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S. MuanzaSimulation Meeting 16 September 2005 Relative Tuning of the Pythia Underlying Event for Recent PDFs OUTLINE I.Introduction and Methodology II.Tools.

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Presentation on theme: "S. MuanzaSimulation Meeting 16 September 2005 Relative Tuning of the Pythia Underlying Event for Recent PDFs OUTLINE I.Introduction and Methodology II.Tools."— Presentation transcript:

1 S. MuanzaSimulation Meeting 16 September 2005 Relative Tuning of the Pythia Underlying Event for Recent PDFs OUTLINE I.Introduction and Methodology II.Tools utilized III.Comparison Method IV.Current Results V.Prospects

2 S. MuanzaSimulation Meeting 16 September 2005 I. Introduction A quite detailed study of the underlying event has been performed by Rick Field a theorist working in the CDF collaboration (http://www.phys.ufl.edu/~rfield/cdf/rdf_talks.html)http://www.phys.ufl.edu/~rfield/cdf/rdf_talks.html This study has been sustained for more than 5 years Working definition of the Underlying Event: All but the hard scattering process ie: beam-beam remnants (spectator partons), plus possible ISR gluon radiations, plus the possible Multiple Parton Interactions (MPI) Systematic comparisons of CDF Run I data (min.bias and soft jets) to different MC models have been performed and finally led to a tuning of Pythia underlying event model:

3 S. MuanzaSimulation Meeting 16 September 2005 I. Introduction First StepSecond Steps Pythia Version 6.1156.206 PDF CTEQ4LCTEQ5L Tuning Name “““Tune 0”””Tune A, B, C, D MSTP Values MSTP(81)=1 (MPI on) MSTP(82)=4 (dble gauss. had. matter dens.) MSTP(81)=1 MSTP(82)=4 PARP Values PARP(82)=2.4 (MPI pT cut-off) PARP(67)=4.0;PARP(82)=2.0 PARP(83)=0.5;PARP(84)=0.4 PARP(85)=0.9;PARP(86)=0.95 PARP(89)=1800.0;PARP(90)=0.25 Usage at D0mcp10-mcp14 cardfiles/np/v 00-02-01 to v 00-04-58 mcp14 cardfiles/np/v 00-04-59 to v00-08-53 cardfiles/dzero/v 00-05-01 to v 00-08-53

4 S. MuanzaSimulation Meeting 16 September 2005 I. Introduction This tuning is PDF dependent (http://cepa.fnal.gov/patriot/mc4run2/MCTuning/run2mc/R_Field.pdf)http://cepa.fnal.gov/patriot/mc4run2/MCTuning/run2mc/R_Field.pdf This tuning fits CDF Run IIA min.bias+soft jets data Provided decent choice for the renormalization scales, this tuning also fits the UE for the bbbar, di-photon, Z+jets processes (http://www.phys.ufl.edu/~rfield/cdf/RickField_Workshop_6-11-04.pdf)http://www.phys.ufl.edu/~rfield/cdf/RickField_Workshop_6-11-04.pdf

5 S. MuanzaSimulation Meeting 16 September 2005 I. Methodolgy Since the UE tuning is PDF dependent it should in principle be redone whenever changing from the “reference PDF” (CTEQ5L for Tune A) However this is obviously cumbersome since it requires correcting either the data or the detailed MC and re-doing the full tuning procedure each time I propose instead to start from a reference (CTEQ5L for Tune A) that was properly tuned to data and just to reproduce its UE properties This only requires generator level or fast simulation scan over the UE parameters: whatever set of parameters that reproduces the reference UE constitutes the relative UE tuning for a given PDF I assume the p/pbar hadronic matter is described by a double gaussian (MSTP(82)=4 as in Tune A), so I’m left w/ scanning “only” over 7 PARP parameters (67,82-86,90) since PARP(89)=1800.0 keeps its fixed value (all the evolutions to another CoM energy are internally treated within Pythia)

6 S. MuanzaSimulation Meeting 16 September 2005 I. Methodolgy UE ParameterMinMaxScan StepDefault PARP(67)1.04.01.0 PARP(82)1.82.10.12.0 PARP(83)0.40.60.10.5 PARP(84)0.30.50.10.2 PARP(85)0.331.00~0.330.33 PARP(86)0.331.00~0.330.66 PARP(90)0.200.300.050.16 Scan over the UE Parameters This scan contains 3888 different PARP configurations

