Measurement of cross sections in Higgs boson …...•Higgs boson decays to four leptons can be...
Transcript of Measurement of cross sections in Higgs boson …...•Higgs boson decays to four leptons can be...
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Measurement of cross sectionsin Higgs boson decays
to four leptonswith the ATLAS detector
Susumu Oda
Kyushu University (Japan)
On behalf the ATLAS Collaboration
The European Physical Society Conference on High Energy Physics (EPS-HEP)
2019-07-11, Ghent, Belgium
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• Higgs boson decays to four leptons can be selected with a very high purity and are very well suited for measurements of Higgs boson properties, despite the small 𝐻 → 𝑍𝑍∗ → 4ℓbranching ratio.
Introduction
For 𝑚𝐻 = 125 GeV
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Main updates from previous results
• Previous 13 TeV results• JHEP 10 (2017) 132 (36.1 fb-1)• JHEP 03 (2018) 095 (36.1 fb-1)• ATLAS-CONF-2018-018 (79.8 fb-1)
• New results• ATLAS-CONF-2019-025 (139 fb-1)
1. Use the full Run 2 statistics (2015—2018)2. Improved lepton isolation to mitigate the impact of pileup3. Constraint of the major non-resonant 𝑍𝑍∗ background
from dedicated data sidebands4. Unfolding method exploiting the full response matrix5. Additional reconstructed event categories and new
discriminants to enhance the sensitivity to the various production modes
6. Dedicated control region to constraint the 𝑡𝑋𝑋 background
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Cross section measurements• Inclusive fiducial cross section• Total cross section
• Differential fiducial cross section• 𝑝𝑇
4ℓ and 𝑁jets : to test the SM prediction and constraint BSM effects because they are sensitive to • Higher-order QCD calculations• The modelling of gluon emission• The fractions of the different production modes• The Lagrangian structure of the Higgs boson interactions
• Production mode cross section• Simplified Template Cross Sections (STXS) framework
• To be model independent• Fiducial selection follows closely reconstruction-level selection.• Unfolding to correct for detector resolution and efficiency effects
• Use likelihood fit including detector response matrix for unfolding
• Template fit of 𝑚4ℓ distribution to extract the number of signal events
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Event selection
• Signal mass window: 115 < 𝑚4ℓ < 130 GeV
• SFOS: same-flavor opposite sign
• ME: matrix element for extra lepton(s) (𝑉𝐻-Lep, 𝑡𝑡𝐻-Lep) to avoid mispairing.
↓ Definition of the fiducial space
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Response matrices for unfolding
𝑝𝑇4ℓ 𝑁jets
• 𝑁𝑖 𝑚4ℓ = σ𝑗 𝑟𝑖𝑗 ∙ 1 + 𝑓𝑖nonfid ∙ 𝜎𝑗
fid ⋅ 𝑃 𝑚4ℓ ∙ ℒ + 𝑁𝑖bkg
(𝑚4ℓ)
• 𝜎𝑗fid = 𝜎𝑗 ∙ 𝐴𝑗 ∙ ℬ(𝐻 → 𝑍𝑍∗ → 4ℓ)
• 𝑟𝑖𝑗 allows to correct for bin migrations and detector efficiencies.
↓ Unfolding for the differential measurements
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Simplified Template Cross Sections (STXS)
• Production bins defined at the particle level for Stage 0 and reduced Stage 1.1
• Corresponding reconstructed event categories for signal and side-bands• 2𝑗 category now consists of a BSM category and a 2𝑗 category (the rest) where
neural network discriminants are used to separate VBF, ggF and 𝑉𝐻-had.
• New 0𝑗-𝑝𝑇4ℓ-High category for 𝑉𝐻 with 𝑍 → 𝜈𝜈, or 𝑊 → ℓ𝜈 where ℓ is missing.
• New side-band categories for backgrounds. (105 − 115 GeV and 130 − 350 GeV)
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SM signal composition (red. Stage 1.1)• In terms of the reduced Stage 1.1 production bins in each
reconstructed event category.
• The 𝑏𝑏𝐻 contributions are included in the ggF production bins.
