Measuring the ttbb production cross-section with 8 TeV ...sargyrop.web.cern.ch/sargyrop/DPGWuppertal.pdf · Measuring the ttbb production cross-section with 8 TeV ATLAS data Spyros

Measuring the ttbb production cross-section with 8 TeV ATLAS data

Spyros Argyropoulos(supervised by J. Katzy)

DPG Wuppertal9/3/2015

Measuring ttbb

Strategy:• Aim for simplicity and robustness: cut-and-count method• Minimize complexity by choosing a clean final state• use as much information from data as possible

➡ MC-to-data correction factors derived from in-situ measurements➡ measure cross section in regions with significantly different S/B

• Minimize extrapolations➡ measure in a fiducial region close to the experimental acceptance

4 b-jets - 2 leptons

2

Several reasons to measure ttbb:1. it’s the dominant irreducible background for ttH(bb),

also background for other physics searches 2. theoretical predictions suffer from large

uncertainties σ = O(αs4)3. it can give access to g → bb splitting (constraints

from LEP/SLC at the 25-30% only)

Overview

Background• 2 categories: tt+jets processes, non-tt+jets processes• estimated from MC ⇒ have to prove that background estimate is under control

Fiducial efficiency• contains all reconstruction/identification efficiencies, in particular b-tagging

efficiencies, C/LF mis-tagging efficiencies (εfid = εll·εb4·...)• the efficiencies are corrected with SF derived from data

We measure the number of events with exactly 2 leptons and 4 b-jets

3

σfidtt̄bb̄ =

Nsig

L · �fid=

Ndata4b −Nbg

L · �fid

4

tt+jets background

Dominant background comes from tt+jets processes:

(i) mis-tagged (ii) non-fiducial

The non-fiducial background comes from the same underlying partonic process as ttbb, so we want to scale it with the signal:

=⇒ σfidtt̄bb̄ =

�Ndata

4b −Nmis−taggedtt̄+jets −Nnon−tt̄+jets

bg

�fsig

L · �fid

σfidtt̄bb̄ =

�Nsig +Nnon−fiducial

tt̄bb̄

�fsig

L · �fid=⇒

�Ndata

4b = Nsig +Nnon−fiducialtt̄bb̄

+Nmis−taggedtt̄+jets +Nnon−tt̄+jets

bg

�

fsig ≡ Nsig

Nsig +Nnon−fiducialtt̄bb̄

Powheg+Pythia (AFII) - nominal

Powheg+Pythia (GEANT4)damp

Powheg+Pythia h

Powheg+Herwig

MadGraph+Pythia

MadGraph+Pythia (Q2 up)

MadGraph+Pythia (Q2 down)

sig

f

0.50.550.6

0.650.7

0.750.8

0.850.9

0.951

ATLAS Internal

Reconstructed in Signal Region Fiducial

Mis-tagged and non-fiducial background

5

non-fid

ucial

mis-tagged

Signal

σfidtt̄bb̄ =

�Ndata

4b −Nmis−taggedtt̄+jets −Nnon−tt̄+jets

bg

�fsig

L · �fid

other bg

Signal regionSignal regionData 37

MC (Signal+Bg) 28.6 +7.4 -5.2

Non-fiducial 7.8 +3.5 -2.9

Mis-tagged 3.5 +1.6 -2.0

Other bg 1.3 +1.1 -0.9

work in progress

Simulation√s = 8 TeV

How can we validate our background estimate using data?

6

highest jet MV1c scoreth4

80%-70% 70%-60% 60%-50% 50%-0%

[fb]

fidbbtt!

0

5

10

15

20

25

30

35

Fixe

d B

kg /

Dat

a

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

ATLAS Internal

Idea: the σttbb is constant - increasing εb would result in increasing the amount of background in the signal region

If the background estimation is not correct, we expect the cross-section to increase/decrease as we move across the different εb bins

background/data

√s = 8 TeV,L = 20.3 fb−1

Validation of background estimate

• no trend appearing across MV1/MV1c points• background estimation procedure seems to work well

7

highest jet MV1c scoreth4

80%-70% 70%-60% 60%-50% 50%-0%

[fb]

fidbbtt!

