1. A measurement of the Ratio of Tree over Two Jet Cross Sections with CMS at 7TeV P.Kokkas, I.Papadopoulos, C.Fountas, I.Evangelou, N.Manthos University of Ioannina, Greece Senior Editor for PAS : James Rohlf Boston University, USA

2. Outline Motivation Monte Carlo studies Studies on rapidity Leading jets p T response and resolution H T resolution MC prediction for ratio R 32 Data analysis Data and MC samples Online Selection and Trigger studies Offline Selection Extraction of ratio R 32 from data Studies on Systematics Summary 2P.Kokkas, Univ. of Ioannina

3. Motivation Motivation: Measure the ratio R 32 and compare with pQCD predictions with goals: Extend the phase space of the measurement in a regime that goes above the Tevatron. Measure  S : Comparisons of the measured ratio at hadron level with the predictions of pQCD (parton level), after accounting for hadronisation corrections uncertainty, will measure the QCD coupling constant  S at a scale never measured before. We measure the ratio because we expect that certain systematic uncertainties will cancel: The dominant sources of systematic uncertainties in the measurement of jet inclusive cross sections are the Luminosity and the Jet Energy Scale (JES). We expect the ratio to be less sensitive than absolute cross section measurements to these uncertainties. The pQCD predictions for the ratio may be less sensitive to uncertainties due to the renormalization and factorization scales which hamper the absolute cross section predictions particularly at low Jet-p T scales. D0 PRL 86, p1955 (2001) 3P.Kokkas, Univ. of Ioannina

4. Monte Carlo models and studies MC samples PYTHIA : /QCDDiJet_Ptxxtoxx/Spring10-START3X_V26_S09-v1/GEN-SIM-RECO Madgraph : /QCD_Ptxxtoxx-madgraph/Spring10-START3X_V26_S09-v2/GEN-SIM-RECO 4 PYTHIA6Madgraph LO processesLO matrix element 2→2 hard process Tree Level helicity amplitudes + Parton shower (PS) model Higher order processes Parton shower (PS) model HadronizationLund string model Parton Distribution (PDF) Model CTEQ6L1 Jets were reconstructed using the antikt (D=0.5) clustering algorithm. CaloJets : using antkt5 on calorimeter energy depositions GenJets : using antikt5 on MC stable particles. Calo jets were corrected for energy loss and effects due to non-linear response of calorimeter Relative (corrects for η dependence) Absolute (corrects for the p T dependence) P.Kokkas, Univ. of Ioannina

5. Plot the difference For various bins of GenJet p T Distributions flat for |y|≤2.5 (Barrel + EndCap regions) Reasonable cut: |y|≤2.5 Studies on rapidity 5 60-100 GeV 100-150 GeV 150-200 GeV P.Kokkas, Univ. of Ioannina Contour PlotProfileY Projection PYTHIA

6. Leading Jets p T Response 6 Fitting above distribution to a Gaussian, we extract p T Response and Resolution. The p T Response of leading jets is uniform for jet p T even below 50 GeV. Calo jet corrections work very well. P.Kokkas, Univ. of Ioannina

7. p T Resolution 7 For jet p T about 50 GeV the resolution is ≈15% dropping to ≈10% at 200 GeV. For our analysis we apply a cut on Jet p T ≥50 GeV. With this cut we can compare our results with Tevatron for a region of H T between 300-600 GeV

8. Resolution on H T 8 By accepting all jets with rapidity |y|≤2.5 and p T ≥50 GeV We construct in the case of number of Jets ≥ 2 number of jets ≥ 3 H T resolution studies are important to define the binning for the ratio R 32. nJets≥2nJets≥3 H T resolution: ≈10% at 200 GeV dropping to ≈5% at 1000 GeV P.Kokkas, Univ. of Ioannina PYTHIA

9. MC predictions for R 32 9 The ratio R 32 starts at 150 GeV, rises fast ad reach to a plato at ≈800 to 1000 GeV. Madgraph is systematically lower than PYTHIA by as much as 30% in the lower H T bins. This difference decreases to ≈10% around 400 GeV and becomes smaller than 5% at higher H T bins. The cross section predicted by Madgraph is consistently ≈30% lower than PYTHIA’s. PYTHIAMadgraph