• To improve the sensitivity neural network discriminants are exploited.
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Neural network (NN) inputs
• An improved performance was found with a structured neural network (multilayer perceptron, MLP) with inputs of• a recurrent NN (rNN) for the vectors of (pT, h) for four leptons• another rNN for up to three jets• and another MLP with additional variables.
• The NN can separate 2 or 3 processes. • For an NN with 3-outputs (PDFs), a cut is applied to one output, using this output as
a discriminant for the events passing the cut.• One of the other two outputs is used as a discriminant with the remained events.
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Systematic uncertainties (Stage 0)
• Luminosity• 2.8% → 1.7%
• Electron/muon reconstruction and identification efficiency and pileup dep.• Dominant• Reduced to about 50% of previous results
• Jet energy scale/resolution and b-tagging efficiencies
• Reducible background
• 𝑍𝑍∗ background• Reduced to about 60% of previous results
• 𝑡𝑋𝑋 background
• Parton distribution functions
• QCD scales
• Showering algorithm
• Correction factor due to relative contribution of each production
Many of systematic uncertainties have decreased.
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Invariant mass and numbers of events
115 GeV < 𝑚4ℓ < 130 GeV
This distribution is pre-fit.
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Invariant mass distributions
4𝜇 2𝑒2𝜇
2𝜇2𝑒 4𝑒
These distributions are pre-fit.
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𝑝𝑇4ℓ and 𝑁jets
𝑝𝑇4ℓ 𝑁jets
These distributions are pre-fit.
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Neural network output distributions (1)
• The expected and observed (pre-fit) distributions of the NN discriminants are shown.
• To separate ggF and ZZ*
• The expected event yields are in reasonable agreement with the observed ones.
0j - 𝑝T4ℓ- Low
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0j - 𝑝T4ℓ- Med
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Neural network output distributions (2)
• 1j-𝑝T4ℓ-Low category
• Discriminants to separate
• ggF, VBF, ZZ*
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Neural network output distributions (3)
• 1j-𝑝T4ℓ-Med category
• ggF, VBF, ZZ*
• 1j-𝑝T4ℓ-High category
• ggF, VBF
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Neural network output distributions (4)
• 2j category
• ggF, VBF, VH
• 2j-BSM-like category
• ggF, VBF
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Neural network output distributions (5)
• 𝑡𝑡𝐻-Had-enrichedcategory
• ggF, ttH, tXX
• 𝑉𝐻-Lep-enrichedcategory
• ttH, VH
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Categories without NN discriminant
• 0j-𝑝T4ℓ-High
• 1j-𝑝T4ℓ-BSM-like
• 𝑡𝑡𝐻-Lep-enriched
• Sideband • 0j, 1j, 2j, 𝑡𝑋𝑋, 𝑉𝐻-Lep
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𝑍 → 2𝜇 𝐻(→ 2𝑒2𝜇) candidate
Invariant mass of the extra di-muon in the upper hemisphere is 91.5 GeV.
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𝑍 → 2𝜈 or 𝑊 → ℓ𝜈 𝐻(→ 2𝜇2𝑒) candidate
MET is 240.3 GeV. 𝑝𝑇4ℓ is 181.1 GeV. They are back-to-back (∆𝜙=3.10).
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Fiducial and total cross sections
• The fiducial cross section is extrapolated to the total phase space.• The total cross section is compared to the cross sections predicted by
N3LO, MadGraph5_aMC@NLO-FxFx (MG5-FxFx), NNLOPS and Hres 2.3for ggF.
• Same-flavor cross sections should be about 10% higher than mixed-flavor cross section due to EW corrections.
• We are not quite sensitive to this yet.• About 14% uncertainty
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Differential cross sections
𝑝𝑇4ℓ 𝑁jets
• All samples are normalized to the most accurate SM predictions.• Fitted values of 𝑍𝑍∗ background normalization factors are also shown.• Good agreement is found between the data and the predictions of the SM.