7 S. MuanzaSimulation Meeting 16 September 2005 II. Tools Utilized Generator: Pythia v6.320 PDF Library: LHAPDF v4.0 Fast detector simulation: ATLFAST v2.60 (Atlas Collaboration), including smeared tracks and jets Events production: Process: Pythia minbias  MSEL=2  MSUB(91-95)  elastic scattering+ diffraction + low pT QCD, w/ pT* > 0 GeV Note: the soft jets part is not yet produced (  MSEL=1, w/ pT* > 5 GeV) Statistics: 25k / sample (ie per PDF/ & per PARP combination) PDF: ref. sample: CTEQ5L (LO fit & LO  S ) compar. sample: CTEQ6LL, ALEKHIN02LO, MRST01LO (LO fit & LO  S ) CTEQ6L (LO fit & NLO  S )

8 S. MuanzaSimulation Meeting 16 September 2005 Events selection: Similar to R. Field's: events w/ 1 or 2 jets, pT(jets)> 0 GeV, |eta(jets)|<2.0 The transverse plane is divided into 4 regions: towards: |  (ojbect,leading jet)|<60° away: |  (ojbect, leading jet)|>120° (only for 2 jet events) transverse regions: 60°<|  (ojbect,leading jet)|<120° Look at tracks w/ pT(tracks)>0.5 GeV and |eta(tracks)|<1.0 in the transverse regions Construct 2-D histos: Ntracks/  /  1 GeV) vs leading jet pT  pT/  /  1 GeV) vs leading jet pT (scalar pT sum) Differences wrt R. Field: I used "calorimeter jets" instead of “track jets” => pT(jets)>6 Gev instead of 0 GeV Note: the overall efficiency is rather low (~12%) and since I did not write any filter for the produced events, the comparisons are only based on a KS test of two 2-D histos w/ ~3 k entries!!! II. Tools Utilized

9 S. MuanzaSimulation Meeting 16 September 2005 Charged Particle  Correlations Look at charged particle correlations in the azimuthal angle  relative to the leading charged particle jet. Define |  | < 60 o as “Toward”, 60 o < |  | < 120 o as “Transverse”, and |  | > 120 o as “Away”. All three regions have the same size in  -  space,  x  = 2x120 o = 4  /3.

10 S. MuanzaSimulation Meeting 16 September 2005 Tuned PYTHIA 6.206 vs HERWIG 6.4 “TransMAX/MIN” vs P T (chgjet#1) Plots shows data on the “transMAX/MIN” and “transMAX/MIN” vs P T (chgjet#1). The solid (open) points are the Min-Bias (JET20) data. The data are compared with the QCD Monte-Carlo predictions of HERWIG 6.4 (CTEQ5L, P T (hard) > 3 GeV/c) and two tuned versions of PYTHIA 6.206 (P T (hard) > 0, CTEQ5L, PARP(67)=1 and PARP(67)=4).

11 S. MuanzaSimulation Meeting 16 September 2005 III. Comparison Method Histo Comparisons: for each PARP configuration and for each PDF, the two 2-D histos are compared using a 2-D Kolmogorov-Smirnov test to those of the ref. sample (just the shapes enter the comparison, not the normalizations) Global probability: the probability assigned to each comparison sample is simply the product [1] of the individual probability of comparing on one hand the charged tracks density and on the other hand the pTsum density Tools: all the histos and comparison methods are taken from ROOT v4.04.02b Valid if & only if var1 and var2 are not correlated!!! Have to calculate a conditional probability if var1 and var2 are correlated!!!

12 S. MuanzaSimulation Meeting 16 September 2005 IV. Current Results PDF: ALEKHIN02LO LO fit and LO  S 3881/3888 configs UE ParameterBestWorstCTEQ5L Tune A PARP(67)FLAT 4.0 PARP(82)2.01.82.0 PARP(83)0.60.40.5 PARP(84)0.30.4 PARP(85)0.660.330.9 PARP(86)0.33-0.661.00.95 PARP(90)0.30 0.25 Max(P KS )=0.967 008 (8 max configs) Min(P KS )=2.058x10 -10 (4 min configs)

13 S. MuanzaSimulation Meeting 16 September 2005 IV. Current Results PDF: MRST01LO LO fit and LO  S 3820/3888 configs UE ParameterBestWorstCTEQ5L Tune A PARP(67)FLAT 4.0 PARP(82)1.801.902.0 PARP(83)0.60.40.5 PARP(84)0.30.50.4 PARP(85)1.00.330.9 PARP(86)FLAT1.00.95 PARP(90)0.20 0.25 Max(P KS )=0.956524 (12 max configs) Min(P KS )=4.433x10 -11 (4 min configs)

