scientific research outside the ATLAS Collaboration. The intended target audience is from high-school students upwards. There has been a previous release of 8 TeV ATLAS Open Data, which succeeded in making particle physics more accessible. The purpose of this work is to improve and build upon the first ATLAS Open Data release, by allowing users to study higher energy 13 TeV collisions. The second release of ATLAS Open Data Project is a set of proton–proton collision data with centre-of-mass energy $ \sqrt{s} = 13$ TeV collected by the ATLAS detector during the year 2016. Associated computing tools are provided to make the analysis of the dataset easily accessible. The general aim of the dataset and tools released is to provide user-friendly and straightforward interactive interfaces to replicate the procedures used by high-energy physics researchers and enable users to experience the analysis of particle physics data in educational environments like university courses or as an extension of the International Particle Physics Masterclasses. This report first summarises the properties of the ATLAS Open Data 13 TeV dataset and the analysis tools. In addition, my summer project focuses on the development of interactive physics analysis tools based on ROOT framework and Jupyter notebooks. Integration of the ROOT data analysis framework with the Jupyter Notebook technology presents the potential of enhancement and expansion of educational and training programs. Two types of notebooks are developed in our work: some analysis examples and the analysis framework interface. The generated analysis structure and tutorials will be used to extend the participation of students from other locations around the World.