Python in High Energy Physics
summary
High Energy Physics uses concrete tooling and measurable shifts: the Worldwide LHC Computing Grid handles petabytes and experiments like CMS and ATLAS have ~3,000 collaborators; GitHub-based counts show Python usage overtaking C++ around 2019. Root remains the dominant file/toolkit, with cppyy providing dynamic C++↔Python bindings and uproot implemented in pure Python to avoid ownership issues and already seeing wide adoption. Benchmarks show vectorized NumPy (and Numba) approaching or exceeding ROOT C++ for some tasks. The scikit-hep ecosystem and awkward-array (now with C++ back end) are actively used.
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chapters (24)
- 0:00Intro
- 0:31What is High Energy Physics?
- 1:13The first computers were built for Physics IEM
- 2:49Computing Challenges in HEP today
- 4:33Worldwide LHC Computing Grid
- 5:01Is CPU power a solved problem?
- 5:41Using GPUs to speed up computation IEM
- 6:14Awkward Array
- 6:46Requirements of a language to be used in HEP
- 7:51Early history of Python in HEP
- 10:48How do HEP physicists work with data?
- 11:34What is ROOT?
- 12:50ROOT and Python
- 14:43Alternate implementation of ROOT in Python
- 16:06uproot-Harbinger of Python in HEP?
- 17:39Python is not so slow
- 20:09Why use pybind11?
- 23:04Scikit-HEP-overview of packages
- 23:44Machine Learning
- 24:22Hear from a Physicist
- 25:16Python in other Physics
- 26:00Adoption-existing HEP codebases
- 28:31Concluding Remarks
- 29:29Acknowledgements
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