JHEP04(2022)144

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Published for SISSA by Springer

Received: December 16, 2021 Accepted: March 29, 2022 Published: April 26, 2022

Measurement of the inclusive t ¯ t production cross section in proton-proton collisions at √

s = 5.02 TeV

The CMS collaboration

Abstract: The top quark pair production cross section is measured in proton-proton collisions at a center-of-mass energy of 5.02 TeV. The data were collected in a special LHC low-energy and low-intensity run in 2017, and correspond to an integrated luminosity of 302 pb⁻¹. The measurement is performed using events with one electron and one muon of opposite charge, and at least two jets. The measured cross section is 60.7±5.0 (stat)± 2.8 (syst)±1.1 (lumi) pb. A combination with the result in the single lepton + jets channel, based on data collected in 2015 at the same center-of-mass energy and corresponding to an integrated luminosity of 27.4 pb⁻¹, is then performed. The resulting measured value is 63.0±4.1 (stat)±3.0 (syst+lumi) pb, in agreement with the standard model prediction of 66.8⁺²−3^..⁹1pb.

Keywords: Hadron-Hadron Scattering, Top Physics ArXiv ePrint: 2112.09114

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Contents

1 Introduction 1

2 The CMS detector and Monte Carlo simulation 2

3 Object reconstruction and event selection 3

4 Background estimation 5

5 Systematic uncertainties 5

6 Results 8

7 Summary 11

The CMS collaboration 16

1 Introduction

The top quark is the most massive elementary particle in the standard model (SM). The study of its production and properties is one of the core elements of the CERN LHC physics program. At the LHC, top quarks are primarily produced in pairs (tt), and the tt production cross section is sensitive to the gluon parton distribution function (PDF) of the proton [1] and to the top quark pole mass [2]. The ATLAS, CMS, and LHCb Collaborations have performed several cross section measurements with increasing precision in a variety of decay channels at four proton-proton (pp) collision energies [3–12], as well as in proton-nucleus [13] and nucleus-nucleus [14] collisions.

The first measurement of the tt production cross section, σ_tt, in pp collisions at a center-of-mass energy of 5.02 TeV, was performed by the CMS experiment analyzing events with one or two leptons (`= electron or muon) and at least two jets, using a data sample taken in 2015 that corresponds to an integrated luminosity of 27.4 pb⁻¹. The measurement of σ_tt = 69.5±6.1 (stat)±5.6 (syst)±1.6 (lumi) pb was obtained from the combination of the results in the dilepton and single lepton decay channels [3].

During the year 2017, the LHC delivered a subset of pp collisions at √

s= 5.02 TeV and CMS collected a data sample corresponding to 302 pb⁻¹, an increase in integrated luminosity of more than an order of magnitude compared to the data set recorded in 2015.

A distinct feature of this data sample is the low number of additional interactions per bunch crossing (pileup) with respect to the standard operating conditions of the LHC. We present here a measurement ofσ_tt using events with two opposite-charge different-flavor leptons, i.e., one electron and one muon (e^±^µ^∓), and at least two jets. The cross section is extracted

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using a counting experiment and the result is then combined with the measurement in the

`+jets final state contained in ref. [3].

This paper is organized as follows. A brief description of the CMS detector, and of the Monte Carlo (MC) simulation samples, are given in section 2, followed by the object and event selection in section 3. The background estimation methods are covered in section4 and the systematic uncertainties in section 5. Results are discussed in section 6 and the summary is given in section7. Tabulated results are provided in HEPData [15].

2 The CMS detector and Monte Carlo simulation

The central feature of the CMS apparatus is a superconducting solenoid of 6 m internal diameter, providing a magnetic field of 3.8 T. Within the solenoid volume are a silicon pixel and strip tracker, a lead tungstate crystal electromagnetic calorimeter (ECAL), and a brass and scintillator hadron calorimeter (HCAL), each composed of a barrel and two endcap sections. Forward calorimeters extend the pseudorapidity (η) coverage provided by the barrel and endcap detectors. Muons are detected in gas-ionization chambers embedded in the steel flux-return yoke outside the solenoid. A more detailed description of the CMS detector, together with a definition of the coordinate system used and the relevant kinematic variables, can be found in ref. [16].

