Latest results on the SM Higgs boson in the WW decay channel using the ATLAS detector

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Latest results on the SM iggs boson in the decay channel using the detector arxiv:188.954, accepted by PRB Claudia Bertella, on behalf of Collaboration The 4th China LC Physics Workshop (CLCP 218) 21-December-218 C. Bertella CLCP218-21-December-218!1

* lνlν The most precise measurement of the iggs couplings in Run 1 * channel well-suited for exploring rare production modes Second largest branching ratio: 22% Only * lνlν ( l=e,μ, lνν ~2%) analysed:.4% Good S/B from clean di-lepton signature 8 TeV results σ(pp +X) [pb] 2 1 1 pp (NNLO+NNLL QCD + NLO EW) pp qq (NNLO QCD + NLO EW) LC IGGS XS WG 214 PhysRevD.92.16 Confirmed: 5.8 σ σ =4.6±1.2 pb 1 1 pp W (NNLO QCD + NLO EW) pp Z (NNLO QCD + NLO EW) pp bb (NNLO and NLO QCD) pp tt (NLO QCD) = 125 GeV MSTW8 7 8 9 1 11 12 13 14 s [TeV] M Evidence: 3.2 σ σ =.51±.2 pb SM signal () () W Z tt 2,3 LC-XS-WG 2,4 2, 2,1 3,8 1 2 3 4 Ratio 13/8 TeV JEP8(215)137 Search: 2.5 σ μ V =3 C. Bertella CLCP218-21-December-218!2

/ iggs Boson Spin zero iggs: charged leptons preferentially emitted in same direction m ll and Δφ ll are used in the event selection or in the BDT training Signal process can not be fully reconstructed presence of neutrinos Events / 1 GeV 1 * eνµν, N jet = 5 1 15 25 two jets with large rapidity gap m T Suppressed hadronic activity in central region Jets bin categorisation Njet= Njet=1 Njet 2 Events 18 1 16 14 12 3 * eνµν 1 8 6 4 2 DY top-quark Mis-id iggs 1 2 3 4 5 6 NB: Significance further enhanced with a multivariate technique C. Bertella CLCP218-21-December-218!3 N jet

Main backgrounds: Backgrounds : estimated with MC simulation, normalisation shape with data for Top and Z ττ: shape from MC simulation, normalisation estimated with data Mis-Id: data-driven from events with one lepton satisfying only loose but failing tight ID criteria; fake rate measured in a Z-jet sample CR N jet,(pt >3 GeV) = N jet,(pt >3 GeV) = 1 N jet,(pt >3 GeV) 2 55 <m`` < 11 GeV m`` > 8 GeV `` < 2.6 m m Z > 25 GeV N b-jet,(pt >2 GeV) = max > 5 GeV m`t t t/wt N N b-jet,(2 GeV<pT <3 GeV) > b-jet,(pt >3 GeV) =1 N b-jet,(2 GeV<pT <3 GeV) = N b-jet,(pt >2 GeV) =1 (``, ET miss ) > /2 max m`t > 5 GeV central jet veto > 3 GeV m <m Z 25 GeV `` < 2.8 outside lepton veto N b-jet,(pt>2 GeV) = Z/ m`` < 8 GeV no p miss T requirement central jet veto max > 5 GeV outside lepton veto m`t `` > 2.8 m >m Z 25 GeV m m Z apple25 GeV C. Bertella CLCP218-21-December-218!4

background estimation N jet 1 iggs signal at low m ll control region at high m ll Normalize to data in CR Category t t/w N jet,(pt >3 GeV) = 1.6 ±.9.99 ± N jet,(pt >3 GeV) = 1.97 ±.17.98 ± N jet,(pt >3 GeV) 2 1.1 ± Main uncertainties: gg in the Signal region QCD and matching scales contribute up to 5%(12%) to σ (σ ) Events / 1 GeV 1 1 N jet =, Purity: 66% * eνµν, N jet = Events / 2 GeV 1 1 1 1 N jet =1, Purity: 37% * eνµν, N jet = 1 5 1 15 25 5 1 15 25 3 35 C. Bertella CLCP218-21-December-218 m T 55 GeV<m ll <11 GeV m ll >8 GeV m T!5

