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Eur. Phys. J. C (2017) 77:172

DOI 10.1140/epjc/s10052-017-4718-8

Regular Article - Experimental Physics

Measurement of the tt production cross section using events

in the eµ ﬁnal state in pp collisions at

√

s = 13 TeV

CMS Collaboration

∗

CERN, 1211 Geneva 23, Switzerland

Received: 12 November 2016 / Accepted: 24 February 2017 / Published online: 20 March 2017

Abstract The cross section of top quark–antiquark pair

production in proton–proton collisions at

√

s = 13 TeV is

measured by the CMS experiment at the LHC, using data

corresponding to an integrated luminosity of 2.2 fb

−1

.The

measurement is performed by analyzing events in which the

ﬁnal state includes one electron, one muon, and two or more

jets, at least one of which is identiﬁed as originating from

hadronization of a b quark. The measured cross section is

815 ± 9(stat)± 38 (syst) ± 19 (lumi)pb, in agreement with

the expectation from the standard model.

1 Introduction

The measurement of the top quark–antiquark pair (t

t) cross

section provides a test of the hadroproduction of top quark

pairs as predicted by quantum chromodynamics (QCD). At

the CERN LHC,measurements havebeen performed inmany

different decay channels and at three different proton–proton

collision energies [1–24]. Precision measurements of these

cross sections allow for a test of their energy dependence

as predicted by QCD; they can also place constrains on the

parton distribution functions (PDFs) [25]. In combination

with some theory, they also provide unambiguous measure-

ments of interesting quantities, such as the top quark pole

mass [13,21], which is difﬁcult to determine by other means.

A detailed understanding of the production cross section is

also required in searches for evidence of new physics beyond

the standard model, as t

t production is often the dominant

background process. This is especially important if the sig-

nature for the new physics is similar to that of t

t produc-

tion [13,26]. This paper presents a measurement of the t

production cross section (σ

)inthee

∓

decay channel

using an event-counting method, based on observed yields.

The analysis follows closely [12], and uses the full data set

recorded by CMS at 13 TeV during 2015, which corresponds



e-mail: cms-publication-committee-chair@cern.ch

to an integrated luminosity of 2.2 fb

−1

. This represents a fac-

tor of 50 increase in the amount of data over the original anal-

ysis and allows for more detailed studies of the experimental

and theory uncertainties.

2 The CMS detector and Monte Carlo simulation

The CMS detector [27] has a superconducting solenoid in its

central region that provides an axial magnetic ﬁeld of 3.8 T.

The silicon pixel and strip trackers cover 0 <φ<2π in

azimuth and |η| < 2.5 in pseudorapidity. The lead tungstate

crystal electromagnetic calorimeter, and the brass and scin-

tillator hadron calorimeter are located inside the solenoid.

These are used to identify electrons, photons and jets. Muons

are measured in gas-ionization detectors embedded in the

steel ﬂux-return yoke outside the solenoid. The detector

is nearly hermetic, providing reliable measurement of the

momentum imbalance in the plane transverse to the beams.

A two-level trigger system selects the most interesting pp

collisions for ofﬂine analysis. A more detailed description of

the CMS detector, together with a deﬁnition of the coordi-

nate system used and the relevant kinematic variables, can

be found in Ref. [27].

Different Monte Carlo (MC) event generators are used to

simulate signal and background events. The next-to-leading-

order (NLO) powheg (v2) [28,29] generator is used for

t events, with the top quark mass (m

) set to 172.5 GeV.

The NNPDF3.0 NLO [30] PDFs are used. For the reference

t sample, the events are interfaced with pythia (v8.205)

[31,32] with the CUETP8M1 tune [33,34] to simulate parton

showering, hadronization, and the underlying event. Addi-

tional samples are produced by showering the events in the

reference sample with herwig++ (v2.7.1) [35] or by gen-

erating events using mg5_amc@nlo (v5_2.2.2) [36] inter-

faced with madspin [37] to account for spin correlations in

the decays of the top quarks, and using pythia for parton

showering and hadronization.

