Z+jet Comparison to Theory
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Z+jet Comparison to Theory. Kittikul Kovitanggoon a , Sung-Won Lee a , Nural Akchurin a , Jordan Damgov a , Efe Yazgan b , Lovedeep Saini c , Stephan Linn d , Luis Lebolo d , Shin-Shan Yu e , Anil Singh e a Texas Tech University b University of Ghent c Panjab University, India

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Kittikul kovitanggoon a sung won lee a nural akchurin a

Z+jet Comparison to Theory

Kittikul Kovitanggoona, Sung-Won Leea, Nural Akchurina,

Jordan Damgova, Efe Yazganb, Lovedeep Sainic, Stephan Linnd, Luis Lebolod,

Shin-Shan Yue, Anil Singhe

aTexas Tech University

bUniversity of Ghent

cPanjab University, India

dFlorida International University

eNational Central University, Taiwan


Kittikul kovitanggoon a sung won lee a nural akchurin a

Part 1

Z(μμ) + jets

- Kinematics

- MCFM


Data sets z jets

Data sets Z(μμ) + jets

  • Analysis is on 2011 (A +B) Rereco datasets in the total of 4.7 fb-1

    DoubleMu_Run2011A-08Nov2011

    DoubleMu_Run2011B-19Nov2011

  • Using the unprescaled Double Muons HLT

  • MC + BG are Fall11

    - MC

    MADGRAPH

    POWHEG

    SHERPA

    MCFM

  • SHERPA weigh = LumiDATA x X-sectionMC/sumWeightMC

  • SHERPA histograms fill with h->Fill(variable,PU_weight*MC_weight)

  • Only shape comparison with MCFM

- Backgrounds are Fall11 MC

DYToTauTau

QCD

WToMuNu

TT

WW

WZ

ZZ


Kittikul kovitanggoon a sung won lee a nural akchurin a

Di-muon properties for Z+njets

Mμμ

pTμμ

  • All MC give good agreement in Di-muon mass within 10%

  • MADGRAPH give better agreement in Di-muon pT than POWHEG and SHERPA


Kittikul kovitanggoon a sung won lee a nural akchurin a

Di-muon properties for Z+njets

Yμμ

Φμμ

  • MADGRAPH , POWHEG, SHERPA give good agreement in Di-muon Y and Φ


Kittikul kovitanggoon a sung won lee a nural akchurin a

Inclusive Jet Multiplicity

Central region

All regions

  • MADGRAPH provide good comparison in jet multiplicity but SHERPA and POWHEG does not


Kittikul kovitanggoon a sung won lee a nural akchurin a

Di-muon pT and Di-muon Y

of

Z + 1 jet event

Yμμ

pTμμ


Kittikul kovitanggoon a sung won lee a nural akchurin a

Jet pT and Jet Y

Of

Z + 1 jet event

Yjet

pTjet

  • MADGRAPH and POWHEG are good predictions of Z and jet in Z+1jet event

  • SHERPA does bad prediction in kinematic of Z and jet


Kittikul kovitanggoon a sung won lee a nural akchurin a

MCFM Comparison

Di-muon pT and Rapidity

pTμμ

Yμμ


Kittikul kovitanggoon a sung won lee a nural akchurin a

MCFM Comparison

Leading Jet pT and Rapidity

pTjet

Yjet

  • Y shape comparisons to MCFM for both Z and jet show agreement within about 5-10%

  • pT shape comparisons to MCFM for both Z and jet show agreement within about 20%


Kittikul kovitanggoon a sung won lee a nural akchurin a

MCFM Comparison

Rapidity Sum and Difference between Z and Jet

0.5*(YZ+Yjet)

0.5*(YZ-Yjet)

  • SHERPA agrees better in term of rapidity sum and rapidity difference than MADGRAPH


Kittikul kovitanggoon a sung won lee a nural akchurin a

Part 2

Z(ee) + jets

- Kinematic

https://indico.cern.ch/getFile.py/accesscontribId=4&resId=0&materialId=slides&confId=176821

- MCFM


Data sets z ee jets

Data sets Z(ee) + jets


Kittikul kovitanggoon a sung won lee a nural akchurin a

MCFM Comparison

Di-muon pT and Rapidity


Kittikul kovitanggoon a sung won lee a nural akchurin a

  • MCFM Comparison

    Leading Jet pT and Rapidity

  • Y shape comparisons to MCFM for jet show agreement within about 10% but not bad for Z

  • pT shape comparisons to MCFM for both Z and jet show agreement within about 20%


