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ArborTracking: a tree topology track pattern recognition algorithm

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Abstract

Purpose

The purpose of this work is to develop a novel pattern tracking algorithm to be used on the detectors of the future electron–positron colliders.

Method

ArborTracking, a light-weighted tracking algorithm, has been developed based on the tree topology of track clusters and applied to the baseline detector of the circular electron–positron collider (CEPC). The algorithm collects all the hits in the tracker as a tree (forest), splits the tree branches to form the track segments, and merges the track segments to form the tracks.

Results

Compared with the general track following method, the algorithm has the advantages of low coding complicity and low CPU cost. The performances at different benchmarks are studied. The results are exhaustively listed showing that the method is approaching the limit of the detector. The tracking efficiencies on single muon sample and three-prong sample are both higher than 99%. The transverse momentum resolution reaches 0.1% level and the boson mass resolution reaches 4.7 GeV/c.

Conclusions

The performances are similar with those of the baseline tracking algorithm of CEPC, and the physics requirement of CEPC is satisfied. The new tree pattern recognition algorithm is a necessary part in the CEPC software. And it is also a competitive algorithm on the market, which can be chosen by the future experiments.

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Change history

  • 01 October 2020

    In the original publication the copyright text below the ���Introduction��� section is incorrectly published.

References

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Acknowledgements

This work is supported by the Continuous Basic Scientific Research Project (No. WDJC-2019-16), National Key Research and Development Project (2018YFE0104800, 2016YFE0100900, 2016YFA0400300), and National Natural Science Foundation of China (11775313).

Author information

Authors and Affiliations

  1. Science and Technology on Nuclear Data Laboratory, China Institute of Atomic Energy, Beijing, 102413, China

    Mingrui Zhao, Shouyang Hu, Jing Zhou, Yuliang Yan, Lei Chen, Wendi Liu, Peiyu Li, Shihai Jia, Yunyu Zhang & Xiaomei Li

  2. Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, 100049, China

    Manqi Ruan

Authors
  1. Mingrui Zhao
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  2. Manqi Ruan
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  3. Shouyang Hu
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  4. Jing Zhou
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  5. Yuliang Yan
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  6. Lei Chen
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  7. Wendi Liu
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  8. Peiyu Li
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  9. Shihai Jia
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  10. Yunyu Zhang
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  11. Xiaomei Li
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Corresponding author

Correspondence to Mingrui Zhao.

Additional information

\(\scriptstyle \copyright \)2013 Chinese Physical Society and the Institute of High Energy Physics of the Chinese Academy of Sciences and the Institute of Modern Physics of the Chinese Academy of Sciences and IOP Publishing Ltd.

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Cite this article

Zhao, M., Ruan, M., Hu, S. et al. ArborTracking: a tree topology track pattern recognition algorithm. Radiat Detect Technol Methods 4, 377–382 (2020). https://doi.org/10.1007/s41605-020-00194-w

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  • DOI: https://doi.org/10.1007/s41605-020-00194-w

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