Simulated event samples are used to define the analysis strategy, to estimate the background contribution, and to evaluate efficiencies and uncertainties. The samples used in the analysis are summarized in table 1. The propagation of the generated particles through the CMS detector and the modeling of the detector response are performed using Geant4[17].

Simulated tt events are generated at next-to-leading order (NLO) in quantum chromodynamics (QCD) using powheg (v2) [18–20], assuming a top quark massm_t of 172.5 GeV.

The events are then interfaced with pythia 8 (v230) [21] with the “CP5” tune [22] for parton showering, hadronization, and the underlying event description. For the study of the acceptance dependence on m_t, alternative generator-level samples have been used with m_t = 166.5 and 178.5 GeV. The NNPDF3.1 [23] next-to-next-to-leading-order (NNLO) PDFs are used. A similar setup is used for the simulation of the single top quark production in association with a W boson (tW).

The MadGraph5_amc@nlo (v2.4.2) generator [24], interfaced with pythia 8 for parton showering, is used to simulate W boson production with additional jets (W+jets), and Drell-Yan (DY) quark-antiquark annihilation into lepton-antilepton pairs through Z boson or virtual-photon exchange. The simulation is performed at NLO in QCD and includes up to two extra partons at the matrix element (ME) level. The FxFx matching scheme [25] is used to merge jets from the ME calculations and the parton shower (PS).

Diboson (VV, with V = W or Z) events are simulated at NLO in QCD withpowheg (v2).

When available, higher-order cross sections are used instead of those of the generator, as shown in table 1.

The SM prediction for σ_tt at 5.02 TeV is 66.8⁺¹−2^..⁹3(scale)±1.7 (PDF)⁺¹−1^..⁴3(α_S(m_Z)) pb form_t = 172.5 GeV and a strong coupling at the Z boson mass,α_S(m_Z), of 0.118±0.001 [30].

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Process Generator + parton shower Cross section order tt powheg +pythia8 NNLO+NNLL [26,27]

tW powheg +pythia8 Approximate NNLO [28]

W+jets MadGraph5_amc@nlo+pythia8 NNLO[QCD]+NLO[EW] [29]

DY MadGraph5_amc@nlo+pythia8 NNLO[QCD]+NLO[EW] [29]

VV powheg +pythia8 NLO

Table 1. Summary of MC samples used to model the signal and background processes. The column

“Cross section order” corresponds to the QCD or electroweak (EW) precision used to normalize the distributions provided by the generators. Where no reference is given, the precision of the MC simulation is kept.

This prediction is calculated with the Top++program [26] at NNLO in perturbative QCD including soft-gluon resummation at next-to-next-to-leading-log (NNLL) approximation [27].

The first uncertainty reflects variations in the factorization (µ_F) and renormalization (µ_R) scales. The second and third uncertainties are associated with possible choices of PDFs and theα_S value respectively, using the NNPDF3.1 [23] NNLO PDF sets that include top quark measurements. The expected integrated event yields for signal in all figures and tables are normalized to the predicted cross section.

The simulated samples include multiple pp collisions occurring in the same bunch crossing (pileup), with a distribution that matches that observed in data, with an average of about two pileup collisions per bunch crossing.

3 Object reconstruction and event selection

Events of interest are selected online using a two-tiered trigger system [31,32]. The first level (L1), composed of custom hardware processors, uses information from the calorimeters and muon detectors to select events at a rate of around 100 kHz within a fixed latency of less than 4µs. The second level, known as the high-level trigger, consists of a farm of processors running a version of the full event reconstruction software optimized for fast processing, and reduces the event rate to around 1 kHz before data storage. Only events that fired at least one of the single-lepton triggers with transverse momentum (p_T) thresholds greater than 17 (12) GeV in the case of electrons (muons) are considered.

Events may contain multiple primary vertices, corresponding to pileup collisions. The candidate vertex with the largest value of summed physics-object p²_T is taken to be the primary pp interaction vertex. The physics objects are the jets, clustered using the jet finding algorithm [33, 34] using tracks assigned to candidate vertices as inputs, and the associated missing transverse momentum, taken as the negative vector sum of the p_T of those jets.