Kittikul kovitanggoon a sung won lee a nural akchurin a

  • MCFM Comparison

    Rapidity Sum and Difference between Z and Jet

0.5*(YZ-Yjet)

0.5*(YZ+Yjet)

  • SHERPA agrees better in term of rapidity sum and rapidity difference than MADGRAPH as we see in Z(μμ) + jet


Kittikul kovitanggoon a sung won lee a nural akchurin a

Conclusions

  • MC generations has their own Pros and Cons

    • MADGRAPH

      • Better agreements in overall kinematics both Z and jets

      • Angular variable (rapidity) between Z and jet is not good agreement

    • POWHEG

      • Good prediction on Z (muons)

      • In term of jet, only give good prediction up to 1 jet but not rapidity

    • SHERPA

      • Better agreement in angular variable (rapidity) in Z+1jet

      • Not so good prediction in term of other variables


Kittikul kovitanggoon a sung won lee a nural akchurin a

Conclusions

  • Madgraph, Sherpa, and MCFM all agree to within 5-20% of the data for pT and Y distributions

  • Sherpa agrees better with data only for the rapidity sum and rapidity difference, but not good particularly for jet pt and jet y, and Z pT

  • ΔY and ΣY should de-correlate matrix elements from PDF'S, but correlations persist.

  • Madgraph agrees with NLO QCD (MCFM)

    Sherpa agrees with the data shape but normalization is wrong**

  • The main difference between Sherpa and Madgraph is the method of matching patron showers to matrix elements to avoid double counting of jets.

    • Madgraph uses MLM

    • Sherpa uses CKKW

Ongoing:

  • We are preparing CMS AN 12-037

  • It would be interesting to see ΔY for photons vs MADGRAPH and SHERPA

**This statements is consistent with the D0 Result   PhysLett b682(2010) p370-380]  D0 did not have MadGraph


Back up

Back Up


Z mumu jets selections

Z(mumu) + jets Selections

The Muon Cuts are

1. Muons are both Tracker muons and Global Muons but used Global muons variables

2. Opposite charge dimuon

3. Muon pT > 20 GeV

4. Muon isolationR03.sumPt < 3

5. Muon |eta| < 2.1

6. | Muon dxy(beamSport.position)| < 0.2

7. Muon ID

- Number of valid Pixel hits ≥ 1

- Number of valid Tracker hits > 10

- normChi2 < 10

- Number of valid Muon hits ≥ 1

AK5 PFJet

- These jets are from the Z mass window events (76<Zmass<106)

- We cleaned the jets from muons with DeltaR jet and muon > 0.5

- The cut is jets pT > 30 GeV

- Central region |jet eta|<2.4


Z ee jets selections

Z(ee) + jets Selections


Z ee jets selections1

Z(ee) + jets Selections


Kittikul kovitanggoon a sung won lee a nural akchurin a

Di-muon pT and Di-muon Y

Of

Z + 2 jet event


Kittikul kovitanggoon a sung won lee a nural akchurin a

First Jet pT and First Jet Y

Of

Z + 2 jet event


Kittikul kovitanggoon a sung won lee a nural akchurin a

Second Jet pT and Second Jet Y

Of

Z + 2 jet event


Kittikul kovitanggoon a sung won lee a nural akchurin a

MEDGRAPH

Generation Variables


Kittikul kovitanggoon a sung won lee a nural akchurin a

#*******************

# Running parameters

#*******************

#

#*********************************************************************

# Tag name for the run (one word) *

#*********************************************************************

'Zjets' = run_tag ! name of the run

#*********************************************************************

# Run to generate the grid pack *

#*********************************************************************

.false. = gridpack !True = setting up the grid pack

#*********************************************************************

# Number of events and rnd seed *

#*********************************************************************

100000 = nevents ! Number of unweighted events requested

0 = iseed ! rnd seed (0=assigned automatically=default))

#*********************************************************************

# Collider type and energy *

#*********************************************************************

1 = lpp1 ! beam 1 type (0=NO PDF)

1 = lpp2 ! beam 2 type (0=NO PDF)