Top-quark background estimation Events with 1 b-jet are used as control regions b-jet veto to suppress in N jet =1 Top-quark background normalisation constrained with the control region Events / 2 GeV Main uncertainties: 7 5 3 1 b-tagging, 5-6% on σ / Top modelling, 5% on σ / N jet =, Purity: 87% * eνµν, N jet = 5 1 15 25 3 35 m T Events / 2 GeV 5 45 35 3 25 15 5 Category Category t t/w t Z/ t t/w N jet,(pt >3 GeV) N= jet,(pt >3 GeV) 1.6 = ±.9.99 1.6 ±.17.9.84.99 ±. N jet,(pt >3 GeV) N= jet,(pt 1 >3 GeV).97 = ± 1.17.98.97 ±.8.17.9.98 ±. N jet,(pt >3 GeV) N jet,(pt 2 >3 GeV) 2 1.1 ±.1.93 1.1 ±. N jet =1, Purity: 97% * eνµν, N jet = 1 5 1 15 25 3 35 m T Events / bin 45 35 3 25 15 5 N jet 2, Purity: 96% * eνµν, N jet 2 Data Uncertainty 1 2 3 4 5 6 7 8 9 b-jet with 2 GeV<pT<3 GeV b-jet with pt>3 GeV b-jet with pt>2 GeV Δ y jj C. Bertella CLCP218-21-December-218!6

Categorisation of the signal region Split SR in m ll, p T sub-lead lep, and flavour channels eμ/μe Improves control of different backgrounds Different background composition in each category Enhances sensitivity Splits defined for both N jet = and N jet = 1 signal regions m T distribution per category 8 bins (6 bins) for N jet = (Njet=1) Events / 5 GeV Events / 5 GeV 1 1 * eνµν, N jet = 1 15 2 25 3 35 4 45 5 55 6 9 7 5 3 1 N jet = * eνµν, N jet = 1 N jet = 1 m ll 1 15 2 25 3 35 4 45 5 55 6 m ll Events / 2.5 GeV Events / 2.5 GeV 1 1 7 5 3 1 * eνµν, N jet = 1 15 2 25 3 35 4 45 5 55 * eνµν, N jet = 1 p l1 t 1 15 2 25 3 35 4 45 5 55 pl1 t C. Bertella CLCP218-21-December-218!7

identification Selection of iggs boson candidate Veto presence of extra jets between the two leading jets Central iggs boson decay Veto Z mass window Properties of * eνμν decay and topology are used in a boosted decision tree * eνμν: m ll, Δφ ll,m T topology: m jj, Δy jj, η centrality, M lj, p T tot ighest ranked variables: m jj and Δy jj, Events / bin Events / bin 1 1 * eνµν, N jet 2 3 1 3 5 1 * eνµν, N jet 2 igh m jj enriched in Data m jj Uncertainty 3 igh Δy jj enriched in 1 2 3 4 5 6 7 8 9 Δ y jj C. Bertella CLCP218-21-December-218!8

Signal regions Combined and fit m T in 16 SR categories BDT with 4 bins in SR Control regions Yield in, top-quark and Z ττ CRs for N jet 1 Yield in Z ττ CR for N jet 2 BDT in top-quark CR Events / 1 GeV Data-Bkg. 1 1 1 1 3 1 * eνµν, N jet 1 t t /Wt ~ iggs 6.σ obs Process N jet = N jet = 1 N jet 2 Inclusive BDT: [.86, 1.] 639 ± 11 285 ± 51 42 ± 16 6 ± 3 7 ± 1 31 ± 2 28 ± 16 16 ± 6 316 ± 23 153 ± 26 ± 6 11 ± 2 333 ± 38 28 ± 32 7 ± 12 3 ± 1 t t/w t 588 ± 13 1397 ± 179 127 ± 8 14 ± 2 Mis-Id 447 ± 77 234 ± 49 9 ± 3 6 ± 2 Z/ 27 ± 11 76 ± 24 28 ± 4 4 ± 1 Total 567 ± 8 3296 ± 61 217 ± 5 6 ± 1 Observed 589 3264 2164 6 Events / bin 25 15 5 6 8 1 12 14 16 18 22 24 * eνµν, N jet 2 Events/bin [,.26] [.26,.61] [.61,.86] [.86,1.] 15 1 5 m T 1.8obs BDT score C. Bertella CLCP218-21-December-218!9