10. Data Analysis Data Samples /MinimumBias/Commissioning10-SD_JetMETTau-v9/RECO /JetMETTau/Run2010A-May27thRereso_v1/RECO JSON file CMS official JSON file : Cert_132440-136297_7TeV_StreamExpress_Collisions10_JSON.txt But for Runs > 134630 (Trigger scheme 6) Total Integ.Lumi = 10.8 nb -1 (Evaluated from crab) Trigger Samples /MinimumBias/Commissioning10-SD_JetMETTauMonitoring-v9/RECO /JetMETTauMonitoring/Run2010A-May27thRereso_v1/RECO /MinimumBias/Commissioning10-May27thReReco_v1/RECO (MinBias Studies) MC Samples PYTHIA: QCDDiJet_Ptxxtoxx/Spring10-START3X_V26_S09-v1/GEN-SIM-RECO Madgraph: QCD_Ptxxtoxx-madgraph/Spring10-START3X_V26_S09-v1/GEN-SIM-RECO 10 On line Selection: Require BPTX Technical bit 0, to select events with consistent timing with LHC bunch crossing None of the BSC beam halo triggers (Technical bits 36,37,38,39) Select events with HLT Jet15U P.Kokkas, Univ. of Ioannina

11. Online Selection - Trigger 11 HLT Jet TriggerL1 PrerequisitePrescaled HLT L1Jet6UL1 SingleJet6Uyes HLT Jet15UL1 SingleJet6Uno HLT Jet30UL1 SingleJet20Uno HLT Jet50UL1 SingleJet30Uno Main HLT Jet Triggers Trigger efficiencies vs HLT MinBiasBSC. HLT L1Jet6U turn on point well in advance, can be used for calculating efficiencies. HLT Jet15U Trigger efficiency with HLT L1Jet6U and HLT MinBiasBSC – complete agreement, P.Kokkas, Univ. of Ioannina

12. Online Selection - Trigger P.Kokkas, Univ. of Ioannina12 Safe to use HLT Jet15U for our analysis Turn on points for simulation is systematically higher. 12 HLT Jet TriggerTurn on points (GeV) Leading Jet HLT Jet15U37 HLT Jet30U62 HLT Jet50U87 Data PYTHIA

13. Online Selection - Trigger 13P.Kokkas, Univ. of Ioannina HLT Jet Trigger H T nJets≥2 (GeV) H T nJets≥3 (GeV) HLT Jet15U100150 HLT Jet30U120150 HLT Jet50U230 HLT Jet15U : R 32 can be measured for H T ≥150GeV. HLT Jet30U : Practically the same as above HLT Jet50U : R 32 can be measured for H T ≥230GeV. The “kink” appearing to HLT Jet50U at ≈150GeV (left plots), is due to events with three jets of almost equal p T which do not pass the trigger HLT Jet50U. nJets ≥2 Data nJets ≥2 PYTHIA nJets ≥3 Data nJets ≥2 PYTHIA

14. Off Line Selection and Data Stability 14 Off line Selection: Removal of “monster” events Primary Vertex: |PVz| 4 Jet selection: p T ≥ 50 GeV and |y|≤2.5 “Loose” Jet ID : EMF > 0.01 OR |η|>2.6, n90Hits > 1, FHPD < 0.98 SelectionEvents Trigger, Data quality &PV1508800 After p T ≥50GeV, |y|≤2.5 & ‘’Loose” JetID At least 2 jets24823 At least 3 jets1418 Data stability : Flat distributions of number of events normalized with run lumi vs run number. Run Numbers 135537, 135573, 136080,136098 and 136119 (marked with the arrows) represent to a small amount of Lumi ≈0.14 nb -1. nJets ≥2 nJets ≥3 P.Kokkas, Univ. of Ioannina

15. Data Stability P.Kokkas, Univ. of Ioannina15 Data stability : Flat distribution of ratio Number of events with (njets≥3 )/(njets ≥2) vs run number. Run Numbers 135537, 135573, 136080, 136098 and 136119 (marked with the arrows) represent to a small amount of Lumi ≈0.14 nb -1. We also tried to normalize the last runs with a MinBias trigger ( eg. HLT_L1_BscMinBiasOR_BptxPlusOR Minus ) but was not possible from point of statistics since these runs are very small.