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Cross section ratio and signal strength
𝑝SM = 73% 𝑝SM = 71%
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𝜎 ⋅ ℬ(𝐻 → 𝑍𝑍∗)/ 𝜎 ⋅ ℬ 𝐻 → 𝑍𝑍∗ SM
Stage 0 Reduced Stage 1.1
All Stage 0 and reduced Stage 1.1 ggF measurements agree with the predictions for the SM Higgs boson within 1.5 standard deviation.
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Summary
• Inclusive fiducial, differential and production mode cross section measurements of Higgs boson in the 𝐻 → 𝑍𝑍∗ → 4ℓ decay channel are presented.
• They are based on 139 fb-1 of 𝑠=13 TeV proton-proton collisions recorded by the ATLAS detector at the LHC in 2015—2018.
• Inclusive fiducial cross section• 𝜎fid = 3.35 ± 0.30 stat. ± 0.12 syst. fb
• 𝜎fid,SM = 3.41 ± 0.18 fb
• Differential cross sections as a function of 𝑝𝑇4ℓ and 𝑁jets
• Good agreement is found between the data and the predictions of the SM.
• ggF production cross section times branching ratio• 𝜎ggF ⋅ ℬ 𝐻 → 𝑍𝑍∗ = 1.15 ± 0.12 stat. ± 0.04 exp. ± 0.03 (th. ) pb
• 𝜎ggF ⋅ ℬ 𝐻 → 𝑍𝑍∗SM
= 1.17 ± 0.08 pb
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Backup slides27/26
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12+3 minute talk
• Title: Measurement of cross sections in Higgs boson decays to four leptons with the ATLAS detector
• Abstract: Higgs boson decays to four leptons can be selected with a very high purity and are very well suited for measurements of Higgs boson properties, despite the small H→ZZ→4l branching ratio. This talk will present measurements of differential cross sections, as well as cross section measurements for the different Higgs boson production processes in the simplified template cross section framework using pp collision data collected at 13 TeV.
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Fiducial and differential XS strategy
• Goal: model independent measurements of Higgs differential fiducial and inclusive cross sections (XS)• Fiducial selection follows closely reconstruction-level selection
• Unfold to correct for detector resolution and efficiency effects
• Template fit of 𝑚4ℓ distribution to extract the number of signal events
• Use likelihood fit including detector response matrix for unfolding as the baseline method.• Bin-by-bin correction factor unfolding is alternative.
• 𝑁𝑖 𝑚4ℓ = σ𝑗 𝑟𝑖𝑗 ∙ 1 + 𝑓𝑖nonfid ∙ 𝜎𝑗
fid ⋅ 𝑃 𝑚4ℓ ∙ ℒ + 𝑁𝑖bkg
(𝑚4ℓ)
• 𝜎𝑗fid = 𝜎𝑗 ∙ 𝐴𝑗 ∙ ℬ(𝐻 → 𝑍𝑍∗ → 4ℓ)
• 𝑁𝑖 : number of expected events in observable bin 𝑖
• 𝑃 : shape of signal contribution (from MC)
• ℒ : integrated luminosity
• 𝐴𝑖 : acceptance in fiducial phase space
• 𝜎𝑖 : total cross section
• 𝑁𝑖bkg
: background contribution
• 𝑟𝑖𝑗 : detector response matrix, generated in bin 𝑗and reconstructed in bin 𝑖
• 𝑓𝑖nonfid: correction for
reconstructed but not in fiducial phase space
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Expected number of SM Higgs events (Stage 0)
For 𝑚𝐻 = 125 GeV at an integrated luminosity 139 fb-1 and 𝑠 = 13 TeV
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Expected and observed numbers of events31/26
The expected numbers are pre-fit.
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Expected and observed cross sections32/26
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Differential fiducial cross section 𝑝𝑇4ℓ33/26
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Differential fiducial cross section 𝑝𝑇4ℓ34/26
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Differential fiducial cross section 𝑝𝑇4ℓ35/26
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Differential fiducial cross section 𝑁jets36/26
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Differential fiducial cross section 𝑁jets37/26
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STXS Stage 038/26
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STXS reduced Stage 1.139/26
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Systematic uncertainties of previous results40/26
ATLAS-CONF-2018-018 (79.8 fb-1)
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𝜎/𝜎SM vs signal strength41/26