sung-won lee
DESCRIPTION
Study of Jets Production Association with a Z boson in pp Collision at 7 and 8 TeV with the CMS Detector. Kittikul Kovitanggoon Ph. D. Thesis Defense March, 24 2014. Sung-Won Lee. 1. Outline. Motivation. Large Hadron Collier (LHC) and Compact Muon Solenoid (CMS). - PowerPoint PPT PresentationTRANSCRIPT
Sung-Won Lee 1
Study of Jets Production Association with a Z boson in pp Collision
at 7 and 8 TeV with the CMS Detector
Kittikul Kovitanggoon
Ph. D. Thesis DefenseMarch, 24 2014
2
Outline
Motivation
Large Hadron Collier (LHC) and Compact Muon Solenoid (CMS)
Overview of Standard Model (SM)
Measurements of Angular Distributions for Z+jet events at 7 TeV Theory Data Samples and Event Reconstructions Unfolded Results with Uncertainties
Differential Cross Section of Jets Associated to Z boson at 8 TeV Theory Data Samples and Event Reconstructions Unfolded Results with Uncertainties
Conclusions
3
Motivation
For Z boson decays into μ+μ- , the trigger system is very efficient and nearly background free
Provide good feedback to the theoretical physics community to improve the precision of perturbative QCD and to event generator experts
Measurements of the rapidity distributions and differential cross sections are one of the crucial test of the SM prediction
Major background processes for various new physics searches such as Higgs and Supersymmetry (SUSY)
4
Large Hadron Collider (LHC)
A 27 km in circumference
To collide rotating beams of protons or heavy ions
Maximum energy of proton-proton collisions at = 14 TeVand 4 x 10-34 cm-2s-1
√s
In 2011, collision at = 14 TeV and 4 x 10-33 cm-2s-1
√s
In 2012, collision at = 8 TeV and 7.7 x 10-33 cm-2s-1
√s
5
Compact Muon Solenoid CMS
6
Compact Muon Solinoid CMS
7
Standard Model (SM)
8
Z + Jet Angular Distribution
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What Do We Measure? Rapidity distributions of Z boson: |y
z|
Rapidity distributions of leading jet: |yjet
|
Rapidity difference: ydiff
= 0.5|yz-y
jet|
Related to the scattering angle at the center of momentum frame: tanh(y
diff) = β*cosθ*
Rapidity average: ysum
= 0.5|yz+y
jet|
Rapidity boost from the center of momentum frame to the lab frame
Rapidity is defined by y=12
ln ( E+pzE− pz )
11
Analysis Procedure(1) Selects events containing a Z(→μμ) and a jet that satisfy kinematic and ID selections.(2) Derive efficiency from MC and correct it with data-to-MC scale factors via tag and probe method. (3) Unfold the distribution of y
jet
Other variable have unfolding correction consistent with one.
(4) Evaluate Systematic uncertainties.
(5) Compare shapes with MCFM, MADGRAPH, and SHERPA MC simulations.
MCFMMatrix element at NLO,without parton showering or hadronizationScale set to the dilepton massCTEQ 6.1 m (NLO PDFs)
MADGRAPH+PYTHIA Matrix element at LO with MLM matching Scale set to the square root sum of dilepton mass and p
T(jet)
CTEQ 6L1 m (LO PDFs)
SHERPA Matrix element at LO with CKKW matching Scale set to the dilepton mass CTEQ 6.6M (NLO PDFs)
12
Dataset and HLT CMS data collected in 2011 for 5.1 ± 0.1 fb-1
Monte Carlo Simulations
JSON: Cert_160404-180252_7TeV_ReRecoNov08_Collisions11_JSON.txt
High Level Trigger
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Basic Kinematic Selections
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Basic Kinematic Properties Well agreements for Z kinematics between data and MC
Z mass distribution was created before Z mass selections
Discrepancy of Z mass < 50 GeV comes from the generator-level mass selection
15
Basic Kinematic Properties
The number of jets accompanying a Z drops by ~αS
Non-zero jet mass is attributed to the finite angular spread of the jet in calorimeter
16
Basic Kinematic Properties
Well agreements for jets kinematics between data and MC
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Muon ID Scale Factor and Efficiency
ID scale factors from Particle Object Group
Use Tag & Probe with Data & MC
Select a pair of muons: one passing tight selections (tag) and the other passing or failing loose selections (probe)
The scale is computed from the ratio of tag+passing probe and tag+failing probe
Use Muon Particle Object Group recommendations
Obtain the data-to-MC ID efficiency scale factors in bins of p
T and η
Re-weight the MC events that pass IDselections with the scale factors
Obtain efficiency as a function of the four rapidity variables
The ID efficiency correction is the reciprocal if the ratio of weighted with ID selections and without ID selection
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Muon ID Efficiency
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Unfolding
Unfolding methods 1. Bayesian with 3 iterations 2. Bin-by-Bin 3. Singular Value Decomposition with kreg=10
Criteria: if unfolding correction is consistent with zero within MC statistical uncertainty, do not unfold
In order to compare experimental result with theoretical prediction, the experimental need to be corrected due to the detector effects.==> The method is called unfolding.