The particle-flow algorithm [35] aims to reconstruct and identify each individual particle in an event, with an optimized combination of information from the various elements of the CMS detector. The energy of electrons is determined from a combination of the electron momentum as measured by the tracker, the energy of the corresponding ECAL cluster, and the energy sum of all bremsstrahlung photons spatially compatible with originating from the electron track. The energy of muons is obtained from the curvature of the corresponding

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track. The energy of charged hadrons is determined from a combination of their momentum measured in the tracker and the matching ECAL and HCAL energy deposits, corrected for the response function of the calorimeters to hadronic showers. Finally, the energy of neutral hadrons is obtained from the corresponding corrected ECAL and HCAL energies.

Jets are clustered from these reconstructed particles using the anti-k_T algorithm [33,34]

with a distance parameter of 0.4. The jet momentum is determined as the vectorial sum of all particle momenta in the jet, and is found from simulation to be, on average, within 5 to 10% of the true momentum over the wholep_T spectrum and detector acceptance. Jet energy corrections are derived from simulation studies so that the average measured energy of jets becomes identical to that of particle-level jets. Measurements of the momentum balance are used to determine any residual differences between the jet energy scale in data and in simulation, and appropriate corrections are made [36]. These corrections were derived using the full low-pileup data set of pp collisions at 5.02 TeV. Additional selection criteria are applied to remove jets potentially dominated by instrumental effects or reconstruction failures [37].

Electron candidates are required to satisfy |η| < 2.5 and p_T > 10 GeV. To identify electrons, requirements are placed on a multivariate discriminant based on the shower shape and track quality of the electron candidates [38]. Electron candidates that are matched to a secondary vertex consistent with a photon conversion, or have a missing hit in the inner layer of the tracker are vetoed.

Reconstructed muon candidates are required to have |η|<2.4 and p_T >10 GeV, and must fulfill criteria on the geometrical matching between the tracks reconstructed by the silicon tracker and the muon system, and on the quality of the global fit [39].

Lepton candidates must be consistent with originating from the primary vertex which is ensured by requiring that the transverse (longitudinal) impact parameter should not exceed 0.05 (0.10) cm. Furthermore, the significance of the three-dimensional impact parameter must be smaller than 8. Electrons and muons must also satisfy a requirement on their relative isolation (I_rel), defined as the scalar p_T sum of all the particles inside a cone around the lepton direction, excluding the lepton itself, divided by the lepton p_T. The cone size, defined as ∆R=^p(∆η)²+ (∆φ)², whereφis the azimuthal angle, changes as a function of the leptonp_Tas ∆R(p_T) = 10 GeV/p_Tif 50 GeV< p_T<200 GeV, ∆R= 0.2 ifp_T≤50 GeV and ∆R= 0.05 otherwise. Electrons (muons) must satisfy the conditionI_rel <0.085 (0.325).

To reject leptons originating from hadron decays, or misidentified leptons, also referred to as “nonprompt” leptons, from those produced in the decay of the electroweak bosons (“prompt”), a gradient boosted decision tree (BDT) is used, trained using MC simulation, to distinguish prompt from nonprompt leptons [40]. This BDT uses the properties of the jet containing the lepton, as returned by the jet clustering algorithm: its b tagging score, the ratio of the lepton p_T to that of the jet, and the momentum of the jet transverse to the lepton direction. Other input variables are the leptonp_T,η,I_rel, longitudinal and transverse impact parameters, and the significance of the three-dimensional impact parameter. In addition, the previously mentioned multivariate discriminant for electrons and the muon segment compatibility for muons are used as input variables [39]. To further suppress nonprompt leptons originating from b quark decays, leptons associated with a jet satisfying the loose working point of the DeepCSV b tagging algorithm [41] are rejected.

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The tt candidate events are required to have at least two leptons (one electron and one muon) with opposite charge and at least two jets. Only jets with p_T >25 GeV, |η|<2.4, and containing no selected leptons are considered. To ensure efficient triggering of the events, the leading lepton is required to havep_T>20 GeV. In addition, events must have a dilepton invariant mass above 20 GeV to reduce the background from photon conversions and low-mass resonances.