0

5

10

15

20

25

30

35

Fixe

d B

kg /

Dat

a

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

ATLAS Internal

Idea: the σttbb is constant - increasing εb would result in increasing the amount of background in the signal region

background/data

Measured cross-section

√s = 8 TeV,L = 20.3 fb−1

Control distributions - Leading b-jets

• data prefer softer lepton/leading jet spectra than nominal MC (known issue)• data/MC disagreement covered by modeling uncertainties

8

work in progress

-3 -2 -1 0 1 2 3

Even

ts-110

1

10

210

310

410

510

610ATLAS Internal

Data inclusivettVtt

Single TopZ+jetsDibosonsHtt

!2nd b-jet -3 -2 -1 0 1 2 3

Dat

a/M

C

0.5

1

1.5

0 50 100 150 200 250 300

Even

ts

1

10

210

310

410ATLAS Internal

Data inclusivettVtt


[GeV]T

2nd b-jet p0 50 100 150 200 250 300

Dat

a/M

C

0.5

1

1.50 50 100 150 200 250 300

Even

ts

210

310

410

ATLAS InternalData inclusivettVtt


[GeV]T

1st b-jet p0 50 100 150 200 250 300

Dat

a/M

C

0.5

1

1.5

-3 -2 -1 0 1 2 3

Even

ts

-110

1

10

210

310

410

510

610ATLAS Internal

Data inclusivettVtt


!1st b-jet -3 -2 -1 0 1 2 3

Dat

a/M

C

0.5

1

1.5

work in progresswork in progress

work in progress work in progress

√s = 8 TeV

L = 20.3 fb−1

Control distributions - additional b-jets

• Powheg+Pythia gives slightly softer additional b-jets than what’s observed in data- in Powheg+Pythia additional b-jets only come from the shower ⇒ valid only in soft/

collinear limit• More events in data with 4 b-jets than in MC • Generators which include matrix elements for ttbb seem to offer a better description of

the pT spectra and of the b-jet multiplicity 9

0 1 2 3 4 5 6 7

Even

ts

-210

-110

1

10

210

310

410

510

610ATLAS Internal

Data inclusivettVtt


N b-jets0 1 2 3 4 5 6 7

Dat

a/M

C

0.5

1

1.5

0 50 100 150 200 250 300

Even

ts

-110

1

10

210

310ATLAS Internal

Data inclusivettVtt


[GeV]T

3rd b-jet p0 50 100 150 200 250 300

Dat

a/M

C

0.5

1

1.5 0 20 40 60 80 100 120 140

Even

ts

-210

-110

1

10

210ATLAS Internal

Data inclusivettVtt


[GeV]T

4th b-jet p0 20 40 60 80 100 120 140

Dat

a/M

C

0.5

1

1.5

-3 -2 -1 0 1 2 3

Even

ts

-210

-110

1

10

210

310

410

510ATLAS Internal

Data inclusivettVtt


!3rd b-jet -3 -2 -1 0 1 2 3

Dat

a/M

C

0.5

1

1.5 -3 -2 -1 0 1 2 3

Even

ts

-210

-110

1

10

210

310 ATLAS InternalData inclusivettVtt


!4th b-jet -3 -2 -1 0 1 2 3

Dat

a/M

C

2

4

work in progress

work in progresswork in progress

work in progress work in progress

√s = 8 TeV

L = 20.3 fb−1

Uncertainties

Uncertainty source Effect on σ

Modeling 23%

Generator 18%

Scale/ISR/FSR 13%

Detector simulation 6%

Shower/Hadronization 4%

PDF 1%

Detector systematics +18% -14%b-tagging +15% -13%

Jet reconstruction +8% -6%

Statistical uncertainty 19%

Luminosity 3%

Total uncertainty +36% -34%

10

• dominant uncertainty are due to modeling

• dominant systematic from detector performance is from b-tagging



Powheg+Pythia h

Powheg+Herwig

MadGraph+Pythia



[fb]

fidbbtt!

5

10

15

20

25 ATLAS Internalwork in progress√s = 8 TeV,L = 20.3 fb−1

Result

• measurement compared to MadGraph5_aMC@NLO + Pythia8

• NLO calculation of ttbb using massive b-quarks

• Scales: μ = mtop1/2(pT(b)pT(bbar))1/4

11

[fb]bbttfid!

5 10 15 20 25 30 35 40

ATLAS InternalData

MG5_aMC@NLO+Pythia8

work in progress

Results• σttbbfid,measured = 12.9 +4.6 -4.4 fb (including ttH/ttZ in signal)• σttbbfid,measured = 12.1 ± 4.6 fb (subtracting ttH/ttZ from signal)• σttbbfid,theory = 14.3 +7.2 -4.8 fb

The measured cross-section agrees with NLO QCD calculations

Summary and outlook

12

• ttbb: difficult but interesting• measurement uncertainties are competitive with theory uncertainties• dominant uncertainties: modeling (23%), statistics (19%), b-tagging (15%)• Result is consistent with NLO QCD calculations

Outlook• improving the modeling uncertainties ⇐ better theory models (e.g. NLO ttbb, NLO

merged tt+jets samples etc)• statistics will be increased in Run 2• b-tagging uncertainty could be reduced by including more constraints from data (e.g.

more control regions can be included in a template fit)

Backup

• calculated with all MC that correspond to the different variations considered for the modeling uncertainty

• differences between models taken into account in the calculation of the cross-section

Fiducial efficiency

�fid =N reco&fid

NfidFiducial

Reco

14



Powheg+Pythia h

Powheg+Herwig

MadGraph+Pythia



[%]

fid!