Response matrices of rapidity: the comparison shows mostly
diagonal elements
Using RooUnfold package
MADGRAPH+Pythia as source of response matrices
20
Unfolding Correction on Data
Unfolding is consistent at one for all but yjet
distribution. Thus, we will unfold y
jet.
21
Systematic Uncertainties
Jet Energy Scale (JES) Uncertainties
Jet Energy Resolution (JER)
Jets are corrected due to the non-uniform and non-linear response of calorimeters Can cause the bin migration i.e. Z+0jet can fake as Z+1jet etc. Shifted jet corrections up and down by 1σ σ is provided by JetMET POG Re-performing measurements after shifting jet
Finite jet energy resolution can be the threshold effects Modified the reconstructed jet pT with the pT difference between matched reconstruction-level jets and generator-level jets
c is a factor provided by JetMET POG
22
JES Uncertainties
Uncertainty is < 1% for all distributions
23
JER Uncertainties
Uncertainty is < 2% for all distributions
24
Comparison to Theories Shape comparisons of CMS data, MADGRAPH, and SHERPA to MCFM are shown.
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Comparison to Theories
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Combined Results
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Combined Results
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Summary CMS detector was used to measure the angular distributions of
the products from Z+1jet events
• Madgraph+Pythia, Sherpa, and MCFM have similar agreement with data for y
z and y
jet .
• For Z + 1jet, Sherpa agrees better with data for ydiff
and ysum
.
Parton showering and matching scheme give the difference.
Provide feedback to theory community for improving theoretical predictions.
29
Z + Jets Differential Cross Sections
30
Z+jets
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What Do We Measure?
In this analysis, we measured the Z+jets differential cross sections ofup to two jets associated with Z → μ+μ- .
The Z+jets production cross section as a function of the jet multiplicity : dσ/ dN
J
The Z+jets cross section as a function of the jet pT : dσ/ dpT
The Z+jets cross section as a function of the jet η : dσ/ dη
32
Dataset CMS data collected in 2012 for 19.8 ± 0.1 fb-1
Monte Carlo Simulations
JSON: Cert_190456-208686_8TeV_22Jan2013ReReco_Collisions12_JSON.txt
High Level Trigger → HLT_Mu17_Mu8_v* with L1_DoubleMu3p5 seed
33
PU Re-Weighting
MC productions use an approximate number of pileup interactions Pileup interactions in MC are re-weighted by the data pileup distribution using the entire data-taking period
34
Basic Muon Selections Using PF muon collection matched the trigger objects
35
The First Muon Candidate
First muon candidate kinematics are agreed between data and MC
36
The Second Muon Candidate
Second muon candidate kinematics are agreed between data and MC
The pT plots show good agreement at the kinematic region up to 60 GeV where we
expect to find most muons coming from Z decays
37
Efficiency Scale Factor
Scale factors of HLT, ID, and isolation from Tag and Probe
Provided by Muon POG
Obtain the data-to-MC scale factors in bins of p
T and η
38
Z Reconstruction Z bosons are reconstructed from opposite charged muons
Z mass window of 71 < MZ < 111 are used and agreed with MC
39
Z Reconstruction
40
Basic Jet Selections Jets are AK5 PF after Charged Hadron subtraction
Data are using L1FastJet + L2Relative + L3Absolute + L2L3Residual
MC are using L1FastJet + L2Relative + L3Absolute
Leptons are vetoed from the jet collection by a simple ∆ R cut of 0.5
41
Z+Jets Control Plots
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Measured Observables
Good agreement between data and MC up to 4 jets as expected
Exclusive Inclusive
43
Measured Observables
pT distributions of the first and second leading jets agree at low pT
44
Measured Observables
