Higgs boson tagging with the Lund jet plane

Khosa, Charanjit K.; Marzani, Simone

doi:10.48550/arxiv.2105.03989

Cited by 3 publications

(3 citation statements)

References 59 publications

(76 reference statements)

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“…The H → b b decay has remained an interesting and widely studied benchmark case, especially for machine learning discrimination studies (see, e.g., Refs. [376,377,378,379,380,381,382,383,384,385,386]). The dominant background to this decay at high energies relevant for jet substructure is the splitting of an off-shell gluon to bottom quarks, g → b b.…”

Section: Second Example: H → B B Identification and Irc Safe Binary D...mentioning

confidence: 99%

Jet substructure at the Large Hadron Collider: A review of recent advances in theory and machine learning

2020

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Section: Second Example: H → B B Identification and Irc Safe Binary D...mentioning

confidence: 99%

Jet substructure at the Large Hadron Collider: A review of recent advances in theory and machine learning

2020

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“…Fortunately, in the last years there has been tremendous progress on quark-gluon tagging studies exploiting jet substructure properties with machine learning techniques [41]. The latest LHC results reach ε g ≈ 60% gluon efficiencies with ε mistag q→g ≈ 10% false positive rates using advanced multivariate analyses [42,43], or ε mistag q→g ≈ 7% [44] further exploiting Lund jet plane information [45]. Reaching mistagging rates down to ε mistag q→g ≈ 1%, while keeping large gluon reconstruction efficiencies, appears feasible in the clean and kinematically constrained QCD environment of future e + e − machines, in particular taking advantage of the very large samples of Z → qq(g) events at the Z pole, and the O(10 5 ) H → gg events collected during the e + e − → ZH runs, available for dedicated studies of the different colour, radiation, spin, charge, hadronization properties of quark and gluon jets [46,47,48].…”

Section: Event Reconstruction and Preselectionmentioning

confidence: 99%

Measuring the electron Yukawa coupling via resonant s-channel Higgs production at FCC-ee

d'Enterria,

Poldaru,

Wojcik

2021

Preprint

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The Future Circular Collider (FCC-ee) offers the unique opportunity of studying the Higgs Yukawa coupling to the electron, y e , via resonant s-channel production, e + e − → H, in a dedicated run at √ s = m H . The signature for direct Higgs production is a small rise in the cross sections for particular final states, consistent with Higgs decays, over the expectations for their occurrence due to Standard Model (SM) background processes involving Z * , γ * , or t-channel exchanges alone. Performing such a measurement is remarkably challenging for four main reasons. First, the low value of the e ± mass leads to a tiny y e coupling, and correspondingly small cross section: σ ee→H ∝ m 2 e = 0.57 fb accounting for initial-state γ radiation. Second, the e + e − beams must be monochromatized such that the spread of their center-ofmass (c.m.) energy is commensurate with the narrow width of the SM Higgs boson, Γ H = 4.1 MeV, while keeping large beam luminosities. Third, the Higgs mass must also be known beforehand with a few-MeV accuracy in order to operate the collider at the resonance peak, √ s = m H . Last but not least, the cross sections of the background processes are many orders-of-magnitude larger than those of the Higgs decay signals. A preliminary generator-level study of 11 Higgs decay channels using a multivariate analysis, which exploits boosted decision trees to discriminate signal and background events, identifies two final states as the most promising ones in terms of statistical significance: H → gg and H → WW * → ν + 2 jets. For a benchmark monochromatization with 4.1-MeV c.m. energy spread (leading to σ ee→H = 0.28 fb) and 10 ab −1 of integrated luminosity, a 1.3σ signal significance can be reached, corresponding to an upper limit on the e ± Yukawa coupling at 1.6 times the SM value: |y e | < 1.6|y sm e | at 95% confidence level, per FCC-ee interaction point per year. Directions for future improvements of the study are outlined.

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“…Idea of using ML for jet tagging using low-level raw information (jet images) has been suggested a couple of years ago. We consider Lund jet images and Convolutional Neural Networks (CNN) 1 for the signal and background classification for hadronically decaying boosted Higgs boson [3]. The Lund jet plane is a theory inspired jet representation which is used for jet tagging recently [4,5].…”

Section: Introductionmentioning

confidence: 99%

Lund jet plane for Higgs tagging

Khosa¹

2021

Preprint

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We study the boosted Higgs tagging using the Lund jet plane. The convolutional neural network is used for the Lund images data set to classify hadronically decaying Higgs from the QCD background. We consider H → b b and H → g g decay for moderate and high Higgs transverse momentum and compare the performance with the cut based approach using the jet color ring observable. The approach using Lund plane images provides good tagging efficiency for all the cases.

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Higgs boson tagging with the Lund jet plane

Cited by 3 publications

References 59 publications

Jet substructure at the Large Hadron Collider: A review of recent advances in theory and machine learning

Jet substructure at the Large Hadron Collider: A review of recent advances in theory and machine learning

Measuring the electron Yukawa coupling via resonant s-channel Higgs production at FCC-ee

Lund jet plane for Higgs tagging

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