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SM-like Higgs searches. M ~ 110-130 GeV/c**2, produced in association with Z and W: topology: two b-jets and at least one isolated, medium-Pt, prompt lepton SM predicts ~ 0.8 pb of HZ and ~1.5 pb of HW at 115 GeV Background mainly t-tbar~ 570 pb. Irreducible: ZZ (12 pb), ZW (30 pb),
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SM-like Higgs searches M ~ 110-130 GeV/c**2, produced in association with Z and W: topology: two b-jets and at least one isolated, medium-Pt, prompt lepton SM predicts ~ 0.8 pb of HZ and ~1.5 pb of HW at 115 GeV Background mainly t-tbar~ 570 pb. Irreducible: ZZ (12 pb), ZW (30 pb), Also: W/gamma/Z+bjets (10**5), b-bbar (10**8),... For SM Higgs 4-vector analysis indicates that S/sqrt(B) ~ 0.6 per year with a sample 5 events/year. Victor's full sim analysis gives S/sqrt(B)~0.34. => We can only hope that Nature has chosen an higher yield... ! * LHCb is good to find secondary vertices * LHCb is good to select “prompt” leptons * We are VERY bad to measure high E electrons * L0 is 88 % efficient to select HW and HZ events * Rapidity coverage limits our rejection power for t-tbar (“massive”) events
Multiple primary vtx (V0): Choose the one with max Sum(Pt of tracks) (Discard event if other V0's have too large Sum(Pt) ) Discard tracks attached to other V0's Lausanne analysis scheme Pre-selection requires: Global event: Sum(calorimetric Et) > 10-20 GeV Lepton(s): Pt > 10 GeV/c, prompt IP/IPE<3, locally isolated (by calorimetry) Also build Z0s from prompt leptons VV algorithm: search of "seeds" for jets. VV based on secondary vertices FJ Fast-jet algorithm FJ is a fast version of Kt di-jet mass (not calibrated) Require at least one VV seed in the event <= b flavour tag Reconstruct jets by cone algorithm Select events with at least two jets R=0.8 apart and R=0.8 away from prompt lepton (i.e. b / bbar / lepton isolation ). Build M(jj) (first jet-jet combination, with jets ordered in Pt).
BACKGROUND Not started yet… First test with new setup gives the known S/B yields at this stage of the analysis: for double VV-tag events we have ~20 signal events/year and ~700 t-tbar in the relevant mass window (70-120). t tbar Higgs From Laurent/Victor thesis: most efficient filter is some NN…
seed V0 Tools and tests: Jet seed finder Jet seed algorithm “VV” - seed is used to reconstruct the jet by a cone algorithm - gives b flavor tag VV searches for 2 (or 3) tracks secondary vertices and determines an average direction: the seed. Study done with “Jet-gun” events: a quark (u, b,...) is sent to Pythia, setup for “independent fragmentation”. => Allows a controlled environment (no underlying event, no hard gluon emission). VV finds a concentration of two-tracks, good (chi2<5) secondary vertices, all around the beam-axis, at radius r ~ 2 cm. Does not depend on: kind of quark phi angle jet energy choice of long tracks only same result with 3 tracks vertices r-phi z: log scale ~20 mm
Tools and tests: Jet calibration Jet calibration (see JWG of 16 April 2008) Infer calibration from Jet-gun events => train a NN with 11 inputs: 1) energies in jet cone (Tracker, PRS, SPD, ECAL, HCAL, MU) 2) value of the jet pseudorapidity 3) information about the possible saturation in ECAL and HCAL 4) position in ECAL, HCAL: inner, middle (ECAL), outer neural-n calibrated FWHM resolution ~ 40% but we still need to study possible NN bias... 1.4*(ecal+hcal+mu) trks+ecal+mu Victor also finds a resolution of about 40% after a calibration using a different calibration method (see his thesis). Mjj GeV/c**2
CONCLUSION & OUTLOOK Main problems encountered: Electron calibration VV strange behaviour Next steps: 1) study VV tag-efficiency vs purity 2) resume NN calibration study 3) resume study of particle-gun events to improve high E electrons calibration 4) seriously attack backgrounds