The mg5_amc@nlo generator is also used to simulate

W+jets events and Drell–Yan (DY) quark–antiquark anni-

123

172 Page 2 of 22 Eur. Phys. J. C (2017) 77 :172

hilation into lepton-antilepton pairs through a virtual pho-

ton or a Z boson exchange; for these backgrounds the event

yields are estimated from data. Single top quark events are

simulated using powheg (v1) [38,39] and pythia, and the

event yields are normalized to the approximate next-to-next-

to-leading order (NNLO) cross sections from Ref. [40]. The

diagram removal approach [41] is used to handle the interfer-

ence between the t

t and tW ﬁnal states starting at NLO. The

contributions from WW, WZ, and ZZ (referred to as “VV”)

processes are simulated with pythia, and the event rates are

normalized to the NLO cross sections from Ref. [42]. Other

contributions from W and Z boson production in associa-

tion with t

t events (referred to as “ttV”) are simulated using

mg5_amc@nlo and pythia. The simulated samples include

additional interactions per bunch crossing (pileup), with the

distribution matching that observed in data, with an average

of about 11 collisions per bunch crossing.

The SM prediction for σ

at 13 TeV is 832

+20

−29

(scales) ±

35 (PDF+α

) pb for m

= 172.5 GeV, as calculated with the

Top++ program [43] at NNLO in perturbative QCD, includ-

ing soft-gluon resummation at next-to-next-to-leading-log

order [44]. The ﬁrst uncertainty reﬂects uncertainties in the

factorization (μ

) and renormalization (μ

) scales. The sec-

ond one is associated with possible choices of PDFs and

the value of the strong coupling constant, following the

PDF4LHC prescriptions [45,46], using the MSTW2008 68%

conﬁdence level NNLO [47,48], CT10 NNLO [49,50], and

NNPDF2.3 5f FFN [51] PDF sets. The expected event yields

for signal in all ﬁgures and tables are normalized to this cross

section.

3 Event selection

In the SM, top quarks in pp collisions are mostly produced

as t

t pairs, where each top quark decays predominantly to

a W boson and a bottom quark. In t

t events where both W

bosons decay leptonically, the ﬁnal state contains two leptons

of opposite electric charge and at least two jets coming from

the hadronization of the bottom quarks.

At the trigger level, a combination of the single lepton

and dilepton triggers is used. Events are required to contain

either one electron with transverse momentum p

> 12 GeV

and one muon with p

> 17 GeV or one electron with

> 17 GeV and one muon with p

> 8 GeV. In addi-

tion, single-lepton triggers with one electron (muon) with

> 23 GeV (20) are used in order to increase the efﬁciency.

The efﬁciency for the combination of the single lepton and

dilepton triggers is measured in data using triggers based on

imbalance in the event. The trigger efﬁciency is mea-

suredtobe0.99 ±0.01 (combined statistical and systematic

uncertainties) when the selection on the leptons described

below is applied. The trigger in simulation is corrected using

a multiplicative data-to-simulation scale factor (SF), given

by the trigger efﬁciency measured in data with independent

monitoring triggers.

The particle-ﬂow (PF) event algorithm [52,53] recon-

structs and identiﬁes each individual particle with an opti-

mized combination of information from the various ele-

ments of the CMS detector. Selected dilepton events are

required to contain one isolated electron [54] and one isolated

muon [55] with opposite electric charge and p

> 20 GeV

and |η| < 2.4. Isolation requirements are based on the ratio

of the scalar sum of the transverse momenta of all PF can-

didates, reconstructed inside a cone centered on the lepton,

excluding the contribution from the lepton candidate. This

isolation variable is required to be smaller than 7% (15%) of

the electron (muon) p

In events with more than one pair of leptons passing

the selection, the two opposite-sign different-ﬂavour leptons

with the largest p

are selected for further study. Events with

W bosons decaying into τ leptons contribute to the measure-

ment only if the τ leptons decay into electrons or muons that

satisfy the selection requirements.

The efﬁciency of the lepton selection is measured using

a “tag-and-probe” [56] method in a sample of same-ﬂavour

dilepton events, which is enriched in Z boson candidates.

The measured p

- and η-dependent values for the combined

identiﬁcation and isolation efﬁciencies average to about 80%

for electrons and 90% for muons. To account for the differ-

ence in efﬁciencies determined using data and simulation,

the event yield in simulation is corrected using p

- and η-

dependent SFs based on a comparison of lepton selection

efﬁciencies in data and simulation. These have an average of

0.99 for electrons and 0.98 for muons.

In order to suppress backgrounds from DY production of

τ lepton pairs with low invariant dilepton mass, t

t candidate

events are further required to have a dilepton pair of invariant

mass m

eμ

> 20 GeV.

