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First Attempts:ABCD Method for background

estimation of W→eνShu Li, Yanwen Liu

Together with Elisabeth Petit, Fabrice Hubaut, Pascal PralavorioCenter of Particle Physics and Technology, USTC

&Center de Physique des Particules de Marseille, CNRS-IN2P3 / Université de la Méditerranée - Aix Marseille II

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7TeV Collision data used: (~14M evts)L1CaloEM ESD: all of RunNumber 152166-153599 L1Calo ESD: all of RunNumber 154810-155160

MC Samples used:mc09_7TeV.105802.JF17_pythia_jet_filter.merge.AOD.e5

05_s765_s767_r1302_r1306 (10M evts, serves as background with signal components excluded)mc09_7TeV.105805.filtered_minbias6.merge.AOD.e530_

s765_s767_r1302_r1306 (7M evts, signal sample)

Datasets in use

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Basic Selection Criteria in usePreSelections:Event Level: Ask for stable beam LumiBlock based on InterestingRuns Twiki: https://twiki.cern.ch/twiki/bin/view/AtlasProtected/InterestingRuns2010 GRL used: (going to update with new egamma GRLs)• data10_7TeV.periodA.152166-153200_LBSUMM_DetStatus-v02-

repro04-00_eg_standard_7TeV.xml• data10_7TeV.periodB.153565-155160_LBSUMM_DetStatus-v02-

repro04-00_eg_standard_7TeV.xml Good LumiBlock with Stable beams required for all runs L1_EM2 trigger passed Good Primary Vertex with ≥3 tracks MET_cleaning implemented using JetCaloQuality Tool (https://twiki.cern.ch/twiki/bin/view/Sandbox/JetCaloQuality)

based on WZObservation fundamental requirements on Twiki:https://twiki.cern.ch/twiki/bin/view/AtlasProtected/WZObservation7TeV

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Further PreSelections: Object Level: Fiducial Cuts applied using CheckOQ Macro(Version4, not the

latest) to exclude dead OTX related clusters (Still updating) (/afs/cern.ch/atlas/groups/EGamma/OQMaps/OLD: checkOQ_v4.C & ObjectQualityMaps_run152166.root & ObjectQualityMaps_run155118.root) ET

clus>15GeV |ηclus|<2.0 without crack region (only within TRT coverage for

eProbabilityHT, should be 2.5 for Calo Isolation study) AuthorElectron (author==1 || author==3 for MC AOD,

author==1 for data ESD) isEM Loose/Medium/Tight applied respectively Track quality requirements: nSCTHits>=6, nPixelHits>0, nTRTHits>=10 Basic shower shapes requirements: f1>0.01; weta1, dEminS1, dEmaxS1, WstotS1 >0.

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ABCD Method 1. (data-driven only, need to verify in MC)

Assume ABCD regions have similar ratio over each other for those background components of each region in the data:

bgdA/bgdB=bgdD/bgdCSo as to extract the signal component in “D” while removing the estimated background in it. (Should be verified based on MC)ABCD Method 2. (using MC information, limited

due to MC and Data disagreement and statistics)Assume ABCD regions have similar ratio over each other for both signal and bgd between data and Monte Carlo:

b1i+b2i+si=Ni,i=A,B,C,D b1i: 1st kind of background (JF17), b2i: 2nd kind of

background (filtered_MinBias) Ni: Expected from data si/si, b1i/b1j, b2i/b2j in data should be consistent with MC 3 equations and 3 unknown variables Can be implemented with more or fewer background samples

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eProbabilityHT Vs MET_Topo • A: MET_Topo <= 25GeV, eProbabilityHT >=

0.9 • B: MET_Topo <= 25GeV, eProbabilityHT < 0.9 • C : MET_Topo > 25GeV, eProbabilityHT <=

0.9 • Signal Region D: MET_Topo > 25GeV, eProbabilityHT > 0.9

Electron Probability for TRT High Threshold(variable named eProbabilityHT)

Vs MET_Topo

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eProbabilityHT distribution after preCuts with isEM medium applied(Not Normalized)

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A

B C

D

A

B C

D AB C

D

eProbabilityHT Vs MET_Topo after preCuts with isEM medium applied(Not Normalized)

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isEM Loose(Not Normalized)

RegionSample/data

A B C D

Wenu(7M)

305964 57413 254392 1332229

JF17(10M)

4323 7347 33 92

Data(~14M)

95 163 1 20

A/B=D/C doesn’t agree

Very tight

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isEM Medium(Not Normalized)

RegionSample/data

A B C D

Wenu(7M)

299627 56346 250544 1309123

JF17(10M)

2268 1721 17 80

Data(~14M)

54 35 1 19

A/B=D/C doesn’t agree

Very tight

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IsEM Tight is not appropriate to be applied due to its correlation with the variable

eProbabilityHT!

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CaloIso Vs MET_Topo • A: MET_Topo <= 25GeV, CaloIso <= 0.1 • B: MET_Topo <= 25GeV, CaloIso > 0.1 • C : MET_Topo > 25GeV, CaloIso >= 0.1 • Signal Region D: MET_Topo > 25GeV, CaloIso < 0.1

Calorimeter Isolation(CaloIso)Vs MET_Topo

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Calorimeter Isolation distribution after preCuts with isEM medium applied(Not Normalized)

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B

A D

C

B

A D

C B

A D

C

Calorimeter Isolation Vs MET_Topo after preCuts with isEM medium applied(Not Normalized)

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isEM Loose(Not Normalized)

RegionSample/data

A B C D

Wenu(7M)

318890 44487 145977 1440644

JF17(10M)

2108 9562 54 71

Data(~14M)

55 208 4 17

A/B=D/C doesn’t agree

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isEM Medium(Not Normalized)

RegionSample/data

A B C D

Wenu(7M)

312709 43264 142109 1417558

JF17(10M)

914 3075 30 67

Data(~14M)

30 59 4 16

A/B=D/C doesn’t agree

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isEM Tight(Not Normalized)

RegionSample/data

A B C D

Wenu(7M)

312709 43264 142109 1417558

JF17(10M)

144 11 11 144

Data(~14M)

30 59 4 16

A/B=D/C agrees with the assumption extremely well

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TRT High Threshold Probability still need to be further investigated since the results did not agree with assumption in method 1 (try with method 2?)

Try with New Recommended Robust isEM Tight Cuts

Update with new fundamental selection criteria(new GRL, OQMap, etc.) with more new collision runs

Some other way: 2-D Matrix method (very simple way to carry on by using only one variable but may result in some disagreement between different variables)

Change some values of the current cut criteria and evaluate the systematics

Some possibilities for next step