24

68

101214

161820

ATLAS InternalSimulation

work in progress

√s = 8 TeV

Selecting the signal sample

Objects usedObjects used

Electrons • pT > 25 GeV, |η| < 2.47 • excluding 1.37 < |η| < 1.52

Muons • pT > 25 GeV, |η| < 2.5

Jets • Anti-kT R=0.4, pT > 25 GeV, |η| < 2.5

b-tagging • MV1 algorthm (70% efficiency)• diffent WP and MV1c were used for cross-checks•

Event pre-selection

single lepton triggers

exactly 2 opposite sign leptons

di-lepton mass cut: Mll > 15 GeV and |Mll - 90GeV| > 10 GeV (for ee,μμ events)

at least 2 b-tagged jets

Signal Region: exactly 4 b-jets

Fiducial volume

exactly 2 opposite sign leptons

di-lepton mass cut

veto events with ΔR(lepton,jet) < 0.4

exactly 4 particle b-jets

15

16

The full story

Denner, Feger, Scharf [1412.5290]

Non-resonant

O(α3sα) O(α2

sα2) O(αsα

3)

ttbb

O(α2sα

2) O(αsα3) O(α4)

ttH

O(αsα3) O(αsα

3) O(α4)

17

The full story


Interferenceincluded

• total cross-section for pp → l+vl jj bbbb 8% higher than pp → ttbb• pure EW production negligible• Non-resonant contribution small < 2%• Mixed QCD/EW terms significant• Destructive interference ∼5%

18

ttbb production - QCD and EW



• pure EW production negligible• Mixed QCD/EW terms significant (∼40%)• Destructive interference ∼4%

19

ttbb production (resonant part only)


O(α2sα

2) O(αsα3)


63% of total2 Wt vertices

probability for bottomnesschanging interaction:

1-0.9992 = 0.2%

37% of total4 Wt vertices

probability for bottomnesschanging interaction:

1-0.9994=0.4%

Total probability for bottomness changing interaction (e.g. incl. probability to have ttb+X) = 0.3%

What we assume:- Bottomness of proton is 0- QCD conserves bottomness- only EW interactions can produce an odd number of b

20

g→bb splitting kernels

dPg→qq̄ ∝ αs(Q2)

2π

1

2

�z2 + (1− z)2

�dz

Parton showers usually provide massless splitting kernels:

In Pythia8 mass dependence can be included:

dPg→QQ̄ ∝ αs(Q2)

2π

βQ

2

�z2 + (1− z)2+2(1− β2

Q)z(1− z)�dz

Several options in Pythia - TimeShower:weightGluonToQuark• 1 (default): neglect mass ⇒ low splitting probability in threshold region• 2: include mass dependence • 3: “DGLAP form” ⇒ high splitting probability out to large masses (upper bound) • 4: “ME form” ⇒ like 3 but with a phase-space suppression factor (lower bound)• 5-8: like 1-4 but using αs(m2) instead of αs(pT2)

Preliminary studies with MadGraph5_aMC@NLO+Pythia8 indicate a factor of 2 difference between the default and most extreme scenarios!This is still within the uncertainties of the measurement though.

R(jet,jet)!min0 1 2 3 4 5

b"

00.10.20.30.40.50.60.70.80.9

1

ATLAS Internal(35,40) GeV"Tp

(1.2,1.6)"#Top b-jetsOther b-jets

21

εb - what does it depend on?

tb

W

gb

b

• εfid ∝ εb4 ⇒ make sure that the b-tagging efficiency is under control

1. correction factors derived from tt events with exactly 2 b-jets

➡ can we rely on these SF for b-jets that come from gluon splittings?

2. correction factors derived from tt events where b-jets are back-to-back ⇒ b-jets usually contain only 1 B hadron

➡ can the same SF be used for b-jets with multiple B hadrons?

[GeV]T

p0 50 100 150 200 250 300 350 400

b!

00.1

0.20.30.40.5

0.60.70.8

0.91

=(67.3 +- 0.5)%b!Jets with 1 B =(69.0 +- 2.4)%b!Jets with at least 2 B

Documents

Measuring the ttbb production cross-section with 8 TeV ...sargyrop.web.cern.ch/sargyrop/DPGWuppertal.pdf · Measuring the ttbb production cross-section with 8 TeV ATLAS data Spyros