Jets are reconstructed from the PF particle candidates

using the anti-k

clustering algorithm [57,58] with a distance

parameter of 0.4. The jet momentum is determined from the

vectorial sum of all particle momenta in the jet, and is found

from simulation to be within 5 to 10% of the true momentum

over the whole p

spectrum and detector acceptance. An off-

set correction is applied to jet energies to take into account

the contribution from additional proton–proton interactions

within the same or nearby bunch crossings. Jet energy cor-

rections are derived from simulation, conﬁrmed with in situ

measurements of the energy balance in dijet and photon +

jet events, and are applied as a function of the jet p

and

η [59] to both data and simulated events. The t

t candidate

events are required to have at least two reconstructed jets

with p

> 30 GeV and |η| < 2.4.

Since t

t events decay into ﬁnal states containing a bottom

quark–antiquark pair, requiring the presence of jets identiﬁed

123

Eur. Phys. J. C (2017) 77 :172 Page 3 of 22 172

as originating from b quarks (“b jets”) reduces backgrounds

from DY and W+jets production. Jets are identiﬁed as b jets

using the combined secondary vertexalgorithm [60,61], with

an operating point which yields an identiﬁcation efﬁciency

of 67% and a misidentiﬁcation (mistag) probability of about

1% and 15% [61] for light-ﬂavour jets (u, d, s, and gluons)

and c jets, respectively. The selection requires the presence

of at least one b jet in the event.

4 Background determination

Background events arise primarily from single top quark,

DY, and VV events in which at least two prompt leptons are

produced by Z or W boson decays. The single top quark and

VV contributions are estimated from simulation.

The DY event yield is estimated from data using the

“R

out/in

” method [1,2,6], where events with same-ﬂavour

leptons are used to normalize the yield of e

∓

pairs from

DY production of τ lepton pairs. A data-to-simulation nor-

malization factor is estimated from the number of events in

data within a 15 GeV window around the Z boson mass and

extrapolated to the number of events outside the Z mass win-

dow with corrections applied using control regions enriched

in DY events in data. The SF is found to be 0.95 ±0.05 (sta-

tistical uncertainty) after applying the ﬁnal event selection.

Other background sources, such as t

t or W+jets events in

the lepton+jets ﬁnal state, can contaminate the signal sample

if a jet is incorrectly reconstructed as a lepton, or the lep-

ton is incorrectly identiﬁed as being isolated. This is more

important for electrons. For muons, the dominant contribu-

tion comes from the semileptonic decay of bottom or charm

quarks. These events are grouped into the nonprompt lep-

tons category (“non-W/Z leptons”) since prompt leptons are

deﬁned as originating from decays of W or Z boson, together

with contributions that can arise, for example, from decays

of mesons or photon conversions.

The contribution of non-W/Z lepton events is estimated

from a control region of same-sign (SS) events and propa-

gated in the opposite-sign (OS) signal region. The SS control

region is deﬁned using the same criteria as the nominal sig-

nal region, except for requiring eμ pairs with the same elec-

tric charge. The SS dilepton events are predominantly events

containing misidentiﬁed leptons. Other SM processes pro-

duce prompt SS or charge-misidentiﬁed dilepton events with

signiﬁcantly smaller rates; these are estimated using simula-

tion and subtracted from the observed number of events in

data.

The scaling from the SS control region in data to the signal

region is performed through the ratio of the numbers of OS to

SS events with misidentiﬁed leptons in simulation. This ratio

is calculated using simulated t

t and W+jets samples, which

are rich in nonprompt dilepton events, and is measured to be

Events

10×

Data

t t

Non W/Z

Vt VV + t

e→*γ Z/

(13 TeV)

-1

2.2 fb

CMS

* e

•

Number of jets

0123 4≥

Data/MC

0.6

1.4

Fig. 1 Distribution of the jet multiplicity in events passing the dilepton

selection criteria. The expected distributions for t

t signal and individual

backgrounds are shown after corrections based on control regions in

data are applied; the last bin contains the overﬂow events. The ratio

of data to the sum of the expected yields is given at the bottom of the

ﬁgure. The error bars, which are within the size of the points, indicate

the statistical uncertainties

1.4 ± 0.1 (stat). In data, 152 SS events are observed, with

a contribution of 79.8 ± 1.9 (stat) prompt lepton SS events

as evaluated from simulation. In total 104 ± 8 (stat + syst)

events with misidentiﬁed leptons contaminating the signal

regionare predicted. This agrees within the uncertainties with

predictions from the simulation.

Figure 1 shows the multiplicity of jets for events passing

the dilepton criteria. The MC simulation does not describe

well the data for events with ≥4 jets, the region in which par-

ton shower effects are expected to dominate the prediction.