14 S. MuanzaSimulation Meeting 16 September 2005 IV. Current Results PDF: CTEQ6L LO fit and NLO  S 3867/3888 configs UE ParameterBestWorstCTEQ5L Tune A PARP(67)FLAT 4.0 PARP(82)2.101.802.0 PARP(83)0.60.40.5 PARP(84)0.50.4 PARP(85)1.00.330.9 PARP(86)FLAT1.00.95 PARP(90)0.250.300.25 Max(P KS )=0.954313 (12 max configs) Min(P KS )=2.924x10 -10 (4 min configs)

15 S. MuanzaSimulation Meeting 16 September 2005 IV. Current Results PDF: CTEQ6LL aka CTEQ6L1 LO fit and LO  S 3886/3888 configs UE ParameterBestWorstCTEQ5L Tune A PARP(67)FLAT 4.0 PARP(82)2.00 2.0 PARP(83)0.4 0.5 PARP(84)0.50.4 PARP(85)1.00.330.9 PARP(86)FLAT1.00.95 PARP(90)0.200.300.25 Max(P KS )=0.977060 (12 max configs) Min(P KS )=1.815x10 -11 (4 min configs)

16 S. MuanzaSimulation Meeting 16 September 2005 IV. Current Results ref best worst « same » Example w/ Alekhin 2002 LO PDF H T (GeV)

17 S. MuanzaSimulation Meeting 16 September 2005 IV. Current Results ref best worst « same » mET (GeV)

18 S. MuanzaSimulation Meeting 16 September 2005 IV. Current Results ref best worst « same » N(jets)

19 S. MuanzaSimulation Meeting 16 September 2005 IV. Current Results ref best worst « same » Total N(tracks)

20 S. MuanzaSimulation Meeting 16 September 2005 IV. Current Results After fixing the correlation issue: Attaching file plots.root as _file0... root [1] h2_hist1_mix0->GetCorrelationFactor(1,2) (const Stat_t)1.22289661104907951e-01 root [2] h2_hist1_mix1->GetCorrelationFactor(1,2) (const Stat_t)8.79092032677424529e-01 root [3] h2_hist2_mix0->GetCorrelationFactor(1,2) (const Stat_t)1.18224432124161408e-01 root [4] h2_hist2_mix1->GetCorrelationFactor(1,2) (const Stat_t)8.23833825978842360e-01 The correlation coefficient drops from 80% downto 12% This makes the marginal probabilities product an acceptable approximation Var1  pT/Ntracks)/  /  1 GeV) Var1  pT/  /  1 GeV)Var2  Ntracks/  /  1 GeV)

21 S. MuanzaSimulation Meeting 16 September 2005 VI. Conclusions & Prospects Conclusions: There are flat directions (as expected in multivariate analyses, especially w/ coarse scans and limited statistics). In this case I propose to pick the PARP value which is the closest to the reference one (CTEQ5L+Tune A) As expected the shape of the so-called “best” configuration (green histos) is the closest to that of the reference (black histos). This demonstate that there is a measurable difference between different UE settings for a given PDF and that the UE is PDF-dependent. Prospects: Produce the low pT QCD samples Add them to the 2-D histos for the comparisons Couple of additional cross checks Increase the statistics

22 S. MuanzaSimulation Meeting 16 September 2005 VI. Prospects Produce the low pT QCD samples Add them to the 2-D histos for the comparisons Couple of additional cross checks Increase the statistics

23 S. MuanzaSimulation Meeting 16 September 2005 Back Up

24 S. MuanzaSimulation Meeting 16 September 2005 Pythia UE Parameters Definition UE ParameterDefinition MSTP(81) MPI on/off MSTP(82) 3 / 4: resp. single or double gaussian hadronic matter distribution in the p / pbar PARP(67) ISR Max Scale Factor PARP(82) MPI pT cut-off PARP(83) Warm-Core: parp(83)% of matter in radius parp(84) PARP(84) Warm-Core: ” PARP(85) prob. that an additional interaction in the MPI formalism gives two gluons, with colour connections to NN in momentum space PARP(86) prob. that an additional interaction in the MPI formalism gives two gluons, either as described in PARP(85) or as a closed gluon loop. Remaining fraction is supposed to consist of qqbar pairs. PARP(89) ref. energy scale PARP(90) energy rescaling term for PARP(81-82)~E CM ^PARP(90)

25 S. MuanzaSimulation Meeting 16 September 2005 VI. Final Checks on Shapes

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