16. All jets: Data over PYTHIA P.Kokkas, Univ. of Ioannina16 Good agreement with simulation. Small differences in shape for f HPD and N90Hits, not important for our analysis. PYTHIA MC normalized to the total number of inclusive DiJet events. The effect of the “loose” JetID selection is ≈0.3%.

17. Leading Jets: Data over PYTHIA 17 PAS PYTHIA MC normalized to the total number of inclusive DiJet events. PYTHIA describes well the shape of the data distributions

18. All jets: Data over Madgraph P.Kokkas, Univ. of Ioannina18 Good agreement with simulation. Small differences in shape for f HPD and N90Hits, not important for our analysis. Madgraph MC normalized to the total number of inclusive DiJet events.

19. Leading Jets: Data over Madgraph 19 PAS Madgraph MC normalized to the total number of inclusive DiJet events. Madgraph describes well the shape of the data distributions

20. Number of Jets (Not in the PAS but requested) 20 PYTHIA and Madgraph MC normalized to the total number of inclusive DiJet events. P.Kokkas, Univ. of Ioannina

21. Method of extracting R 32 P.Kokkas, Univ. of Ioannina21 Inclusive jet cross section Ratio R 32 A B measurement The factor AxB has been used to correct the Calo Level ratio to stable particle level (Hadron Level).

22. Method of extracting R 32 P.Kokkas, Univ. of Ioannina22 1/ε 3 (1/efficiency) nJets≥3 C Smear3 Smearing correction nJets≥3 ε 2 (efficiency) nJets≥2 1/C Smear2 Smearing correction nJets≥2 With This MC driven method of extracting R 32 from the data does not depend upon the absolute predictions of the MC programs. It does depend on how well the MC distributions describe the shape of the data distributions. As we have seen in the previous slides both PYTHIA and Madgraph describe well the shapes of the data distributions, hence we are entitle to use them to derive the AXB correction factors to the data.

23. Closure test 23P.Kokkas, Univ. of Ioannina PYTHIA MC events were considered as “data” (top left). Madgraph MC events were considered as “MC” and used to evaluate factor AxB (bottom left). Then with AxB from Madgraph, PYTHIA CaloJets were corrected and compared with GenJets from PYTHIA (top right). The corrected PYTHIA CaloJet ratio (with AxB from Madgraph) is within ±5% from the GenJet ratio except the first bin which is off by ≈10%. AxB from Madgraph PYTHIA PYTHIA Corrected

24. Ratio R 32 at Calo level 24 Data over PYTHIAData over Madgraph High R 32 bins merged to match statistics. AxB factors evaluated with new binning. AxB from PYTHIA CaloJets P.Kokkas, Univ. of Ioannina

25. Ratio R 32 at Hadron Level 25P.Kokkas, Univ. of Ioannina Measured ratio rises with H T in the range 150≤H T ≤800 GeV in agreement with predictions of PYTHIA and Madgraph. PAS

26. Studies on the Systematic uncertainties. P.Kokkas, Univ. of Ioannina26 Studies on Systematics Jet Energy Scale (JES) systematics Absolute scale : flat 10% JES uncertainty Relative scale : 2% for every unit of pseudorapidity Systematic uncertainty due to difference in shape between data and MC Reweight the p T and H T spectra so that the shape of distributions changes and repeat the analysis to compute systematic. Systematic uncertainty due to detector response Smearing Calo Jets by 10% and 15% while leaving Hadron jets unchanged.

27. Jet Energy Scale (JES) systematics : Absolute Scale 27 The p T ≥50 GeV/c cut modulates the efficiency at low H T Above 400 GeV we observe a rather flat distribution shifted by 50% to 80% P.Kokkas, Univ. of Ioannina Absolute scale : flat 10% JES uncertainty

28. Jet Energy Scale (JES) systematics : Absolute Scale 28 Smearing effects dominate P.Kokkas, Univ. of Ioannina We observe a strong uncertainty cancellation (uncertainty less than 5%). For the first two bins bellow 200 GeV systematics are of the order of 10%. Absolute scale : flat 10% JES uncertainty

29. Jet Energy Scale (JES) systematics : Relative Scale P.Kokkas, Univ. of Ioannina29 Relative scale : 2% for every unit of pseudorapidity This results to a systematic uncertainty which is significantly small than the previous.

