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Status of NLOjet++ for dijet angular distributions

Status of NLOjet++ for dijet angular distributions. Lee Pondrom University of Wisconsin 20 May 2010. Ingredients. 1.1 fb -1 jet100 triggered data 1E10 nlojet++ events with CTEQ6 2E6 Pythia events with full CDFSim and CTEQ5

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Status of NLOjet++ for dijet angular distributions

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  1. Status of NLOjet++ for dijet angular distributions Lee Pondrom University of Wisconsin 20 May 2010

  2. Ingredients • 1.1 fb-1 jet100 triggered data • 1E10 nlojet++ events with CTEQ6 • 2E6 Pythia events with full CDFSim and CTEQ5 • 1E6 ‘standalone’ Pythia events with CTEQ6 and ISR, FSR turned off.

  3. Pythia first • We have to use Pythia to correct the data to the hadron level. • We use a calculation of the subprocess cross sections to understand Pythia. • We learn that to reproduce the Pythia angular distributions, the 2->2 subprocesses with nonidentical final state partons must be u<->t symmetrized.

  4. 2->2 symmetirzed jet_chi cross sections 600 GeV mass bin

  5. Key to previous slide • q1q2->q1q2 t channel gluon exchange • q1q2bar->q1q2bar t channel gluon* • q1q1->q1q1 t channel gluon • q1q1bar->q2q2bar s channel annihilation • q1q1bar->q1q1bar s and t channels* • q1q1bar->glueglue s channel annihilation • glueglue->q1q1bar/glueglue* s and t • q1glue->q1glue compton* *=large 

  6. 2->2 subprocesses • The peaks at =1 come from the u<->t symmetrization • The t channel gluon exchange cross sections dominate, which is the motivation for the choice of scale Q2=pT2. • Now that we understand Pythia born, let us look at nlojet++ born

  7. 2->2 Pythia compared to Nlojet born and jet_chi

  8. 2->2 Pythia compared to Nlojet born and jet_chi

  9. Normalization • Each set of four mass plots has one overall normalization. • All programs agree on the 1/mass4 dependence of the cross section. • Nlojet++ born agrees better with Pythia as the mass increases.

  10. conclusion • We understand Pythia. It agrees well with the data, and strengthens the Pythia based quark substructure analysis. • To compare nlojet++ to the data, we need to correct the data to the hadron level using Pythia

  11. Nlojet++ has no CDF trigger • After jet energy corrections the 100 GeV trigger moves to about 125 GeV • ET= M/(1+)=(Msin(*))/2 which has to be removed, in addition to other instrumental effects.

  12. 125 GeV trigger threshold cut in the angular distribution

  13. Correct the data to the hadron level using Pythia MC

  14. Correct the data to the hadron level using Pythia MC

  15. Corrected data agree well with hadron level Pythia Q2=pT2

  16. Corrected data agree well with hadron level Pythia Q2=pT2

  17. 2 for hadron level data compared to Q2=pT2 Pythia noqsub • 20 bins one parameter fits • M (GeV) events (data) 2 • 600 150343 32 • 700 42106 38 • 800 11392 17 • 900 3134 17

  18. Jet-jet angular distribution and quark substructure • Quark substructure effective contact color singlet Lagrangian of Eichten, et al is: • L = ±(g²/2Λ²(LLLL • Looks just like muon decay. Affects only the u and d quarks. Color singlet means that some diagrams have no interference term. • g²/4 = 1; strength of the interaction ~(ŝ/²)² • This measurement is not sensitive to the interference term. _ _ _

  19.  Dependence of the angular distributions

  20.  Dependence of the angular distributions

  21. Plot the ratio R=(1<<7)/(7<<13) vs (mass)4 for each

  22. Fitted slopes vs (1/4) give sensitivity to quark substructure

  23. Run nlojet++ 1010 events 0=ETavge

  24. Vary 0 in NLOjet++

  25. Fit nlojet++ to hadron level data

  26. 2 for one parameter fits to first 12 bins of data with nlojet++ • Mass GeV 0=Etav 0.7Etav 1.4Etav • 600 75 110 78 • 700 75 48 65 • 800 36 48 35 • 900 37 35 37 • No fit is particularly good, compared to Pythia

  27. Compare lo and nlo 0=ETaveK factor 1.1

  28. Cuts in nlojet++ • For 2 partons with highest ET • ET>10 GeV • ||<2 • Cone size D=0.7 in (,) space • Rsep = 1.3. D and Rsep govern when the third parton is included with one of the other two to form a ‘jet’. Should have no effect on a born calculation.

  29. Systematics • Calculate R(Nlojet++) for 0=ETave, 0.7 ETave, and 1.4ETave. • Calculate R(data) for level7JetE corrections, and 1 on JetE corrections • Average the results <R(data)> and <R(Nlojet)>

  30. Table • M(GeV) R(data) R(nlojet) ratio • 600 .815.017 .818.009 1.0.02 • 700 .87.02 .81.01 1.07 .02 • 800 .85.05 .82.02 1.04.06 • 900 .92.09 .83.02 1.1.1 • Fitted slope s=0.160.07, intersept=1.0, 2=2.3

  31. R(data)/R(Nlojet++) vs (mass)4

  32. Conclusions • The original Pythia based analysis has been repeated, with the following changes. • Only Pythia with Q2=pT2 used. • Data corrected to hadron level with Pythia • Sensitivity to quark substructure uses Pythia integrated over smaller regions in  to accommodate Nlojet++.

  33. Conclusions continued • Systematics are included in the comparison of data to nlojet++ by varying the jet energy corrections in data and the hard scale 0 in nlojet++. •  limit from the fitted slope: >2.1 TeV 95% confidence. • Expected limit for zero slope is >2.6 TeV 95% confidence.

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