Framework and software implementation for data-driven trigger efficiency estimation at LHCb using reconstructed candidate properties.
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Reviews precision timing integration in LHC upgrades and discusses a possible shift to triggerless detectors enabled by timing and networking, with reflections on physics benefits.
This paper overviews the LHCb Stripping framework's Python-based architecture, GitLab workflows, automation, and roadmap for processing both legacy and new high-energy physics data.
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A framework and implementation for data-driven trigger efficiency estimation at LHCb
Framework and software implementation for data-driven trigger efficiency estimation at LHCb using reconstructed candidate properties.
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Towards triggerless four-dimensional detectors for High Energy Physics collider experiments
Reviews precision timing integration in LHC upgrades and discusses a possible shift to triggerless detectors enabled by timing and networking, with reflections on physics benefits.
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The LHCb Stripping Project: Sustainable Legacy Data Processing for High-Energy Physics
This paper overviews the LHCb Stripping framework's Python-based architecture, GitLab workflows, automation, and roadmap for processing both legacy and new high-energy physics data.