QCD and Top backgrounds in W+jets and Rjets

QCD and Top backgrounds in W+jets and Rjets

Alessandro Tricoli (CERN)

on behalf of

W+jets and Rjets groups

3rd May 2013 W+jets and Rjets EB Meeting

A. Tricoli 23rd May 2013

Overview

Progress made in understanding QCD multi-jet and Top backgrounds Better understanding of QCD background in W m and e channels, e.g.

pileup, trigger and template dependencies Systematics available for QCD in electron channel Top background estimations available in both m and e channels with

most of systematics included To do list getting smaller and smaller

big effects already addressed, remaining sub-leading effects to be considered


QCD Methods recap

Both m and e channels fit MET distribution (10-60 GeV) in exclusive jet multiplicity bins, using data-driven template for QCD and other processes from MC QCD Control samples (Templates);

o Mu channel: uses same trigger as for signal and reverts impact parameter significance (d0/s(d0)>3)

o Electron Channel: uses logical OR of a few loose electron triggers and revert some electron identification requirements, plus anti-isolation (etcone30/eT > 0.2). Control sample split in 2 data-periods: D-K and L-M

See my presentation on 25th February WZ subgroup for more details


Investigation of reasons for increase of QCD background wrt 2010 Is difference of 3x-5x between 2010 and 2011 due to the broadening

of the MET distribution with more pile-up? Previous results were inconclusive

Study QCD fractions in different sampleso Low/Medium/High Pileup o D-K and L-M Periodso Low/Medium/High jet pT

QCD – W->mn +jetsPileup


Sample Njej==0 [%]

Njej==1 [%] Njej==2 [%] Njej==3 [%] Njej==4 [%] Njej==5 [%]

Reference 4.91±0.18 14.23±0.23 13.23±0.43 12.5±0.9 9.4±1.5 11±10

m=0-4 3.8±1.1 7.5±1.3 8.3±2.9 5.4±3.3 5.7±5.4 1.4±5.0

m=4-8 3.87±0.21 10.91±0.30 10.31±0.58 10.8±1.2 7.7±2.0 10±12

m=8+ 5.88±0.29 16.67±0.31 15.54±0.63 13.7±1.2 10.6±2.1 12±14

D-K 3.99±0.21 11.04±0.28 10.47±0.56 10.8±1.2 7.5±1.9 10±13

L-M 5.81±0.29 16.70±0.32 15.49±0.64 13.5±1.2 10.9±2.2 12±14

jet pT>45 GeV 5.33±0.12 14.67±0.28 10.64±0.64 8.3±1.4 8.0±3.3 3.5±7.7

jet pT>60 GeV 5.55±0.11 12.77±0.35 9.64±0.96 7.3±2.2 3.3±2.3 0.3±3.2

QCD Fractions increases when pileup increases, in all three tests QCD Fractions for m=0-4 close to 2010 values (pileup conditions rather similar) Pileup is cause of increased pileup in 2011 wrt 2010

QCD – W->mn +jetsPileup


QCD – W->mn +jetsComparison with W inclusive

W inclusive group uses different definition of QCD control sample 0.1 < ptcone20/pT<0.5

Good agreement on QCD fraction between our results and theirs when same selection is used

Reason for different strategy is bias on jet kinematics by reversing relative isolation

Reversed D0 Reversed Iso

Jet pT biased in all templates tested except our nominal (reversed d0)


QCD – W->mn +jetsComparison with W inclusive

Larger W Contamination in QCD control sample found with our selection (reverted impact param significance) wrt W inclusive method Frac. of expected Wmn events in QCD control region: 42% vs 13%

with 0 jets

W+jets

W incl

Studying if we should subtract this contamination or try different template definition Find a balance between contamination and jet pT bias


QCD – W->mn +jetsTemplate shape bias

Our method assumes no change of shape in moving QCD events fromthe control region to the signal region

Test this hypothesis by comparing the shape of QCD MC in the signal selection to the data templates

The heavily signal contaminated templates (i.e. 1 & 3) show large differences in the zero jet bin, others are all more similar

Clear trend: templates have harder met spectrum than MC Is this a real bias or more general MC-data discrepancy for QCD?


QCD – W->en +jetsComparison with Inclusive group

Believe we have resolved differences with inclusive group Very good agreement

Inclusive group also see period dependence consistent with us


QCD – W->en +jetsUncertainties

Uncertainties considered so far Fit range (5-20 GeV) Varying the anti-isolation requirement (different cone sizes and cut values) Sherpa instead of Alpgen Statistical uncertainty

Study of template bias Different failed tight requirements (different isEM sub-sets)

o adding following requirement to pass at a time (in addition to loose+track quality):

Envelope of these then taken for an additional systematic


QCD – W->en +jetsUncertainties

Due to significantly reduced stats in the QCD template for TRACKMATCH bit reversalo Either we increase

stat. or eliminate stat fluctuations from sys.