3500 = ebeam1 ! beam 1 energy in GeV

3500 = ebeam2 ! beam 2 energy in GeV

#*********************************************************************

# Beam polarization from -100 (left-handed) to 100 (right-handed) *

#*********************************************************************

0 = polbeam1 ! beam polarization for beam 1

0 = polbeam2 ! beam polarization for beam 2

#*********************************************************************

# PDF CHOICE: this automatically fixes also alpha_s and its evol. *

#*********************************************************************

'cteq6l1' = pdlabel ! PDF set

#*********************************************************************

# Renormalization and factorization scales *

#*********************************************************************

F = fixed_ren_scale ! if .true. use fixed ren scale

F = fixed_fac_scale ! if .true. use fixed fac scale

91.1880 = scale ! fixed ren scale

91.1880 = dsqrt_q2fact1 ! fixed fact scale for pdf1

91.1880 = dsqrt_q2fact2 ! fixed fact scale for pdf2

1 = scalefact ! scale factor for event-by-event scales

#*********************************************************************

# Matching - Warning! ickkw > 0 is still beta

#*********************************************************************

1 = ickkw ! 0 no matching, 1 MLM, 2 CKKW matching

1 = highestmult ! for ickkw=2, highest mult group

1 = ktscheme ! for ickkw=1, 1 Durham kT, 2 Pythia pTE

1 = alpsfact ! scale factor for QCD emission vx

F = chcluster ! cluster only according to channel diag

T = pdfwgt ! for ickkw=1, perform pdf reweighting

#*********************************************************************

#

#**********************************

# BW cutoff (M+/-bwcutoff*Gamma)

#**********************************

15 = bwcutoff

F = cut_decays ! Apply decays to products


Kittikul kovitanggoon a sung won lee a nural akchurin a

SHERPA

Generation Variables


Kittikul kovitanggoon a sung won lee a nural akchurin a

import FWCore.ParameterSet.Config as cms

source = cms.Source("EmptySource")

generator = cms.EDFilter("SherpaGeneratorFilter",

maxEventsToPrint = cms.untracked.int32(0),

filterEfficiency = cms.untracked.double(1.0),

crossSection = cms.untracked.double(-1),

Path = cms.untracked.string('SherpaRun'),

PathPiece = cms.untracked.string('SherpaRun'),

ResultDir = cms.untracked.string('Result'),

default_weight = cms.untracked.double(1.0),

SherpaParameters = cms.PSet(parameterSets = cms.vstring(

"Run"),

Run = cms.vstring(

"(run){",

" EVENTS = 1000;",

" EVENT_MODE = HepMC;",

" # avoid comix re-init after runcard modification",

" WRITE_MAPPING_FILE 3;",

"}(run)",

"(beam){",

" BEAM_1 = 2212; BEAM_ENERGY_1 = 3500.;",

" BEAM_2 = 2212; BEAM_ENERGY_2 = 3500.;",

"}(beam)",

"(processes){",

" Process 93 93 -> 90 90 93{4};",

" Order_EW 2;",

" Enhance_Factor 2 {3};",

" Enhance_Factor 35 {4};",

" Enhance_Factor 40 {5};",

" Enhance_Factor 50 {6};",

" CKKW sqr(20./E_CMS);",

" Integration_Error 0.02 {5,6};",

" End process;",

"}(processes)",

"(selector){",

" Mass 90 90 50. E_CMS;",

"}(selector)",

"(me){",

" ME_SIGNAL_GENERATOR = Internal Comix",

" EVENT_GENERATION_MODE = Unweighted;",

"}(me)",

"(mi){",

" MI_HANDLER = Amisic # None or Amisic",

"}(mi)"

),

)

)

ProductionFilterSequence = cms.Sequence(generator)


Kittikul kovitanggoon a sung won lee a nural akchurin a

MCFM

Generation Variables


Kittikul kovitanggoon a sung won lee a nural akchurin a

[General options to specify the process and execution Z+1j=41,Z+2j=44]

41 [nproc]

'tota' [part 'lord','real' or 'virt','tota']

'ex_cal'['runstring']

7000d0[sqrts in GeV]

+1 [ih1 =1 for proton and -1 for antiproton]

+1 [ih2 =1 for proton and -1 for antiproton]

120d0[hmass]

1.0d0[scale:QCD scale choice]

1.0d0[facscale:QCD fac_scale choice]

'm(34)'[dynamicscale]

.false.[zerowidth]

.false.[removebr]

10 [itmx1, number of iterations for pre-conditioning]

400000 [ncall1]

10 [itmx2, number of iterations for final run]

400000 [ncall2]

1089 [ij]

.false.[dryrun]

.true.[Qflag]

.true.[Gflag]

[Heavy quark masses]

172.5d0[top mass]

4.75d0[bottom mass]

1.5d0[charm mass]

[Pdf selection]

'ctq61.00' [pdlabel]

4 [NGROUP, see PDFLIB]

46 [NSET - see PDFLIB]

mstw2008nlo90cl.LHgrid [LHAPDF group]

