Optimizing cut-based algorithms to specific physics acceptance regions

Developments of the new Level-1 Trigger at CMS for the High-Luminosity operation of the LHC are in full swing. The Global Trigger, the final stage of this new Level-1 Trigger pipeline, is foreseen to evaluate a menu of up to 1000 cut-based trigger algorithms. Automating the task of tailoring individual algorithms to specific physics signatures would be a significant time saver while ensuring flexibility to adapt swiftly to evolving run conditions. This task represents a multi-objective optimization problem, where the goal is to strike a balance between the trigger rate and the trigger efficiency of the desired physics region. We present the idea of leveraging an achievement scalarizing function, effectively turning the two objective functions into a scalar function. An iterative approach can then be employed to minimize this function, each iteration slightly modifying the cut parameters in the direction of descent. Exemplary results of using this procedure in targeting a B meson decay to a pair of muons and a Higgs boson decay to a pair of tau leptons are presented.

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Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-10-07
DOI
https://doi.org/10.1051/epjconf/202533701128/pdf
Primary Topic
Particle physics theoretical and experimental studies
Type
article
Field-Weighted Citation Impact
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article

Optimizing cut-based algorithms to specific physics acceptance regions

Benjamin Huber, Gabriele Bortolato, Hannes Sakulin, Elias Leutgeb et al.
Springer Link (Chiba Institute of Technology)
Particle physics theoretical and experimental studies
article

Optimizing cut-based algorithms to specific physics acceptance regions

Benjamin Huber, Gabriele Bortolato, Hannes Sakulin, Elias Leutgeb, Dinyar Rabady
article en

Abstract

Developments of the new Level-1 Trigger at CMS for the High-Luminosity operation of the LHC are in full swing. The Global Trigger, the final stage of this new Level-1 Trigger pipeline, is foreseen to evaluate a menu of up to 1000 cut-based trigger algorithms. Automating the task of tailoring individual algorithms to specific physics signatures would be a significant time saver while ensuring flexibility to adapt swiftly to evolving run conditions. This task represents a multi-objective optimization problem, where the goal is to strike a balance between the trigger rate and the trigger efficiency of the desired physics region. We present the idea of leveraging an achievement scalarizing function, effectively turning the two objective functions into a scalar function. An iterative approach can then be employed to minimize this function, each iteration slightly modifying the cut parameters in the direction of descent. Exemplary results of using this procedure in targeting a B meson decay to a pair of muons and a Higgs boson decay to a pair of tau leptons are presented.

Springer Link (Chiba Institute of Technology)
Openalex Percentile: Top 19%
Particle physics theoretical and experimental studies
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