Statistical fluctuations dominate systematics at high Njets From period L5 new triggers were introduced specifically for QCD

background estimations in the electron channel EF_e22vh_loose_4j15_a4tc_EFFS EF_e22vh_loose_3j20_a4tc_EFFS Loosely-identified electrons + 2 and 3 jets respectively (beware of e/j overlap)

with 15,20 GeV thresholds on HLT jets (Full Scan) Increase statistics of QCD Control Sample for 2 and more jets

Statistics increase of factor 2 to 5• 2.0x (Njets =2)• 3.4x (Njets =3)• 3.6x (Njets =4)• 4.1x (Njets =5)• 5.0x (Njets ≥6)

Need to check bias on distributions as 30 GeV cut offline on jet threshold is not at jet trigger efficiency plateau

QCD – W->en +jetsTrigger Statistics


QCD – W->en +jetsTrigger Statistics and Bias

No evidence of bias on MET from these triggers for 2 and more jets

Will check bias on other distributions, e.g. jet pT Will evaluate impact on overall analysis uncertainty of gain in control

sample statistics


QCD – W->en +jetsTrigger Bias

Three types of triggers used for collecting control sample1) e20(22)_loose, e20(22)_looseTrk (= loose + track quality cuts)2) e20(22)_loose1

No trigger bias on control sample from different types of triggers on jet observables

However bias on electron kinematics (as expected)

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Top Background Summary

Have fits from 3-jet to 7-jets for both electron and muon channel Have evaluated all major systematic uncertainties

But still have several cross checks to do with R+jets code Remaining outstanding items

Understanding fits using MET and Top mass Correlations between the QCD fit and top fit

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Top - Reminder of Method Top background is one of the largest uncertainties Use a full data-driven method

A ttbar template from data An independent variable to normalize the ttbar template

Can select a ‘pure’ ttbar sample by requiring events with one or two b-jets

Found using Transverse Sphericity yields the most stable fits, fits converge up to 7 jets

Also studying Top mass and MET fits for comparison

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Top Fit Example

Top template: - B-tagged Data- Wc,b from MC

W template- From MC- No b-tagging requirement

Data- No b-tagging

QCD- Fixed in the fit

Njet=4

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Top Template Corrections

The b-tagged data-driven sample has slight biases with respect to the non-b-tagged sample

Correct for this using MC The two distributions are

normalised in the ratio so that when the corrections are applied the total area is not changed (correct for bias on shape only)

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Top - Wcc, Wbb Contamination Question was raised in EdBoard about

what k-factors to apply to the Wbb and Wcc samples

Estimate of the k-factor in the 1-jet and 2-jet bin where top contribution is small

Has small effect on the fit <4% at 3-jet (compared to 8% statistical uncertainty)

Use K-factor of 1.18 as systematic uncertainty

1-jet 2-jet

Wcc, Wbb Alpgen 1.11 1.18

Sherpa 0.95 1.02

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Top - Uncertainties

Statistical uncertainties from the fit W signal model

Fit using W Sherpa sample Btagging bias correction

Use largest of statistical errors on Alpgen, or difference between Powheg vs Alpgen

Fit range, template shape dependence Compare the pseudo-data sets to truth as a function of fit range

Wcc, Wbb contamination subtraction Redo fits using K-factor of 1.18

Standard MC-based uncertainties on W template including B-tagging efficiency uncertainties (on b, c, and light) JES, JER, lepton energy scale, etc

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Top Fit Results Take the central value of the 3-jet bin with a grain of salt (sudden

change with recent MC version, need to de-bug this) 3-jet bin is dominated by JES (where the W signal is largest) 7-jet bin is dominated by statistical uncertainties from the fit

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Top Fit Results Detector level distributions look good

MC Data-driven

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Top Open Problems

The Sherpa sample has poor statistics

Using sherpa as a modeling uncertainty has large fluctuations (red curve) Using Sherpa for both W signal

template and W contamination in Top control sample

Will use pseudo-data sets to evaluate if the modeling uncertainty is fully included in the fit range systematic

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Top Open Problems

Fits using top Mass and MET are very unstable and dependent on the fit range.

It would be helpful to have a second variable as a cross check

Need to re-do pseudo-data set fits to evaluate fit ranges for these variables

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QCD and Top - To Do List

QCD multi-jet background Re-evaluate systematics in W->mn channel Study W contamination in QCD control region and alternative control

samples (with no kinematic bias) in W->mn channel Study alternative method, e.g. isolation, in both channels Cross check strategy of systematics with W inclusive group

Top background Cross check all JES uncertainties, cutflow on MC with R+jets Add electron, muon systematics Cross check results with alternative fit methods, i.e. MET and Top

Mass, including their systematics Adding fit range systematic uncertainty and closure tests Correlation between QCD and Top data-driven estimations Evaluate Top background on Z (follow Z+jets/CMS method)

3rd May 2013

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Backup

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Pileup – muons

No need of period dependence fit in Muon Channel since same trigger used for signal and background samples pileup effects (e.g. broadening of MET

distribution) in signal sample is well reproduced by background sample

Oppositely to electron channel, QCD fraction seems to go down in L-M, by a factor ˜3 wrt D-K Is this because isolation becomes tighter with more pileup?

QCD control sample

Signal sample

Clear period-dependence of isolation distribution(D-K,L-M)

25th February 2013

Slide from 25 February


QCD – W->en +jetsSystematics – 5th jet

QCD and Top backgrounds in W+jets and Rjets

Documents

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