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Search for the Higgs boson produced in association with top quarks and decaying into bottom quarks with the ATLAS detector Shunsuke Honda (High Energy Physics Laboratory) 1 2018/03/27 Top Quarks and Higgs Bosons 2 Top Quark:


  1. Search for the Higgs boson produced in association with top quarks and decaying into bottom quarks with the ATLAS detector Shunsuke Honda (High Energy Physics Laboratory) � 1 2018/03/27

  2. Top Quarks and Higgs Bosons � 2 Top Quark: Largest and unique mass value m top = 173.3 GeV ~ v / √2 → Top-Yukawa coupling Yt ~ 1: a key parameter of the SM Yt probes BSM such as VLQ, SUSY, … The ttH production allows the direct measurement of top-Yukawa with significant sensitivities in LHC Run2. Small cross sections, but distinct signatures in various decay channels in Higgs and ttbar γγ 0.2% g g t VV,ττ 30.6% Yt H H bb 57.6% g g t others Cross-section = 0.51 pb at 13TeV 11.6% 2018/03/27 Shunsuke Honda (U Tsukuba)

  3. ttH(H → bb) Objects � 3 ttH → 6jets(4b-jets), 1lepton, MET / 4jets(4b-jets), 2leptons, MET W → light-/c-jets W → ℓν MET e/μ MET W → ℓν W → ℓν e/μ e/μ t t t t H H b-jets b-jets H → bb H → bb Background sources: tt+jets (85-96% of total Bkgd.) (generated gluon instead of Higgs) t t tt+bb : 4b-jets g → same final states: irreducible tt+cc : 2b-jets + 2c-jets / tt+light: 2b-jets + 2 light-jets 
 → reducible BKG with b-jet identification (=> b-tagging) 2018/03/27 Shunsuke Honda (U Tsukuba)

  4. Flavor Tagging (b-tagging) � 4 10 Arbitrary units ATLAS Simulation Preliminary tracks s = 13 TeV, t t 1 b jets jet c jets Light-flavour jets 1 − 10 secondary vertex B-hadron decaying cτ~450 μm − 2 10 3 − 10 primary vertex generated B-hadron 1 0.8 0.6 0.4 0.2 0 0.2 0.4 0.6 0.8 1 − − − − − 1 2 3 4 5 mv2c10 BDT score t t H 5 5 4 3 1 1 larger smaller 2018/03/27 Shunsuke Honda (U Tsukuba)

  5. Region Definition � 5 Using four highest btagging scores per event: t t H 5 5 4 3 1 1 larger smaller (1 st , 2 nd ) jet Single Lepton, ≥ 6 j b b b -tagging discriminant (3, 3) (4, 3) remaining bins: CR t ¯ (5, 3) t + light >30% of tt+b >30% of tt+≥1c (4, 4) CR t ¯ CR t ¯ t + b t + ≥ 1 c (5, 4) (5, 5) SR 1 SR 2 SR 3 >60% >45% >30% (3 rd , 4 th ) jet (5, 5) (5, 4) (5, 3) (5, 2) (4, 4) (4, 3) (4, 2) (3, 3) (3, 2) (2, 2) (5, 1) (4, 1) (3, 1) (2, 1) (1, 1) b b -tagging of tt+≥2b b discriminant 2018/03/27 Shunsuke Honda (U Tsukuba)

  6. Defined Regions � 6 12 regions for single-lepton channel (5jets, ≥6jets) - two control regions enriched by tt+light , tt+≥1c or tt+b - five tt+bb and signal enriched regions ATLAS t t + light t t + 1c t t + 1b ≥ ≥ s = 13 TeV t t + V Non-t t Single Lepton - one boosted region 5j 5j 5j CR CR CR t t +light t t + ≥ 1c t t +b B B 2 / S ATLAS / S 0.05 -1 s = 13 TeV, 36.1 fb 1.8 5j 5j boosted SR SR SR 2 1 Single Lepton 1.6 0.04 1.4 1.2 0.03 1 6j 6j 6j ≥ ≥ ≥ CR CR CR t t +light t t + ≥ 1c t t +b 0.8 0.02 0.6 0.4 0.01 0.2 ≥ 6j ≥ 6j ≥ 6j SR SR SR 3 2 1 0 0 CR CR CR CR SR SR SR CR CR SR SR SR 5 5 5 5 5 ≥ ≥ ≥ j j boosted 6 ≥ ≥ 6 6 ≥ 6 6 j j j 6 j j j j j j 1 tt+b 1 tt+b 3 2 tt+light tt+ 2 tt+light tt+ ≥ ≥ 1c 1c 2018/03/27 Shunsuke Honda (U Tsukuba)

