Pileup and Underlying Event Mitigation with Iterative Constituent Subtraction

Abstract

The hard-scatter processes in hadronic collisions are often largely contaminated with soft background coming from pileup in proton-proton collisions, or underlying event in heavy-ion collisions. This paper presents a new background subtraction method for jets and event observables (such as missing transverse energy) which is based on the previously published Constituent Subtraction algorithm. The new subtraction method, called Iterative Constituent Subtraction, applies event-wide implementation of Constituent Subtraction iteratively in order to fully equilibrate the background subtraction across the entire event. Besides documenting the new method, we provide guidelines for setting the free parameters of the subtraction algorithm. Using particle-level simulation, we provide a comparison of Iterative Constituent Subtraction with several existing methods from which we conclude that the new method has a significant potential to improve the background mitigation in both proton-proton and heavy-ion collisions.

References in corpus (19)

• PYTHIA 6.4 Physics and Manual
• Jet substructure as a new Higgs search channel at the LHC
• Particle-flow reconstruction and global event description with the CMS detector
• Pileup subtraction using jet areas
• The Catchment Area of Jets
• Jet substructure as a new Higgs search channel at the LHC
• Pileup Per Particle Identification
• Neutralino Dark Matter at 14 and 100 TeV
• Pileup subtraction for jet shapes
• Identification techniques for highly boosted W bosons that decay into hadrons
• Pileup Mitigation with Machine Learning (PUMML)
• Particle-level pileup subtraction for jets and jet shapes
• Neutralinos in Vector Boson Fusion at High Energy Colliders
• Identifying boosted new physics with non-isolated leptons
• Jet grooming through reinforcement learning
• On the use of charged-track information to subtract neutral pileup
• Substructure dependence of jet cross sections at HERA and determination of alpha_s
• A background estimator for jet studies in p+p and A+A collisions
• Measurements of the jet internal sub-structure and its relevance to parton shower evolution in p+p and Au+Au collisions at STAR

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• Dead-cone searches in heavy-ion collisions using the jet tree
• Solving Key Challenges in Collider Physics with Foundation Models
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• Accuracy versus precision in boosted top tagging with the ATLAS detector
• Measurement of inclusive and leading subjet fragmentation in pp and Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV
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• Deep learning for jet modification in the presence of the QGP background
• Apples to Apples in Jet Quenching: robustness of Machine Learning classification of quenched jets to Underlying Event contamination
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