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Run-11 Transverse Jets: PYTHIA vs. NLO
NOTE: I have added another update examining PYTHIA vs. NLO for the embedding sample. They provide a much better comparison at high pT, revealing an apparent constant offset of ~1.6 in the PYTHIA vs. NLO ratios. Thus, one should consider that study prior to interpreting too deeply what one sees at high pT in the present blog.
Carl suggested that it might be informative to see how well the PYTHIA parton-jet and particle-jet cross sections agree with NLO pQCD. It is possible that the data-simulation discrepancies in low-pT JP0 triggers are simply the result of PYTHIA not perfectly recreating reality. For the comparison I have generated 3M pure PYTHIA events (partonic pT > 2 GeV/c) following Pibero's procedure for the 2009 analysis. I, then, ran the standard jet finder at the particle-jet and parton-jet levels using the anti-kT algorithm with radius of 0.6. The events are weighted by the total cross section (34.97 mb) divided by the total number of generated events (3e6). To compare to Zilong's NLO calculation, I further scale by 0.5 to divide out the eta range of |η| < 1. The results of the comparison are shown in Fig. 1. As a word of caution, the statistics for partonic pT > 15 GeV/c are very, very sparse. Thus, one should not put too much stock in the cross sections for high jet pT.
Figure 1
There is clearly a discrepancy between PYTHIA and NLO pQCD at low-pT. The low-pT PYTHIA cross sections are enhanced both for parton jets and particle jets. This is qualitatively similar to what Pibero observed at 200 GeV (see Fig. 2 of the 2009 inclusve jet analysis note). At pT = 7 GeV/c I find the PYTHIA cross sections larger than NLO by a factor of 2 and at 8 GeV/c by a factor of 1.8. In the 7.1-8.4 GeV/c bin for reconstructed jets, I find a Data/M.C. ~ 0.57 (while normalizing to the number of data counts in the range 11.7-55 GeV/c). Thus, assuming the normalization is not completely crazy, the enhancement in the PYTHIA jet cross sections relative to NLO may play a large role in the discrepancy between data and embedding.
PYTHIA Details
- PYTHIA 6.426
- pythia->SetMSEL(1); // QCD jets
- pythia->SetCKIN(3,2); // Lower partonic pT bound in GeV
- pythia->SetCKIN(4,-1); // Higher partonic pT bound in GeV
- pythia->SetMSTP(5,320); // Perugia 0 tune
- pythia->SetMDCY(102,1,0); // PI0 111
- pythia->SetMDCY(106,1,0); // PI+ 211
- pythia->SetMDCY(109,1,0); // ETA 221
- pythia->SetMDCY(116,1,0); // K+ 321
- pythia->SetMDCY(112,1,0); // K_SHORT 310
- pythia->SetMDCY(105,1,0); // K_LONG 130
- pythia->SetMDCY(164,1,0); // LAMBDA0 3122
- pythia->SetMDCY(167,1,0); // SIGMA0 3212
- pythia->SetMDCY(162,1,0); // SIGMA- 3112
- pythia->SetMDCY(169,1,0); // SIGMA+ 3222
- pythia->SetMDCY(172,1,0); // Xi- 3312
- pythia->SetMDCY(174,1,0); // Xi0 3322
- pythia->SetMDCY(176,1,0); // OMEGA- 3334
- pythia->Initialize("cms","p","p",500); // p+p collisions at sqrt(s)=500 GeV
- pythia->SetMSTP(51,7);
- pythia->SetMSTP(52,1);
Example PYSTAT Output
********* PYSTAT: Statistics on Number of Events and Cross-sections ********* ============================================================================== I I I I I Subprocess I Number of points I Sigma I I I I I I----------------------------------I----------------------------I (mb) I I I I I I N:o Type I Generated Tried I I I I I I ============================================================================== I I I I I 0 All included subprocesses I 10000 87280 I 3.507D+01 I I 11 f + f' -> f + f' (QCD) I 429 3575 I 1.417D+00 I I 12 f + fbar -> f' + fbar' I 3 21 I 1.385D-02 I I 13 f + fbar -> g + g I 9 37 I 1.997D-02 I I 28 f + g -> f + g I 3709 37885 I 1.311D+01 I I 53 g + g -> f + fbar I 136 741 I 5.232D-01 I I 68 g + g -> g + g I 5714 45021 I 1.998D+01 I I I I I ============================================================================== ********* Total number of errors, excluding junctions = 0 *************
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