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arXiv · 2509.05294

The LHCb Stripping Project: Sustainable Legacy Data Processing for High-Energy Physics

Nathan Grieser·Eduardo Rodrigues·Niladri Sahoo·Shuqi Sheng·Nicole Skidmore·Mark Smith
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Abstract

The LHCb Stripping project is a pivotal component of the experiment's data processing framework, designed to refine vast volumes of collision data into manageable samples for offline analysis. It ensures the re-analysis of Runs 1 and 2 legacy data, maintains the software stack, and executes (re-)Stripping campaigns. As the focus shifts toward newer data sets, the project continues to optimize infrastructure for both legacy and live data processing. This paper provides a comprehensive overview of the Stripping framework, detailing its Python-configurable architecture, integration with LHCb computing systems, and large-scale campaign management. We highlight organizational advancements such as GitLab-based workflows, continuous integration, automation, and parallelized processing, alongside computational challenges. Finally, we discuss lessons learned and outline a future road-map to sustain efficient access to valuable physics legacy data sets for the LHCb collaboration.

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Nathan Grieser, Eduardo Rodrigues, Niladri Sahoo, Shuqi Sheng, Nicole Skidmore, Mark Smith. 2025-09-05. The LHCb Stripping Project: Sustainable Legacy Data Processing for High-Energy Physics. https://doi.org/10.1007/s41781-025-00151-6

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