After requiring at least two jets, Fig. 2 shows the p

and |η|

distributions of the selected leptons, and Fig. 3 shows the

(a, c) and |η| (b, d) distributions of the two most ener-

getic jets; Fig. 3(e) shows the scalar sum of the transverse

momenta of all jets (H

) and Fig. 3(f) the b jet multiplicity.

Good agreement between data and the predictions for signal

and background is observed.

5 Sources of systematic uncertainty

Table 1 summarizes the statistical uncertainty and the dif-

ferent sources of systematic uncertainties in the measured t

production cross section.

The uncertainty in the trigger efﬁciency SF applied to

simulation to correct for differences with respect to data is

1.1%. The uncertainty in the SF applied to correct the elec-

tron (muon) identiﬁcation efﬁciency is found to be about

1.8%(1.5%), with some dependence on the lepton p

and η.

The modeling of lepton energy scales was studied using

Z → ee/μμ events in data and simulation, resulting in

123

172 Page 4 of 22 Eur. Phys. J. C (2017) 77 :172

Events/5 GeV

500

1000

1500

Data

t t

Non W/Z

Vt VV + t

e→*γ Z/

(13 TeV)

-1

2.2 fb

CMS

(a)

2 jets≥ +

* e

•

(GeV)

Electron p

20 40 60 80 100 120 140 160 180 200

0.6

1.4

Events/0.1 units

500

1000

Data

t t

Non W/Z

Vt VV + t

e→*γ Z/

(13 TeV)

-1

2.2 fb

CMS

(b)

2 jets≥ +

* e

•

|ηElectron |

0 0.5 1 1.5 2 2.5

Data/M

0.6

1.4

Events/5 GeV

500

1000

1500

Data

t t

Non W/Z

Vt VV + t

e→*γ Z/

(13 TeV)

-1

2.2 fb

CMS

(c)

2 jets≥ +

* e

•

(GeV)

Muon p

20 40 60 80 100 120 140 160 180 200

Data/MC

0.6

1.4

Events/0.1 units

500

1000

Data

t t

Non W/Z

Vt VV + t

e→*γ Z/

(13 TeV)

-1

2.2 fb

CMS

(d)

2 jets≥ +

* e

•

|ηMuon |

0 0.5 1 1.5 2 2.5

Data/MC

0.6

1.4

Fig. 2 The distributions of a p

and b |η| of the electron, and c p

and d |η| of the muon after the selection of jets and before the b jet

requirement. The expected distributions for t

t signal and individual

backgrounds are shown after corrections based on control regions in

data are applied; for the left plots (a, c) the last bin contains the over-

ﬂow events. The ratios of data to the sum of the expected yields are

given at the bottom of each panel .Theerror bars indicate the statistical

uncertainties

an uncertainty for the electron (muon) energy scale of

1.0(0.5)%. These values are used to obtain the effect on the

signal acceptance, which is taken as a systematic uncertainty.

The impact of uncertainties in jet energy scale (JES) and

jet energy resolution (JER) is estimated from the change

observed in the number of simulated t

t events selected after

changing the jet momenta within the JES uncertainties, and

for JER by an |η|-dependent variation of the JER scale factors

within their uncertainties.

The uncertainties resulting from the b tagging efﬁciency

and misidentiﬁcation rate are determined by varying the b

tagging SF of the b jets and the light-ﬂavour jets, respectively.

These uncertainties depend on the p

and η of the jet and

amount to approximately 2% for b jets and 10% for mistagged

jets [61]int

t signal events. They are propagated to the tt

selection efﬁciency using simulated events.

The uncertainty assigned to the number of pileup events

in simulation is obtained by changing the inelastic proton–

proton cross section, which is used to estimate the pileup in

data, by ±5% [62].

The systematic uncertainty related to the missing higher-

order diagrams in powheg is estimated as follows: the uncer-

tainty in the signal acceptance is determined by changing the

and μ

scales in powheg independently up and down by

a factor of two, with the uncertainty taken as the maximum

observed difference.

The predictions of the NLO generators powheg and

mg5_amc@nlo for t

t production are compared, where both

use pythia for hadronization, fragmentation, and additional

radiation description. The difference in the signal acceptance

between the two is taken as an uncertainty.

The uncertainty arising from the hadronization model

mainly affects the JES and the fragmentation of b quark

jets. The uncertainty in the JES already contains a contri-

bution from the uncertainty in the hadronization. In addition,

we determine a related uncertainty by comparing samples

123

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