  7. � 7 Multi-Variate Analysis: ttH and tt+bb Separation Advanced discriminants : Reconstruction kinematics MEM discriminant identify jet assignments uses Signal / Bkgd. probability via ME calculation for top/Higgs candidates LH discriminant using MVA algorithm uses various PDFs of masses/angles, 
 500 Events / 25 GeV Data t t H ATLAS t t + light t t + 1c ≥ -1 s = 13 TeV, 36.1 fb considering missing object prob. t t + ≥ 1b t t + V 400 Single Lepton Non-t t Total unc. ≥ 6j SR S/B ~ 0.10 t t H (norm) 1 Post-Fit Pre-Fit Bkgd. 300 Events / bin Data t t H 450 ATLAS Higgs mass t t + light t t + 1c ≥ -1 s = 13 TeV, 36.1 fb t t + 1b t t + V ≥ 200 400 Single Lepton Non-t t Total unc. ≥ 6j SR t t H (norm) 1 350 Post-Fit 100 MVA score tt+bb 300 250 1.5 0 Data / Pred. 1.25 200 1 S/B ~ 0.23 0.75 150 tt+bb 0.5 0 50 100 150 200 250 300 350 Higgs 100 m (reco BDT) [GeV] bb 50 1.5 0 Data / Pred. Simple kinematic variables 1.25 1 Δ R bb max.pT , m bb min. Δ R , … 0.75 0.5 b-tagging scores for each jet 1 0.8 0.6 0.4 0.2 0 0.2 0.4 0.6 0.8 1 − − − − − Classification BDT output 2018/03/27 Shunsuke Honda (U Tsukuba)

  8. Results � 8 Observed (Expected) excess = 1.4σ (1.6σ) over SM bkgd. determined with free-floating normalizations for tt+HF: - tt+≥1b: 1.24±0.10, tt+≥1c: 1.63±0.23 -1 Events / bin ATLAS s = 13 TeV, 36.1 fb 8 10 ATLAS Data t t H t t + light -1 s = 13 TeV, 36.1 fb t t + 1c t t + 1b t t + V ≥ ≥ tot. m = 125 GeV 7 10 Single Lepton Non-t t Total unc. t t H H stat. Post-Fit Single-lepton regions tot (stat syst) 6 10 5 10 1.02 0.54 0.87 Dilepton + + + − 0.24 ( ) 1.05 0.52 0.91 − − − (two- combined fit) µ 4 10 3 10 + 0.65 + 0.31 + 0.57 Single Lepton 0.95 ( ) − 0.62 − 0.31 − 0.54 2 10 (two- combined fit) µ 10 1.5 Data / Pred. 0.64 0.29 0.57 + + + 1.25 0.84 ( ) Combined 0.61 0.29 0.54 − − − 1 0.75 0.5 C C C S S C C C S S S 1 0 1 2 3 4 5 6 S − R R R R R R R R R R R 5j 5j 5j 5j 5j R boosted ≥ ≥ ≥ ≥ ≥ ≥ 6j 6j 6j 6j 6j 6j 1 3 2 1 tt+light tt+ tt+b 2 tt+light tt+ tt+b ≥ ≥ 1c 1c t t H t t H Best fit µ = σ / σ SM no signal SM normalizations in all regions: tot (stat syst) consistent btw data and pred. Run1: 1.5 ± 1.1 ( ±0.8 ±0.7) − 1 0 1 2 3 4 5 6 t t H t t H Best fit µ = σ / σ SM → 40% improvements from Run1 2018/03/27 Shunsuke Honda (U Tsukuba)