0 [LHAPDF set]


Kittikul kovitanggoon a sung won lee a nural akchurin a

POWHEG

Generation Variables


Kittikul kovitanggoon a sung won lee a nural akchurin a

<LesHouchesEvents version="1.0">

<!--

file generated with POWHEG-BOX version 1.0

Input file powheg.input contained:

! Z production parameter

vdecaymode 2 !(1:leptonic decay, 2:muonic decay, 3: tauonic decay,...)

numevts 10000000 ! number of events to be generated

ih1 1 ! hadron 1 (1 for protons, -1 for antiprotons)

ih2 1 ! hadron 2 (1 for protons, -1 for antiprotons)

ndns1 131 ! pdf set for hadron 1 (mlm numbering)

ndns2 131 ! pdf set for hadron 2 (mlm numbering)

ebeam1 3500d0 ! energy of beam 1

ebeam2 3500d0 ! energy of beam 2

! To be set only if using LHA pdfs

lhans1 10800 ! pdf set for hadron 1 (LHA numbering)

lhans2 10800 ! pdf set for hadron 2 (LHA numbering)

! To be set only if using different pdf sets for the two incoming hadrons

! QCDLambda5 0.25 ! for not equal pdf sets

! Parameters to allow or not the use of stored data

use-old-grid 1 ! if 1 use old grid if file pwggrids.dat is present (<> 1 regenerate)

use-old-ubound 1 ! if 1 use norm of upper bounding function stored in pwgubound.dat, if present; <>

ncall1 100000 ! number of calls for initializing the integration grid

itmx1 5 ! number of iterations for initializing the integration grid

ncall2 100000 ! number of calls for computing the integral and finding upper bound

itmx2 5 ! number of iterations for computing the integral and finding upper bound

foldcsi 1 ! number of folds on csi integration

foldy 1 ! number of folds on y integration

foldphi 1 ! number of folds on phi integration

nubound 20000 ! number of bbarra calls to setup norm of upper bounding function

icsimax 1 ! <= 100, number of csi subdivision when computing the upper bounds

iymax 1 ! <= 100, number of y subdivision when computing the upper bounds

xupbound 2d0 ! increase upper bound for radiation generation


Kittikul kovitanggoon a sung won lee a nural akchurin a

! OPTIONAL PARAMETERS

ptsqmin 0.8 ! (default 0.8 GeV) minimum pt for generation of radiation

charmthr 1.5 ! (default 1.5 GeV) charm treshold for gluon splitting

bottomthr 5.0 ! (default 5.0 GeV) bottom treshold for gluon splitting

charmthrpdf 1.5 ! (default 1.5 GeV) pdf charm treshold

bottomthrpdf 5.0 ! (default 5.0 GeV) pdf bottom treshold

#renscfact 1d0 ! (default 1d0) ren scale factor: muren = muref * renscfact

#facscfact 1d0 ! (default 1d0) fac scale factor: mufact = muref * facscfact

#ptsupp 0d0 ! (default 0d0) mass param for Born suppression factor (generation cut) If < 0 su

#bornonly 0 ! (default 0) if 1 do Born only

#smartsig 1 ! (default 1) remember equal amplitudes (0 do not remember)

#withsubtr 0 ! (default 1) subtract real counterterms (0 do not subtract)

#withdamp 1 ! (default 0, do not use) use Born-zero damping factor

testplots 1 ! (default 0, do not) do NLO and PWHG distributions

#hfact 100d0 ! (default no dumping factor) dump factor for high-pt radiation: > 0 dumpfac=h**2

#testsuda 1 ! (default 0, do not test) test Sudakov form factor

#radregion 1 ! (default all regions) only generate radiation in the selected singular region

iseed 0019 ! initialize random number sequence

#rand1 -1 ! initialize random number sequence

#rand2 -1 ! initialize random number sequence

#iupperisr 1 ! (default 1) choice of ISR upper bounding functional form

#iupperfsr 2 ! (default 2) choice of FSR upper bounding functional form

#pdfreweight 1 ! (default 0) write extra pdf infos on LHEF

#manyseeds 1 ! (default 0) allow for the generation of different statistically independent samples (

sthw2 0.2312 ! sin**2 theta w

masswindow_low 28.529817249118306 ! M Z > Zmass - masswindow low * Zwidth

masswindow_high 2768.84113497916 ! M Z < Zmass + masswindow high * Zwidth

runningscale 1 ! choice for ren and fac scales in Bbar integration Z

! 0: fixed scale M

! 1: running scale inv mass Z

End of powheg.input content


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