30. Systematic uncertainty due to difference in shape between data and MC No reweight nJets≥2 Pythia with harder p T spectrum nJets≥2 Pythia with softer p T spectrum nJets≥2 No reweight nJets≥3 Pythia with harder p T spectrum nJets≥3 Pythia with softer p T spectrum nJets≥3 To see how sensitive we are to smearing corrections we assume that the detector response is correct in the MC and we change the underline physics by reweighting and we observe the change in the measured ratio due to different smearing effects. Reweight the p T and H T spectra so that the shape of distributions changes and repeat the analysis to compute systematic. 30

31. Systematic uncertainty due to difference in shape between data and MC P.Kokkas, Univ. of Ioannina31 This uncertainty, while probably over-estimated, is of the same order of the JES uncertainty.

32. Systematics due to detector response P.Kokkas, Univ. of Ioannina32 Smearing Calo Jets by 10% or 15% while leaving Hadron jets unchanged. 10% Smearing 15% Smearing With 10% smearing MC shape describes data better. We plot :

33. Systematics due to detector response : smearing by 10% P.Kokkas, Univ. of Ioannina33 Results consistent with previous studies. Uncertainty ≈5%, except the first two bins bellow 200 GeV where uncertainty is of the order of 10%. Smearing Calo Jets by 10% while leaving Hadron jets unchanged.

34. Systematics due to detector response : smearing by 15% P.Kokkas, Univ. of Ioannina34 Smearing Calo Jets by 15% while leaving Hadron jets unchanged. Results consistent with previous studies. Uncertainty ≈5%, except the first two bins bellow 200 GeV where uncertainty is of the order of 10%.

35. Summary Summary: The ratio of the inclusive three-jet over two-jet cross sections as a function of the total jet transverse energy, H T, has been measured with the CMS detector at the LHC for proton-proton center-of-mass energy 7 TeV using an integrated luminosity of 10.8 nb -1. Measurements have been performed for jets with p T ≥50 GeV in the rapidity range |y| ≤2.5. The measured ratio rises with H T in the range 150≤H T ≤800 GeV. The measured ratio is consistent with the predictions of PYTHIA and MadGraph. P.Kokkas, Univ. of Ioannina35

36. Spare 36P.Kokkas, Univ. of Ioannina

37. Gen H T for PYTHIA and Madgraph 37P.Kokkas, Univ. of Ioannina PYTHIAMadgraph The cross section predicted by Madgraph is consistently ≈30% lower than PYTHIA’s

38. Predicted R 32 with various p T – y cuts 38P.Kokkas, Univ. of Ioannina Both Figures demonstrate the influence of the threshold cuts on p T and y to the measurement.

39. Main HLT Jet Trigger efficiencies 39 HLT Jet Trigger L1 PrerequisitePrescaledTurn on points (GeV) Raw p T Turn on points (GeV) corrected p T HLT L1Jet6UL1 SingleJet6Uyes1328 HLT Jet15UL1 SingleJet6Uno1637 HLT Jet30UL1 SingleJet6Uno3260 HLT Jet50UL1 SingleJet6Uno≈53>80 Main HLT Jet Triggers Raw p T Corrected p T

40. Ratio R 32 at Calo level P.Kokkas, Univ. of Ioannina40 CaloJets

41. AxB from PYTHIA and Madgraph P.Kokkas, Univ. of Ioannina41 Correction factors AxB from PYTHIA and Madgraph agrees better than 5%. Except the two first bins where disagreement is ≈10%.

42. Residual Corrections P.Kokkas, Univ. of Ioannina42 According to JEC group a residual correction for η>1.5 is needed (on the top of the Default L2L3). SelectionEvents with Residual Corrections At least 2 jets2482323909 At least 3 jets14181369 The effect is ≈ 3%. Small effect to the measurement.

43. Analysis without JetID selection P.Kokkas, Univ. of Ioannina43 SelectionEvents With ‘’Loose” JetID Events Without ‘’Loose” JetID At least 2 jets2482324891 At least 3 jets14181420 The effect of the “loose” JetID selection is ≈ 0.3%.

44. Full resolution Systematics P.Kokkas, Univ. of Ioannina44 Moving Calo p T cut by 15% (the p T resolution at 50 GeV) while leaving Hadron cut unchanged. Uncertainty probably over-estimated for the lower bins (H T < 400GeV)