High Energy Physics is the study of the most fundamental constituents of matter and how these elementary particles interact. Often synonymous to Particle Physics, High Energy Physics seeks to find the secrets of the Universe, one of the recent major discoveries being that of the Higgs Boson that confirmed the Standard Model that dictates how all the forces in the Universe interact with each other. High Energy Physics is probably the physics sub-field that has adopted Python most rapidly, only second to Astrophysics.
The talk starts with a look at how computing has looked like in the field of High Energy Physics in the past and how a lot of physicists played major roles in the development of Computer Science. It then explores the emergence of Python as the language of choice for several physicists and two of the major libraries that have been vital to the adoption of Python in the High Energy Physics community - cppyy and uproot. These are especially important since they demonstrate the different ways one could approach shifting the High Energy Physics community from C++ to Python successfully. The talk will focus on a review of where and how Python is used in the High Energy Physics community and how it is slated to look like in the future.
High Energy Physics has its own python toolkit, scikit-hep which comes with a set of python libraries for use by physicists. The Scikit-HEP project is a community-driven and community-oriented project with the aim of providing Particle Physics at large with an ecosystem for data analysis in Python. It is also about improving the interoperability between High Energy Physics tools and the scientific ecosystem in Python.
This year is ideal for this particular talk, being the year when according to some available data, Python usage trumps C++ usage in several High Energy Physics experiments at CERN - as some physicists have dubbed it, this is the year of Python in High Energy Physics.