4 Background estimation

Background events arise mainly from tW, DY, and VV production in which at least two prompt leptons emerge from the Z or W boson decays. The tW and VV contributions are estimated from simulation.

The DY event yield is estimated from data using the R_out_/_in method [6], where events with same-flavor leptons are used to normalize the yield of different-flavor pairs from DY production of^τ lepton pairs. A data-to-simulation normalization 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 boson mass window with corrections applied using control regions enriched in DY events in data. This factor is measured to be 0.91±0.01. The stability of the method against a potential mismodeling of the jet multiplicity is checked and found to be within 30%, which will be considered as an extra systematic uncertainty in this background estimation.

Other residual background sources, such as tt where only one of the W bosons decay leptonically or W+jets events, may contaminate the signal sample when a jet is misrecon- structed as a lepton, or contains a lepton from a b/c hadron decay, incorrectly identified as a prompt lepton. These events are grouped into the nonprompt lepton category, together with meson decays and photon conversions; their contribution is estimated with simulated tt events with at least one W boson decaying into jets and W+jets events.

Figure 1shows thep_T of the two leptons and of the leading jet, and the jet multiplicity of the selected events. The data are compared to the sum of the expected signal and background distributions for the tt signal and individual backgrounds, which are derived either from simulated samples or from data, as described above. The expected distributions describe the data within the experimental uncertainties.

5 Systematic uncertainties

The measurement of σ_tt is affected by sources of systematic uncertainty related to detector effects or theoretical assumptions. Each source of systematic uncertainty is evaluated by repeating the σ_tt extraction with variations of the input parameters by ±1 standard deviations (experimental uncertainty) or from dedicated simulation samples with different settings (theoretical uncertainty). The experimental uncertainties affect mostly the efficiency, while modeling uncertainties affect both the acceptance and the efficiency. The total uncertainty is calculated by adding the effects of all the individual systematic components

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0 50 100

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Figure 1. Leading lepton p_T (upper left), sub-leading lepton p_T (upper right), leading jet p_T (lower left), and jet multiplicity (lower right) in the selected events. The hatched band corresponds to systematic and statistical uncertainties summed in quadrature. The lower panels show the data-to-prediction ratio. The last bin in each distribution includes overflow events.

in quadrature, assuming they are independent. The sources of systematic uncertainty are described in detail below:

Lepton-related uncertainty: Lepton reconstruction and identification efficiencies, as well as energy scale and resolution, are measured using Z boson events in low-pileup data and simulation of pp collisions at 5.02 TeV [38,39]. Correction factors are then applied to the simulation to improve the agreement with the data. The uncertainty in these corrections is propagated to the σ_tt measurement. For the selected events, the trigger efficiency is very close to 1, as the trigger conditions are satisfied redundantly by both leptons in most of the events. The deviation of the efficiency from unity, obtained from a tt simulated sample, is used as the associated uncertainty in σ_tt. Jet-related uncertainty: The impact of the uncertainty in jet energy scale (JES) is

estimated from the change in the number of simulated tt events selected after changing the jet momenta within the JES uncertainties [36]. The effect of the jet energy resolution (JER) is determined by an η-dependent variation of the JER scale factors within their uncertainty.

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L1 prefiring: During the 2017 data taking, a gradual shift in the timing of the inputs of the ECAL L1 trigger in the region|η|>2.0 caused a trigger inefficiency [32]. Simulations are corrected to mimic this behavior in data and the uncertainty in these corrections is propagated to σ_tt by varying the correction within the associated uncertainty.

Scale choice: The uncertainty related to the missing higher-order diagrams in powhegis estimated by varying the defaultµ_F andµ_R choices independently by a factor of 2 and 1/2. As uncertainty in the signal acceptance is assigned the maximum difference of each variation from the nominal values, excluding variations of the scales in opposite directions.

Parton shower scale: The effect of the choice of PS scale is studied by changing the scale used for the initial- and final-state radiation by a factor 2 and 1/2 with respect to its default value. The maximum variation with respect to the central sample is taken as the uncertainty.

Matrix element and PS matching (h_damp): The impact of the ME and PS matching, which is parameterized by the powheg generator as h_damp, with a nominal value of (1.4⁺⁰−0.5^.⁹)m_t [22], is calculated by varying this parameter within the uncertainties, using dedicated samples. The variation with respect to the central value of the signal acceptance at particle level is considered as the uncertainty in the σ_tt extraction.

