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b-tagging with muons

b-tagging with muons. Aim: estimate the b-content in µ+jet data, using the pt distribution of muons / (jet+muon) axis. Use this µ+jet real data sample, to test the b-tagging in other methods (impact parameter, 2ndary vertices, …) and compute b-tag efficiencies with minimum MC inputs.

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b-tagging with muons

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  1. b-tagging with muons Aim:estimate the b-content in µ+jet data, using the pt distribution of muons / (jet+muon) axis. Use this µ+jet real data sample, to test the b-tagging in other methods (impact parameter, 2ndary vertices, …) and compute b-tag efficiencies with minimum MC inputs. Combine the muon-tag with the impact parameter (+other variables) in a likelihood-tag. I. Ripp-Baudot + Daniel Bloch, D.Gelé, S.Greder (IReS Strasbourg) I. Ripp-Baudot (IReS Strasbourg)

  2. Tools for the muon-tag Estimate the background from light quarks by using real data calorimeter jet triggers. Estimate smearing effects to the pTrel distribution by comparing jet trigger data with QCD MC. Apply this correction to b ( c)  µ and c  µ MC. Fit the pTrel distribution on real data, using 3 contributions : light quark (i.e. jet trigger data), c quark MC, b quark MC. calorimeter jet muon+jet pTrel muon I. Ripp-Baudot (IReS Strasbourg)

  3. Remarks Very different from b-tagging with DCA : have to use MC to get background & signal shapes. data/MC agreement ? Need samples : b ( c)  µ . c  µ light  µ pTrel distributions sensitive to :  , pT(jet),pT(track), R cuts… but need enough statistics to subdivide samples... Are tracks within an ordinary jet with pT>Xcut exactly the same (in average) as pions/kaons decaying into muons inside a jet of pT(µ+jet)>Xcut ?? I. Ripp-Baudot (IReS Strasbourg)

  4. Data p11 : 900k µ+jet streamed by the Top group (pT(µ)>5GeV) for runs 158…-162… (july-august). 230k jet triggers sampled along the SAME runs Use a RUN SELECTION : good smt+cft+calo+µdet and reject jets inside calo hot cells regions. MC p10.15 : 41k qcd pt>20, 34k qcd pt>40, 390k qcd pt>80 for data/MC comparisons and to extract (generated) cµ/e. 5k b(c)µ (reconstructed) from the B group, 66k Zbb used also to extract (reconstructed) b(c)µ. Event samples I. Ripp-Baudot (IReS Strasbourg)

  5. Muonid : nseg=3, ²<100, choose best ² if  2 candidates, pT>5GeV within a JCCB jet (standard cuts) with ΔR(/jet)<0.7and pT(jet+µ)>15GeV Gtracks : ask pT>5GeV, same jet association with pT(jet)>15GeV No η cut Selections µ+jet Data µ+jet Data pT(µ) pT(µ+jet) I. Ripp-Baudot (IReS Strasbourg)

  6. pT(jet) comparison data/MC Compare jet trigger data with QCD MC : not so easy to get a good agreement in pT(jet)… pT(jet) pT(jet) I. Ripp-Baudot (IReS Strasbourg)

  7. pTrel comparison data/MC Compare jet trigger data with QCD MC in order to correct the pTrel distribution in MC : (at present only a simple ratio, plan to smear the pTrel) apply this correction to b(c)µ and cµ MC I. Ripp-Baudot (IReS Strasbourg)

  8. b-signal : MC b  µ + b  c µ Samples : MC p10.15 Z  bb + inclusive bb with µ Muonid pTrel distributions : subdivided in pT(µ) bins pT(m) 5-7 GeV/c pT(m) 7-10 GeV/c pT(m) 10-15 GeV/c pT(m) > 15 GeV/c Fit : polyn( pTrel ) x exp( -pTrel/ p4 ) I. Ripp-Baudot (IReS Strasbourg)

  9. c-background Not enough statistics of reconstructed Muonid from c : Have checked on b ( c)  µ that : pTrel (generated + rec. µ)  pTrel (reconstructed µ)   pTrel (generated but not reconstructed µ) Use generated e + µ w.r.t. reconstructed jets I. Ripp-Baudot (IReS Strasbourg)

  10. c-background : MC Samples : MC p10.15 QCD pT>20, 40, 80 GeV/c Generated muon pTrel distributions : pT(m) 5-7 GeV/c pT(m) 7-10 GeV/c pT(m) 10-15 GeV/c pT(m) > 15 GeV/c I. Ripp-Baudot (IReS Strasbourg)

  11. light-background : data MC : very few light quark  reconstructed Muonid use Gtracks in data, pT > 5 GeV/c, associated to jets (have checked : Muonid and Gtrack are identical) Sample : jet triggers run 158…-162… Gtrack pTrel distributions : pT(m) > 15 GeV/c pT(m) 5-7 GeV/c pT(m) 7-10 GeV/c pT(m) 10-15 GeV/c I. Ripp-Baudot (IReS Strasbourg)

  12. Let’s try to fit the data… Samples : muon+jet, p11 runs 158…-162… Muonid pTrel distributions : b = 28 % b = 23 % b = 4 % b = 35 % pT(m) 5-7 GeV/c pT(m) 7-10 GeV/c pT(m) 10-15 GeV/c pT(m) > 15 GeV/c Fit : ( p0 [b] + p1 [c] ) x MC-correction + p2 [light] b, c, light contributions = free norm. with fixed shapes I. Ripp-Baudot (IReS Strasbourg)

  13. Prospects Cross-checks/improvements : study sensitivity to (jet), pT(jet), R cuts ; study cµ / light quark separation. Use the muon+jet events to estimate the efficiency/purity of the impact parameter b-tagging method. Combine impact parameter and muon pTrel in a likelihood b-tagging. I. Ripp-Baudot (IReS Strasbourg)

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