Algorithm for Enhancing Event Reconstruction Efficiency by Addressing False Track Filtering Issues in the SPD NICA Experiment
Amirkhanova G. Mansurova M. Ososkov G. Burtebayev N. Shomanov A. Kunelbayev M.
July 2023Multidisciplinary Digital Publishing Institute (MDPI)
Algorithms
2023#16Issue 7
This paper introduces methods for parallelizing the algorithm to enhance the efficiency of event recovery in Spin Physics Detector (SPD) experiments at the Nuclotron-based Ion Collider Facility (NICA). The problem of eliminating false tracks during the particle trajectory detection process remains a crucial challenge in overcoming performance bottlenecks in processing collider data generated in high volumes and at a fast pace. In this paper, we propose and show fast parallel false track elimination methods based on the introduced criterion of a clustering-based thresholding approach with a chi-squared quality-of-fit metric. The proposed strategy achieves a good trade-off between the effectiveness of track reconstruction and the pace of execution on today’s advanced multicore computers. To facilitate this, a quality benchmark for reconstruction is established, using the root mean square (rms) error of spiral and polynomial fitting for the datasets identified as the subsequent track candidate by the neural network. Choosing the right benchmark enables us to maintain the recall and precision indicators of the neural network track recognition performance at a level that is satisfactory to physicists, even though these metrics will inevitably decline as the data noise increases. Moreover, it has been possible to improve the processing speed of the complete program pipeline by 6 times through parallelization of the algorithm, achieving a rate of 2000 events per second, even when handling extremely noisy input data.
algorithm , neural network tracking , paralleling methods , SPD NICA experiment , track reconstruction
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Institute of Nuclear Physics, 1 Ibragimov Str, Almaty, 050032, Kazakhstan
School of Information Technology, Al-Farabi Kazakh National University, 71 Al-Farabi Ave, Almaty, 050040, Kazakhstan
Joint Institute for Nuclear Research, Joliot-Courie Str. 6, Moscow Region, Dubna, 141980, Russian Federation
School of Engineering and Digital Sciences, Nazarbayev University, Kabanbay Batyr Ave. 53, Astana, 010000, Kazakhstan
Institute of Information and Computational Technologies, Pushkina 125, Almaty, 050060, Kazakhstan
Institute of Nuclear Physics
School of Information Technology
Joint Institute for Nuclear Research
School of Engineering and Digital Sciences
Institute of Information and Computational Technologies
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