Studies on a Higgs-like Boson in the H(bb )W(`ν ) Channel with the CMS Experiment

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ser, Th. Chwalek, S. Fink, H. Held, B. Maier, Th. Mu ller, P.

23 K ARLSRUHE I NSTITUTE OF T ECHNOLOGY KIT University of the

1 Studies on a Higgs-like Boson in the H(bb )W(`ν ) Channel with the CMS Experiment DPG Fru hjahrstagung Dresden 23 Christian Bo ser, Th. Chwalek, S. Fink, H. Held, B. Maier, Th. Mu ller, P. Schieferdecker, F.-P. Schilling, J. Wagner-Kuhr K ARLSRUHE I NSTITUTE OF T ECHNOLOGY KIT University of the State of Baden-Wueremberg and National Laboratory of the Helmholtz Association

Introduction The search for the standard model Higgs boson produced in association with a Vector boson (VH) found to be very challenging in the beginning Buerworth, Davison, Rubin and Salam, Jet

2 Introduction The search for the standard model Higgs boson produced in association with a Vector boson (VH) found to be very challenging in the beginning Buerworth, Davison, Rubin and Salam, Jet Substructure as a New Higgs-Search Channel at the LHC, PRL,242 (28) q W W H l ν b Boosted Higgs q b Basic idea: Search for VH with H b b in a boosted regime Lower cross section, but very clean and well defined event topology good signal vs. background discrimination V & H and their decay products central good jet resolution b-tagging possible collimated decay products Christian Böser Studies on H(b b)w(lν) with CMS /

3 2 ν CMS-HIG2-44 (for HCP 22) Analysis Strategy 5 channels: Wlν, Zll, Zνν (l = e,µ) Jet energy regression for b jets Using Boosted Decision Trees (BDT), shape analysis Control Regions enriched in main backgrounds ( & V+jets): Verify that agree with Monte Carlo Predict the expected background in signal region Events / CMS Preliminary s = 7 TeV, L = 5. fb s = 8 TeV, L = 2. fb pp VH; H bb Data VH(25 GeV) VV VH(25 GeV) VV Z + bb Z + udscg W + bb W + udscg Single top Events / 5. CMS Preliminary 8 s = 7 TeV, L = 5. fb s = 8 TeV, L = 2. fb pp VH; H bb 6 Data Sub. stat. uncert. VH(25 GeV) VV MC uncert. (stat.) 5 MC uncert. (stat.) Data/MC χ =.37 K s = M [GeV] bb -2 2 M bb [GeV] Christian Böser Studies on H(b b)w(lν) with CMS /

4 Results & Prospects for H b b Exclusion limits p-value Best fit σ/σ SM 95% Asymptotic CL Limit on σ/σ SM CMS Preliminary s = 7 TeV, L = 5 fb s = 8 TeV, L = 2. fb VH(bb), combined CL S Observed CL S H25 injected CL S Expected CL S Expected ± σ CL S Expected ± 2 σ Local p-value CMS Preliminary s = 7 TeV, L = 5 fb s = 8 TeV, L = 2. fb VH(bb), combined Observed Expected from SM Higgs σ 2σ 3σ - + Z(l l )H(bb) Z(νν)H(bb) W(lν)H(bb) s = 7 TeV, L = 5. fb s = 8 TeV, L = 2. fb CMS Preliminary m H = 25 GeV m H [GeV] m H [GeV] Next analysis goal is to reach 3σ evidence Best fit σ/σ SM More and additional analysis improvements are required for this Very promising: Use advanced reconstruction technique considering the jet substructure SubJet/Filterjet (SJF) Algorithm Christian Böser Studies on H(b b)w(lν) with CMS /

5 The SJF algorithm Specifically designed to reconstruct heavily boosted objects decaying into jets [Buerworth et al., PRL,242] b b R flt b R b g b R b b b g R b b g fat jet CA jet clustering big R sub jet Undo clustering mass drop criteria filter jet CA reclustering small R Higgs candidate from 3 (2) leading filter jets One drawback of using jet substructure are missing dedicated energy corrections Jet energy regression [T. Aaltonen et al., arxiv:7.326v] Christian Böser Studies on H(b b)w(lν) with CMS /

6 BDT Regression Technique Goal: Correct filter jets for missing dedicated energy corrections BDT training on generated filter jet p gen T of signal MC Among jet specific information like momenta and b-tagging also event information, i.e. the pile-up density ρ, enter the BDT Already done in similar way for standard jets Reconstructed m(h) in Signal MC Shapes of Signal + Background MC norm. to unit area.6.4 WH25 nominal WH25 regression mean: 4.5 σ: 3.3 mean: 24.4 σ: 2.8 norm. to unit area.5. Di-Boson nominal Di-Boson regression W+Jets nominal W+Jets regression WH(25) nominal WH(25) regression [GeV] filter m jj Mass resolution improves and means shift to true values [GeV] Christian Böser Studies on H(b b)w(lν) with CMS / filter m jj

