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S. Chakrabarti (K. Tschann-Grimm, Y. Hu, P. Grannis ) SUNY @ Stony Brook

Search for the SM Higgs boson in tt jj final state. S. Chakrabarti (K. Tschann-Grimm, Y. Hu, P. Grannis ) SUNY @ Stony Brook. NSF Site Visit Nov. 19, 2009. Outline. Motivation Preselection Multivariate Method Results Summary.

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S. Chakrabarti (K. Tschann-Grimm, Y. Hu, P. Grannis ) SUNY @ Stony Brook

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  1. Search for the SM Higgs boson in ttjj final state • S. Chakrabarti • (K. Tschann-Grimm, Y. Hu, P. Grannis) • SUNY @ Stony Brook NSF Site Visit Nov. 19, 2009

  2. Outline • Motivation • Preselection • Multivariate Method • Results • Summary Analysis presented here is for 3.9 fb-1 from Run 2b (combine with similar search in Run IIa with 1.0 fb-1 2 Higgs in tt jj final states - Chakrabarti

  3. Motivation Higgs production • The channels involving tau decays of either Higgs or W/Z have about half the XS *BR as the W(lv)H(bb) or Z(vv)H(bb), so add measurably to Higgs sensitivity • Simultaneous search for associated VH production and Vector Boson Fusion (VBF)/ gluon gluon fusion (GGF) signals • First Tevatron search for SM Higgs in tau final states • Mainly sensitive at low mass • Discuss here mainly the Run 2b analysis (3.9 fb-1); then combine with published Run 2a result (1.0 fb-1) Higgs decays low high 3 Higgs in tt jj final states - Chakrabarti

  4. L= 3.9 fb-1 VH/VBF→ttjj Signal channels Z(tt) H(bb) H(tt) Z(qq) H(tt) W(qq’) VBF: qqq’q’WWq’q’H(tt) GGF: ggH(tt)+2jets • Event Preselection • Only one isolated muon, pT>15 GeV(from t decay) • One hadronic tau candidate, pT>15 GeV • At least two jets pT>20 GeV and |h|<3.4 • Opposite sign mu-tau pair requirement • Veto on electrons • spatial separation of jets, m, t • No b tagging (allow W/Z  qq’) At preselection 4 Higgs in tt jj final states - Chakrabarti

  5. Multivariate Analysis No single variable allows good separation of (very small) signal and background. Select 17 well-modeled variables to train Boosted Decision Trees (BDT)* to differentiate signal/background. Comparison of data and MC for 3 of BDT input variables (at preselection level): ST= S|pT| for m, t, jets, MET C= HT/HE where HE(HT) is scalar sum of total energy (transverse energy) for all jets * DTs are iteratively trained learning networks in which events are sorted into ‘signal-like’ and ‘background-like’ nodes using successive selections on some input variable. Boosting is a technique of weighting those events that are misclassified more heavily in the next iteration. 5 Higgs in tt jj final states - Chakrabarti

  6. BDTs for ττjj selection 32 BDTs trained: one for each of 4 signals (VBF and GGF done together) with respect to each of 4 bkgds (ttbar, W+jets, Z+jets, Multijet). Train for low (<135 GeV) and high (>135 GeV) Higgs mass. Representative BDT outputs for HW signal vs tt, W+jets, multijet background: HW vs MJ HW vs tt HW vs W+jets Signal (dotted histogram) tends to high BDT; bknd being trained against (stacked colored histogams)tend to low BDT. 6 Higgs in tt jj final states - Chakrabarti

  7. Max BDT For each background j (j = tt, W+jets, MJ), use the Maximum BDT output BDTj= maxi BDT(i,j) over signals (i = ZH, HZ, HW, VBF). Final selection sample is obtained after cuts on BDTj (>-0.2, >-0.2, >0). Z+jets background is not well discriminated since its event topology is similar to the signals. Max BDT ttbar Max BDT W+jets Max BDT MJ Signal tends toward high MaxBDT; backgrounds tend to small MaxBDT 7 Higgs in tt jj final states - Chakrabarti

  8. Weighted Avg BDT for Zjets Yields after MaxBDT cuts: After the MaxBDT cuts, form a final variable for limit setting from the Z+jets BDTs averaged over signals: BDTZjets = S ei*BDT(i, Zjets)/Sei (ei = XS*BR*Acceptance for signal i) Use BDTZjets distribution for final limit setting. Use modified frequentist method: Form log likelihood ratios (LLR) from the BDTZjet distributions to conform to Bknd only or Signal+bknd over many pseudo experiments. Obtain CLb (CLs+b) for B (S+B) to be less likely than observed. Scale up signal until CLs=CLs+b/CLb reaches 5% to obtain signal 95% CL limits.) The pseudoexpts allow fluctuations within statistical and systematic uncertainties (correlations included). Low MH Major systematics: t energy scale (4.5%) Lumi (6.1%), MJ bknd (15%) Cross sections (~10%), jet energy scacle(7.5%) 8 Higgs in tt jj final states - Chakrabarti

  9. Limits Run 2b results: LLR (more negative is more signal-like). Black dotted curve is LLR expected if Bknd only (green/yellow for ±1, ±2s bands) and black solid line is observed in our data. Corresponding expected and observed 95% CL XS limits/(SM expectation) (Run 2b only) Run 2b Combine with Run 2a result (PRL 102, 251801 (2009)) to get limits for 4.9 fb-1. For MH=115 GeV, expected/observed limit ratio to SM is 16/27. 9 Higgs in tt jj final states - Chakrabarti

  10. Summary • First results for Higgs search with tau final states • This analysis included in the combined Tevatron limits (3/09) below. • Sensitive at low mass; 95% CL limit currently 27x SM prediction • Update and improve with >6 fb-1 for Moriond 2010 and publication with et channel 10 Higgs in tt jj final states - Chakrabarti

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