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A Common Tracking Software Project

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arxiv 2106.13593 v1 pith:E2PIAAHE submitted 2021-06-25 physics.ins-det hep-ex

Xiaocong Ai , Corentin Allaire , Noemi Calace , Angéla Czirkos , Irina Ene , Markus Elsing , Ralf Farkas , Louis-Guillaume Gagnon
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Rocky Garg Paul Gessinger Hadrien Grasland Heather M. Gray Christian Gumpert Julia Hrdinka Benjamin Huth Moritz Kiehn Fabian Klimpel Attila Krasznahorkay Robert Langenberg Charles Leggett Joana Niermann Joseph D. Osborn Andreas Salzburger Bastian Schlag Lauren Tompkins Tomohiro Yamazaki Beomki Yeo Jin Zhang Georgiana Mania Bernadette Kolbinger Edward Moyse David Rousseau
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classification physics.ins-dethep-ex
keywords reconstructiontrackalgorithmsactscommonexperimentssoftwarecomputational
verification ladder T0 review T1 audit T2 compute T3 formal
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The reconstruction of the trajectories of charged particles, or track reconstruction, is a key computational challenge for particle and nuclear physics experiments. While the tuning of track reconstruction algorithms can depend strongly on details of the detector geometry, the algorithms currently in use by experiments share many common features. At the same time, the intense environment of the High-Luminosity LHC accelerator and other future experiments is expected to put even greater computational stress on track reconstruction software, motivating the development of more performant algorithms. We present here A Common Tracking Software (ACTS) toolkit, which draws on the experience with track reconstruction algorithms in the ATLAS experiment and presents them in an experiment-independent and framework-independent toolkit. It provides a set of high-level track reconstruction tools which are agnostic to the details of the detection technologies and magnetic field configuration and tested for strict thread-safety to support multi-threaded event processing. We discuss the conceptual design and technical implementation of ACTS, selected applications and performance of ACTS, and the lessons learned.

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Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. An eightfold equivalence-preserving speedup of the JUNO OMILREC vertex and energy reconstruction

    physics.ins-det 2026-08 conditional novelty 6.0 of 10

    Staged equivalence-preserving optimizations cut JUNO's OMILREC reconstruction time from 1524.8 to 189.2 ms/event (8.06x) on an Intel Xeon, with numerical drift below 1.3e-14.

  2. GPT-like transformer model for silicon tracking detector simulation

    physics.ins-det 2025-12 conditional novelty 6.0 of 10

    A decoder-only transformer trained on tokenized Geant4 hit sequences generates silicon tracker hits that reconstruct to near-Geant4-quality tracks for single muons.

  3. MAIA: A new detector concept for a 10 TeV muon collider

    physics.ins-det 2025-01 conditional novelty 5.0 of 10

    The MAIA detector concept for a 10 TeV muon collider achieves over 95% reconstruction efficiency for energetic tracks, photons, and neutrons in the central region under simulated beam-induced background.

  4. Track reconstruction as a service for collider physics

    physics.ins-det 2025-01 conditional novelty 4.0 of 10

    Running the Patatrack and Exa.TrkX tracking algorithms through NVIDIA Triton as a remote service gives near-local GPU throughput while letting one GPU serve many more CPU clients.

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