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arXiv:2309.17309hep-ex

Polyglot Jet Finding

Graeme Andrew Stewart, Philippe Gras, Benedikt Hegner, Atell Krasnopolski

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Abstract

The evaluation of new computing languages for a large community, like HEP, involves comparison of many aspects of the languages' behaviour, ecosystem and interactions with other languages. In this paper we compare a number of languages using a common, yet non-trivial, HEP algorithm: the \akt\ clustering algorithm used for jet finding. We compare specifically the algorithm implemented in Python (pure Python and accelerated with numpy and numba), and Julia, with respect to the reference implementation in C++, from Fastjet. As well as the speed of the implementation we describe the ergonomics of the language for the coder, as well as the efforts required to achieve the best performance, which can directly impact on code readability and sustainability.

arXiv comments
Journal reference
DOI
doi:10.1051/epjconf/202429505017
Subjects
hep-exHigh Energy Physics, Experiment physics.comp-phComputational Physics

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Linked by 1 identifiable commenter in 1 comment across 1 thread, from Feb 2026 to Feb 2026. Found in 1 HN submission from Jan 2026 to Jan 2026. Open submission discussions.

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  1. Show HN: A physically-based GPU ray tracer written in Julia 1 comment

    • Polyglot Jet Finding: https://arxiv.org/abs/2309.17309 This paper in experimental high-energy physics is a good example of why Julia is popular for scientific calculations. It shows that #julialang is over 100 times faster than Python and even faster than C++.

      leephillipsView on HNParent context

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