Parton distribution functions: The uncertainty due to the proton PDFs is evaluated by reweighting simulated signal events using the replicas of the NNPDF3.1 set [23].

The variations consist of a central PDF and 100 replicas, for which the root mean square of all differences of the resulting σ_tt with respect to the central value is taken as the uncertainty. Two extra variations corresponding to different α_S(m_Z) choices are added in quadrature [42].

Underlying event tune: The parameters of pythiaare adjusted to model the measured underlying event tune [22]. The uncertainty is calculated by varying these parameters within their uncertainties in dedicated simulated samples. The variation with respect to the central value of the signal acceptance is taken as the uncertainty.

Background normalization: The uncertainty in the tW and VV cross sections is taken to be 20 and 30%, respectively, based on the theoretical uncertainties and the effect of finite size of the simulated samples. To the nonprompt background estimation is assigned a 50% uncertainty to account for possible mismodeling of the data in simulation. As explained in section 4, a 30% uncertainty is considered for the DY background normalization.

Pileup and integrated luminosity: The uncertainty assigned to the number of pileup events in simulation is calculated by varying the total inelastic pp cross section by 4.6% [43]. The impact of this uncertainty on the result is negligible, as the number of pileup events is also small. The uncertainty in the measurement of the integrated luminosity is estimated to be 1.9% [44].

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Source ∆σ_tt/σ_tt (%)

Electron efficiency 1.6

Muon efficiency 0.6

Trigger efficiency 1.3

JES 2.2

JER 1.2

L1 prefiring 1.4

µ_R,µ_F scales 0.2

Final-state radiation 1.1 Initial-state radiation <0.1

h_damp 1.0

PDF⊕α_S(m_Z) 0.3

Underlying event tune 0.7

tW 1.0

Nonprompt leptons 0.4

Drell-Yan 1.8

VV 0.8

Total systematic uncertainty 4.3 Integrated luminosity 1.9 Statistical uncertainty 8.2

Table 2. Summary of the systematic and statistical relative uncertainties for the inclusive tt cross section measurement.

Table 2 summarizes the sources of systematic and statistical uncertainties in the measured σ_tt, as obtained using eq. (6.1), explained in the next section. The result is dominated by the statistical uncertainty, while the uncertainty in the JES and the DY background estimate constitute the largest systematic uncertainties.

6 Results

The tt production cross section is extracted via the expression

σ_tt = N−N_bkg

εABL , (6.1)

where N is the number of observed events, N_bkg is the number of estimated background events, L is the integrated luminosity, B = 3.19% is the SM value [30] of the branching fraction of a W boson pair to e^±^µ^∓, including decays through ^τ leptons, A is the total acceptance, defined as the fraction of all generated tt →e^±µ^∓events fulfilling the aforemen- tioned kinematic selection criteria, andε is the reconstruction efficiency. The acceptance is estimated from simulation and is found to be 0.54±0.01. The efficiency is estimated

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Process Event yield

tW 8±2

Nonprompt leptons 2±1

DY 10±4

VV 4±1

Total background 24±4

tt 187±9

Data 194

Table 3. Event yields for all the processes at the final level of selection. The uncertainty corresponds to the quadratic sum of the statistical and systematic sources.

from simulation, after applying all the correction factors for leptons and jets to match the performance of the data, and is measured to be 0.53±0.02. Table 3 shows the total number of events observed in data together with the total number of expected signal and background events.

The measured inclusive cross section for a top quark mass of 172.5 GeV is σ_tt = 60.7±5.0 (stat)±2.8 (syst)±1.1 (lumi) pb.

The fiducial cross section (σ_tt^fid) is measured for events containing one electron and one muon withp_T >10 GeV and|η|<2.4, invariant mass of the pair of at least 20 GeV, a leading leptonp_T of at least 20 GeV, and at least two jets withp_T>25 GeV and |η|<2.4. For the fiducial cross section measurement, an estimate of the uncertainties similar to that shown in table2is made. The resulting value isσ^fid_tt = 1.05±0.09 (stat)±0.05 (syst)±0.02 (lumi) pb.