η distributions of the first and second leading jets also agree in barrel region and show some discrepancy in endcap region as expected from detector performance
45
Unfolding Using MADGRAPH+Pythia as source of response matrices
Unfolding methods 1. Bayesian with 3 iterations → used for the final results 2. Bin-by-Bin 3. Singular Value Decomposition with kreg=10
Generator level phase space Muons are dressed with all the photons that are within
the cone of radius 0.1 Stable muons from Z (status =1) Cuts on muons pt > 20,η < 2.4 after adding photons
Background subtraction from data
Using MADGRAPH+Pythia as source of response matrices
46
Unfolding
Response matrix
47
Unfolding
48
Unfolding
49
Systematic Uncertainties
Jet Energy Scale (JES) Uncertainties
Jet Energy Resolution (JER)
Jets are corrected due to the non-uniform and non-linear response of calorimeters Can cause the bin migration i.e. Z+0jet can fake as Z+1jet etc. Shifted jet corrections up and down by 1σ σ is provided by JetMET POG Re-performing measurements after shifting jet
Finite jet energy resolution can be the threshold effects Modified the reconstructed jet pT with the pT difference between matched reconstruction-level jets and generator-level jets
c is a factor provided by JetMET POG
50
Systematic Uncertainties
Smearing jet pT can change
Z+0jet to Z+1jet etc
Higher the jet mutiplicity, more bin migration
JES causes up to 10% uncertainty
51
Systematic Uncertainties
JER causes only 2-4% uncertainty
52
Systematic Uncertainties
Summary
53
Results
54
Results
55
Z+Jets Summary
The differential cross-sections of Z+n jets (n up to 2) are measured as functions of
Jet multiplicity Jet transverse momentum Jet rapidity
The measurements are done on 8 TeV with integrated luminosity of 19.8 fb−1
Detector effects are corrected by unfolding with Bayes method
Results are compared to the following MCFM+Pythia generator prediction
56
Conclusions Jets productions in association with a Z boson in p-p collision
provides a good opportunity to test perturbative QCD and
important background for new physics
Angular distributions for the Z boson and a single jet of 4.7 fb− 1
at 7 TeV have been analyzed
|y
z| and |y
jet| are found to agree with predictions from SHERPA,
MADGRAPH, and MCFM y
sum described by all predictions up to 5% precision for y
sum < 1.0
At ysum
> 1.0, SHERPA is the best described due to the hybrid
calculations that employ NLO PDFY
diff is best described MCFM
57
Conclusions
Differential cross sections for the Z boson and jets of 19.8 fb− 1 at 8 TeV have been calculated
The measurements of Z+jets production deferential cross section up to two jets as a function of the
Jet multiplicity: dσ/ dNJ
Transverse momentum: dσ/ dpT
Rapidity: dσ/ dη
J
Results after unfolding and efficiency corrected, compared with different theoretical pQCD predictions in MADGRAPH
JES and JER are studied as the main systematic uncertainties
Comparisons are agreed with data and MC
58
Back Up
59
Unfolding Correction with SHERPA
Use the response matrices of MEDGRAPH to unfold the independent MC prediction of Z+jets, SHERPA
60
PU Systematic Uncertainty for Z + Jet Angular
61
Background Systematic Uncertainty for Z + Jet Angular
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PU Systematic Uncertainty for Z + Jet Angular
63
Combination of Electron and Muon Best Linear Unbiased Esttimator
Andrea Valassi, NIM, A500, 391 Louis Lyons, Duncan Gibaut, and Peter Clifford, NIM, A207, 110
JES and PU uncertainties are 100% correlated between electron and muon channel
The covariance matrix has 2N dimension N is the number of bins with non-zero contents For each channel of y
jet, the bin-by-bin correlation is obtained
from the covariance matrix of RooUnfold after unfolding
For every bin of the observable, the uncorrelated uncertainty is at least 3 times of the correlated uncertainty
64
Breakdown Differential Cross Section
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Breakdown Differential Cross Section