  9. � 9 Systematic Uncertainties (15 Unc. with Largest Impacts on μ-value) Pre-fit impact on µ : Δ µ ∆ µ = + = - θ θ Δ θ θ θ Δ θ 1 0.5 0 0.5 1 − − -1 -0.5 0 0.5 1 Post-fit impact on : µ more This result more ATLAS = + = - Run1 θ θ Δ θ θ θ Δ θ impact impact -1 ATLAS -1 s = 8 TeV, 20.3 fb , m =125 GeV s = 13 TeV, 36.1 fb Nuis. Param. Pull H t t +b b normalisation t t + 1b: S 5F vs. nominal ≥ HERPA jet energy scale 1 t t + ≥ 1b: S 4F vs. nominal HERPA t t + ≥ 1b: PS & hadronization t t +c c normalisation t t + ≥ 1b: ISR / FSR t t +b b renormalisation scale choice m t t H: PS & hadronization bb t t +V cross section b-tagging: mis-tag (light) NP I k(tt+ ≥ 1b) = 1.24 ± 0.10 t t +b b shower recoil scheme Jet energy resolution: NP I jet energy scale 2 t t H: cross section (QCD scale) light-jet tagging 1 tt+ ≥ 1b: tt+ ≥ 3b normalization t t +c c t t p reweighting T t t + ≥ 1c: S 5F vs. nominal HERPA b-jet tagging 1 t t + ≥ 1b: shower recoil scheme t t + ≥ 1c: ISR / FSR t t +c c top p reweighting T Jet energy resolution: NP II t t +b b renormalisation scale t t +light: PS & hadronization jet energy scale 3 Wt: diagram subtr. vs. nominal light-jet tagging 2 b-tagging: efficiency NP I b-tagging: mis-tag (c) NP I t t +b b PDF (MSTW) miss E : soft-term resolution T -1.5 -1 -1 -0.5 -0.5 0 0 0.5 0.5 1 1.5 1 b-tagging: efficiency NP II ( - )/ Pull θ θ ∆ θ 0 2 1.5 1 0.5 0 0.5 1 1.5 2 Pre-fit Impact on − − − − µ Post-fit Impact on ( - )/ µ θ θ Δ θ 0 Less impacts from tt+cc , other Bkgd. modelings But still large impact by tt+bb modeling also in new results. 2018/03/27 Shunsuke Honda (U Tsukuba)

  10. Comparison btw. ATLAS and CMS � 10 Events / bin Data t t H 450 ATLAS t t + light t t + ≥ 1c -1 s = 13 TeV, 36.1 fb t t + 1b t t + V ≥ 400 Single Lepton Non-t t Total unc. 6j ≥ SR t t H (norm) 1 350 Post-Fit 300 most sensitive region 250 200 good consistencies in all bins. 150 100 50 0 1.5 Data / Pred. 1.25 1 0.75 0.5 1 0.8 0.6 0.4 0.2 0 0.2 0.4 0.6 0.8 1 − − − − − Classification BDT output Result -1 ATLAS s = 13 TeV, 36.1 fb ~ same results in both analysis tot. m = 125 GeV H stat. tot (stat syst) but smaller unc. in CMS. 1.02 0.54 0.87 Dilepton + + + − 0.24 ( ) − 1.05 − 0.52 − 0.91 combined fit) different treatments for 0.65 0.31 0.57 Single Lepton + + + 0.95 ( ) tt+jets modeling − 0.62 − 0.31 − 0.54 combined fit) +0.24/-0.28 for CMS 0.64 0.29 0.57 + + + 0.84 ( ) Combined 0.61 0.29 0.54 − − − +0.46/-0.46 for ATLAS − 1 0 1 2 3 4 5 6 t t H t t H Best fit = / µ σ σ SM 2018/03/27 Shunsuke Honda (U Tsukuba)

  11. � 11 Conclusion The ttH production allows the direct measurement of top-Yukawa: largest and unique coupling value = a key for SM/BSM physics. Searched for ttH production with H->bb Key point: large systematic uncertainties in tt+jets modeling Run1 result: 1.4 σ observed (1.1 σ expected) Developed MVAs for optimized event categorization → μ = σ ttHobs / σ ttHSM = 0.8±0.6 : 1.4 σ observed (1.6 σ expected) 2018/03/27 Shunsuke Honda (U Tsukuba)

  12. � 12 Backup 2018/03/27 Shunsuke Honda (U Tsukuba)

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