* eνμν @ 13TeV All results extracted by the simultaneous fit of all the and SRs and CRs One parameter of interest per production mode Cross-sections times branching fraction and signal strength 1 σ compatible with SM σ = 1.4±.6 pb σ =.81±.2 pb C. Bertella CLCP218-21-December-218!1

cross-section systematic dominated (exp:12%, theo:1%) Main theo. unc.: Signal QCD scales gg, PS top-quark modelling Systematic Uncertainties Source B! [%] B! [%] Data statistics 1 46 CR statistics 7 9 MC statistics 6 21 Theoretical uncertainties 1 19 signal 5 13 signal <1 4 6 12 Top-quark 5 5 Experimental uncertainties 8 9 b-tagging 4 6 Modelling of pile-up 5 2 Jet 2 2 Lepton 3 <1 Misidentified leptons 6 9 Luminosity 3 3 TOTAL 18 57 cross-section statistic dominated (46%) Main theo. unc.: MC statistic has a large contribution QCD scales on in phase space MC modelling missing higher order C. Bertella CLCP218-21-December-218!11

* eνμν @ 13TeV Presented the and cross-sections times branching ratio in the * eνμν using 36 fb measurement dominated by the systematic uncertainty measurement will gain from including the 217/18 data A lot a room of improvements for the run 2 legacy paper Challenge ahead Data with very high pile-up Reduce Mis-Id contamination and impact of its uncertainties Control uncertainties on the SM * eνμν plays an important role in the iggs boson combination -CONF-218-31 C. Bertella CLCP218-21-December-218!12

Back-up C. Bertella CLCP218-21-December-218!13

Discriminant variable in SRs Events / 2 GeV 1 * eνµν, N jet = 1 Events / 1 GeV 1 * eνµν, N jet = 5 1 15 25 5 1 15 25 m T m T C. Bertella CLCP218-21-December-218!14

Z ττ background estimation Events / 1 GeV 1 1 1 1 N jet =, Purity: 9% * eνµν, N jet = Events / 1 GeV 1 1 1 N jet =1, Purity: 7% * eνµν, N jet = 1 Events / bin 25 15 1 5 N jet 2, Purity: 73% * eνµν, N jet 2 Data Uncertainty 4 6 8 1 12 14 16 18 m T 4 6 8 1 12 14 16 18 m T 1 2 3 4 5 6 7 8 9 Δ y jj C. Bertella CLCP218-21-December-218!15

MC Samples Monte Carlo generators used to model the signal and background processes with the corresponding product of cross section and the branching ratio for the iggs boson production are 13 TeV Process Matrix element PDF set UEPS model Prediction order (alternative) (alternative model) for total cross-section Powheg-Box v2 NNLOPS [16,8,1] PDF4LC15 NNLO [9] Pythia 8 [14] N 3 LO QCD + NLO EW [24,25,26,27,28] (MG5 amc@nlo [46,47]) (erwig 7 [48]) Powheg-Box v2 PDF4LC15 NLO Pythia 8 NNLO QCD + NLO EW [24,29,3,31] (erwig 7) V Powheg-Box v2 [49] PDF4LC15 NLO Pythia 8 NNLO QCD + NLO EW[5,51,52] qq! Sherpa 2.2.2 [32,32,33] NNPDF3.NNLO [34] Sherpa 2.2.2 [35,36] NLO [37] (Powheg-Box v2, MG5 amc@nlo) (erwig++ [48]) gg! Sherpa 2.1.1 [37] CT1 [53] Sherpa 2.1 NLO [38] W Z/V /ZZ Sherpa 2.1 CT1 Sherpa 2.1 NLO [37] V Sherpa 2.2.2 NNPDF3.NNLO Sherpa 2.2.2 NLO [37] (MG5 amc@nlo) (CSS variation [35,54]) t t Powheg-Box v2 [55] NNPDF3.NLO Pythia 8 NNLO+NNLL [56] (Sherpa 2.2.1 ) (erwig 7) Wt Powheg-Box v1 [57] CT1 [53] Pythia 6.428 [58] NLO [57] (MG5 amc@nlo) (erwig++) Z/ Sherpa 2.2.1 NNPDF3.NNLO Sherpa 2.2.1 NNLO [59,6] C. Bertella CLCP218-21-December-218!16