The acceptance has been predicted for m_t = 166.5 and 178.5 GeV and is parameterized as a linear function ofm_t. The cross section varies by ∓0.30 pb when the top quark mass changes by±0.5 GeV.

The result is combined with that obtained in the `+jets decay channel of ref. [3], corresponding to an integrated luminosity of 27.4 pb⁻¹. The result obtained in the dilepton decay channel of ref. [3] was not added to the combination, as its contribution would be negligible. We determine the combinedσ_tt using the best linear unbiased estimator (BLUE) method [45,46]. The 2015 measurement in the`+jets channel yielded a cross section of σ_tt = 68.9 pb with a total uncertainty of 13%, dominated by the statistical uncertainty.

Most sources of experimental uncertainty are considered as uncorrelated, given that the data sets and background estimation methods are different, with the exception of the uncertainties on the tW background and the scale choice, which are considered as fully correlated. The modeling uncertainties are taken as fully correlated. The resulting cross section is

σ_tt^comb = 63.0±4.1 (stat)±3.0 (syst+lumi) pb,

where the total uncertainty of 8.0% is the quadrature sum of the individual sources of uncertainty. The weights of the individual measurements, to be understood in the sense of

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(TeV)

2 4 6 8 10 12 s 14

cross section (pb)t Inclusive t

10 10

2

10

3 eµ(2017)⊕ l+jets(2015), 5.02 TeV (L = 302 ^⊕^{27.4 pb}^-1⁾

CMS

-1) , 7 TeV (L = 5 fb eµ

-1) l+jets, 7 TeV (L = 2.3 fb

-1) , 8 TeV (L = 19.7 fb eµ

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NNPDF3.1 MSHT20

CT18 ABMP16

jets(2015)

⊕l+

(2017) eµ

015) (2 jets l+

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⊕µ eµ

Figure 2. Inclusive tt cross section in pp collisions as a function of the center-of-mass energy in the separate`+jets and dilepton channels along with the combined measurement at 5.02 TeV presented in this analysis are displayed. Some of the previous CMS measurements at √

s = 7, 8 [6,7], and 13 TeV [2,11] are also shown. The NNLO+NNLL theoretical prediction [27] using the NNPDF3.1 [23] PDF set withα_S(m_Z) = 0.118 andm_t= 172.5 GeV is shown in the main plot. In the inset, predictions at 5.02 TeV using the MSHT20 [48], CT18 [49], and ABMP16 [50] NNLO PDF sets, the latter withα_S(m_Z) = 0.115 andm_t= 170.4 GeV, are compared, along with the NNPDF3.1 NNLO prediction, to the individual and combined results from this analysis. The vertical bars and bands represent the total uncertainties in the data and in the predictions, respectively. Points corresponding to measurements at the same √

sare horizontally shifted for better readability.

ref. [46], are 27 and 73% for the `+jets [3] and the measurement presented in this paper, respectively. This result is in agreement with the SM prediction.

The combined result is found to be robust by performing an iterative variant of the BLUE method [47] and varying some assumptions on the correlations of different combinations of systematic uncertainties. Also, the correlations between the nuisance parameters in both channels have been checked and found to have a negligible impact.

Figure 2 presents a summary of the CMS measurements [2,6,7,10,11] of σ_tt in pp collisions at different√

sin the `+jets and dilepton channels, including the one presented in this paper, compared to the NNLO+NNLL prediction using the NNPDF3.1 NNLO PDF set withα_S(m_Z) = 0.118 andm_t = 172.5 GeV. In the inset, the results from this analysis at

√s= 5.02 TeV are also compared to the predictions from the MSHT20 [48], CT18 [49], and ABMP16 [50] NNLO PDF sets, with the latter using α_S(m_Z) = 0.115 andm_t = 170.4 GeV.

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Theoretical predictions using different PDF sets have comparable values and uncertainties, once consistent values of α_S(m_Z) and m_t are associated with the respective PDF set.

The impact of the combined σ_tt measurement at √

s= 5.02 TeV on the knowledge of the proton PDFs is tested following the MC methodology of ref. [3]. Improvement with respect the baseline fit (i.e., without the inclusion of tt measurements) is observed, verifying the findings of ref. [3] that the σ_tt measurements at √

s = 5.02 TeV are sensitive to the gluon PDF at high Bjorken-x values.