7 How to Gain from Substructure? Easiest and fastest way: Put the additional information in the BDT classification training Additional variables in different control regions: m filter jj m jj m filter jj p filter T,jj L=2 fb KS=.797 L=2 fb KS=.874 L=2 fb KS= H(bb)W(eν) V+udscg CR 2. < p (W) < 7. T H(bb)W(µν) CR 2. < p (W) < 7. T H(bb)W(µν) V+bb CR p (W) > 7. T (-mc) filter m jj [GeV] V + udsc CR (-mc) filter m - m jj [GeV] jj t t CR (-mc) T,jj T,jj pfilter [GeV] filter p [GeV] V + b CR Additional variables are well described and add a significant amount of discriminating power Christian Böser Studies on H(b b)w(lν) with CMS /

8 BDT Outputs in Signal Region Classification training including the additional variables Exclusion of in the signal region to avoid experimenter s bias (blinded analysis) Good Data/MC agreement found in all categories Output in 3 analysis bins: loose b-tag medium p T (W ) high p T (W ) L=2 fb H(bb)W(µν) BDT selection p (W) > 7. T VH(25) bb VH(25) bb L=2 fb H(bb)W(µν) BDT selection 2. < p (W) < 7. T VH(25) bb VH(25) bb L=2 fb H(bb)W(µν) BDT selection p (W) > 7. T VH(25) bb VH(25) bb (-mc) BDT output (-mc) BDT output (-mc) BDT output BDT output Show possible improvement additional variables in terms of expected limits Christian Böser Studies on H(b b)w(lν) with CMS /

9 Expected Exclusion Limits no additional substructure additional SJF variables 95% C.L. Limit on σ/σ SM H(bb)W(lν) BDT analysis CL s CL s CL s L=2 fb expected expected ± expected ± σ 2σ 95% C.L. Limit on σ/σ SM H(bb)W(lν) BDT analysis CL s CL s CL s L=2 fb expected expected ± expected ± σ 2σ Higgs Mass [GeV] Higgs Mass [GeV] Expected CLs Limit for: H() H(5) H(2) H(25) H(3) H(35) no add. substructure add. SJF variables On average 6% improvement in terms of expected limits Studies in Zll and Zνν confirm improvements Christian Böser Studies on H(b b)w(lν) with CMS /

results Including information from the jet substructure can help to reach the

10 Summary & Outlook VH(bb) analysis in CMS has been studied in detail for possible improvements The SJF algorithm has been validated and shows promising results Including information from the jet substructure can help to reach the 3σ evidence goal Stay tuned! Christian Böser Studies on H(b b)w(lν) with CMS /

11 BACKUP Christian Böser Studies on H(b b)w(lν) with CMS /

12 Definition of Control Regions Variable W+light t t W+heavy p T (j ) > 3 > 3 > 3 p T (j 2 ) > 3 > 3 > 3 p T,jj > 2 > 2 > 2 p T (W ) [2 7](> 7) [2 7](> 7) [2 7](> 7) CSV [ ] >.898 >.898 N(extra jets) < 2 > = /E T > 35 (e only) > 35 (e only) > 35 (e only) /E T significance > 2.(µ) > 3.(e) mjj flt (,25) (,25) veto(9,5) Christian Böser Studies on H(b b)w(lν) with CMS /

13 Validation: Reconstruction of t had,boost Take only with 2 filter jets and 4 jets in total Ask for exactly filter jet in fat higgs with CSV >.6 In principle the tri filter jet system yields t had,boost q g t t W + l + ν b b If 3 filter jets t had,boost If 2 filter jets add nearest add. jet t had,boost q W t had q q m jl j l m W < 5 GeV Christian Böser Studies on H(b b)w(lν) with CMS /

14 Invariant Mass of t had,boost nominal regression 2 5 H(bb)W(µν) Top nominal L=2 fb 2 5 L=2 fb H(bb)W(µν) Top regression 5 5 (-mc) 2 t had [GeV] m flt (-mc) 2 t had [GeV] m flt Good -MC agreement before and after regression Regression yields correct value for the mass of the hadronic top Relative resolution improves about 4% norm. to unit area.5..5 mean: σ: 5.98 mean: σ: nominal regression mt flt had [GeV] Christian Böser Studies on H(b b)w(lν) with CMS /

Measurements of Fermionic Couplings of the Standard Model Higgs Boson using the bb, ττ and µµ Decay Channels with the ATLAS Detector

Measurements of Fermionic Couplings of the Standard Model Higgs Boson using the bb, ττ and µµ Decay Channels with the ATLAS Detector International Europhysics Conference on High Energy Physics Venice,