Event Selection Category N jet,(pt >3 GeV) = N jet,(pt >3 GeV) = 1 N jet,(pt >3 GeV) 2 Preselection Background rejection!! e µ Two isolated, di erent-flavour leptons (` = e, µ) with opposite charge p lead T > 22 GeV, p sublead T > 15 GeV m`` > 1 GeV > 2 GeV p miss T (``, ET miss ) > /2 max m`t N b-jet,(pt >2 GeV) = > 5 GeV p`` T > 3 GeV m <m Z 25 GeV m`` < 55 GeV `` < 1.8 central jet veto outside lepton veto Discriminant variable m T BDT BDT input variables m jj, y jj, m``, ``, m T, P` C`, P`,j m`j, p tot T C. Bertella CLCP218-21-December-218!17

Mis-identified lepton background W+jets (Mis-Id) evaluated from Z+jets data and corrected for expected differences with W+jets Challenges: Mis-id extrapolation factor Reduce W+jets background while using low p T leptons.6.5.4.3.2.1 η < 2.5 Extrapolation factor Stat. uncertainty EW subtraction Flavour composition 2 1 FF(p T, η) = * s = 13 TeV, 36 fb Electron p T 1 3 N e(μ),id Events / 5 GeV Events / 5 GeV N e(μ),anti ID Mis-id extrapolation factor 3 25 15 1 5 3 (a) Identified electron (c) Anti-identified electron 2 3 4 5 6 7 8 9 1.5 η < 2.5 Extrapolation factor Stat. uncertainty.4 EW subtraction Flavour composition.3.2.1 2 1 Electron p T Events / 5 GeV Events / 5 GeV 5 3 1 15 5 Muon p T (b) Identified muon (d) Anti-identified muon * s = 13 TeV, 36 fb 2 3 4 5 6 7 8 9 1 1 3 Muon p T * s = 13 TeV, 36 fb Observed (stat.) Background Syst. uncertainty FF applied in control region with 1 ID and 1anti-ID leptons to predict the Mis-ID in the ID+ID region C. Bertella CLCP218-21-December-218!18

identification Selection of iggs boson candidate Veto presence of extra jets between the two leading jets Events /.31 rad 5 3 * eνµν, N jet 2 3 Central iggs boson decay 1 Veto Z mass window Properties of * eνμν decay and topology are used in a boosted decision tree * eνμν: m ll, Δφ ll,m T topology: m jj, Δy jj, η centrality, M lj, p T tot ighest ranked variables: m jj and Δy jj, Events / 1 GeV 5 3 1.5 1 1.5 2 2.5 3 * eνµν, N jet 2 Data Uncertainty 3 2 4 6 8 1 12 14 16 18 m ll Δ φ ll C. Bertella CLCP218-21-December-218!19

channels C. Bertella CLCP218-21-December-218!2

channels * eνμν candidate and two jets with topology Longitudinal view MET ET 45 35 25 Projected η-φ view muon jet jet electron 15 5 4 2 η -2-4 9 18 27 36 φ Run 35618, Ev. no. 2461194919 Aug. 5, 216, 8:37:53 CEST C. Bertella CLCP218-21-December-218!21

* eνμν @ 13TeV Impact = Δσ B SM * /σ.1.5.5.1 Impact = Δσ B SM * /σ.1.5.5.1 gg fraction, N jet = Modeling of pile-up b-jet tagging Mis-Id sample composition generator and UEPS model, N jet 2 +3j QCD scale +2j QCD scale Mis-Id subtraction of electroweak processes QCD scale, N jet 1 Mis-Id subtraction of electroweak processes UEPS model, N jet 1 UEPS, N jet M jj 2 b-jet tagging modelling tt generator, N jet 2 Double fakes, N jet 2 matching scale, N jet 1 tt UEPS model, N jet * 2 Pull +1σ Impact σ Impact 2 3 1.5 2 1.5 1.51 1 2 1.5 3 2 Pull = (θ-θ )/Δθ tt UEPS model, Jet energy scale pile-up p term T N jet * 2 Pull +1σ Impact σ Impact 1.5 4 1 2.5.52 1 41.5 Pull = (θ-θ )/Δθ C. Bertella CLCP218-21-December-218!22

CMS Results Main theoretical uncertainties are cross section and jet bin migration Main experimental systematics come from the background rates, luminosity, and lepton identification efficiencies C. Bertella CLCP218-21-December-218!23