ORIGINAL RESEARCH article
Front. Phys.
Sec. High-Energy and Astroparticle Physics
Volume 13 - 2025 | doi: 10.3389/fphy.2025.1612829
This article is part of the Research TopicPromoting Green Computing in High-Energy Physics and AstrophysicsView all 5 articles
Assessing carbon footprint and performance of the Kalman Filter track fitter in the CBM experiment
Provisionally accepted
- 1Goethe University Frankfurt, Frankfurt, Germany
- 2Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany
- 3Helmholtz Research Academy Hesse, Frankfurt, Germany
- 4GSI Helmholtz Center for Heavy Ion Research, Helmholtz Association of German Research Centres (HZ), Darmstadt, Hesse, Germany
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The CBM experiment at FAIR (GSI, Germany) is one of the most significant upcoming projects in heavy-ion physics. A key feature of the experiment is the high interaction rate, reaching up to 10 7 collisions per second, resulting in the production of substantial volumes of experimental data that must be processed and analyzed in real time. Consequently, the success of the CBM experiment largely depends on the availability of high-performance reconstruction algorithms, particularly track finding, which is the most complex and time-consuming part of particle heavy-ion collision analysis. The tracking algorithm, based on the concepts of the Cellular Automaton (CA) and the use of the Kalman Filter (KF) for fitting, provides the optimal solution to this challenge.The simplicity of the concept and the high degree of internal parallelism make the algorithm extremely efficient in terms of computational resource utilization. In this paper, we examine the fitting algorithm using the KF, evaluating its energy efficiency and environmental impact in the context of computational data processing in heavy-ion physics.
Keywords: Kalman filter, Heavy-ion, CBM experiment, energy efficiency, Carbon Footprint, Parallel Computing, Track fitting
Received: 16 Apr 2025; Accepted: 05 Jun 2025.
Copyright: © 2025 Kozlov and Kisel. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Grigory Kozlov, Goethe University Frankfurt, Frankfurt, Germany
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