7 Summary

A measurement of the top quark pair production cross section at a center-of-mass energy of 5.02 TeV is presented for events with one electron and one muon of opposite charge, and at least two jets, using proton-proton collisions collected by the CMS experiment in 2017 and corresponding to an integrated luminosity of 302 pb⁻¹. The measured cross section is found to beσ_tt = 60.7±5.0 (stat)±2.8 (syst)±1.1 (lumi) pb. A combination with the single lepton + jets measurement, using a data set collected in 2015 at the same center-of-mass energy and corresponding to an integrated luminosity of 27.4 pb⁻¹, is performed. A measurement of 63.0±4.1 (stat)±3.0 (syst+lumi) pb is obtained, in agreement with the prediction from the standard model of 66.8⁺²−3^..⁹1pb.

Acknowledgments

We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at CERN and at other CMS institutes for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centers and personnel of the Worldwide LHC Computing Grid and other centers for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC, the CMS detector, and the supporting computing infrastructure provided by the following funding agencies: BMBWF and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, FAPERGS, and FAPESP (Brazil); MES and BNSF (Bulgaria); CERN; CAS, MoST, and NSFC (China); MINCIENCIAS (Colombia); MSES and CSF (Croatia); RIF (Cyprus); SENESCYT (Ecuador); MoER, ERC PUT and ERDF (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France);

BMBF, DFG, and HGF (Germany); GSRI (Greece); NKFIA (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); MES (Latvia); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT,

LNS, SEP, and UASLP-FAI (Mexico); MOS (Montenegro); MBIE (New Zealand); PAEC (Pakistan); MSHE and NSC (Poland); FCT (Portugal); JINR (Dubna); MON, RosAtom,

RAS, RFBR, and NRC KI (Russia); MESTD (Serbia); MCIN/AEI and PCTI (Spain);

MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); MST (Taipei); ThEPCenter, IPST, STAR, and NSTDA (Thailand); TUBITAK and TAEK (Turkey); NASU (Ukraine);

STFC (United Kingdom); DOE and NSF (U.S.A.).

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Individuals have received support from the Marie-Curie program and the European Research Council and Horizon 2020 Grant, contract Nos. 675440, 724704, 752730, 758316, 765710, 824093, 884104, and COST Action CA16108 (European Union); the Leventis Foundation; the Alfred P. Sloan Foundation; the Alexander von Humboldt Foundation;

the Belgian Federal Science Policy Office; the Fonds pour la Formation à la Recherche dans l’Industrie et dans l’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the F.R.S.-FNRS and FWO (Belgium) under the “Excellence of Science — EOS” — be.h project n. 30820817; the Beijing Municipal Science

& Technology Commission, No. Z191100007219010; the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Deutsche Forschungsgemeinschaft (DFG), under Germany’s Excellence Strategy — EXC 2121 “Quantum Universe” — 390833306, and under project number 400140256 — GRK2497; the Lendület (“Momentum”) Prog ram and the János Bolyai Research Scholarship of the Hungarian Academy of Sciences, the New National Excellence Program ÚNKP, the NKFIA research grants 123842, 123959, 124845, 124850, 125105, 128713, 128786, and 129058 (Hungary); the Council of Science and Industrial Research, India; the Latvian Council of Science; the Ministry of Science and Higher Education and the National Science Center, contracts Opus 2014/15/B/ST2/03998 and 2015/19/B/ST2/02861 (Poland); the Fundação para a Ciência e a Tecnologia, grant CEECIND/01334/2018 (Portugal); the National Priorities Research Program by Qatar National Research Fund; the Ministry of Science and Higher Education, projects no.

14.W03.31.0026 and no. FSWW-2020-0008, and the Russian Foundation for Basic Research, project No. 19-42-703014 (Russia); MCIN/AEI/10.13039/501100011033, ERDF “a way of making Europe”, and the Programa Estatal de Fomento de la Investigación Científica y Técnica de Excelencia María de Maeztu, grant MDM-2017-0765 and Programa Severo Ochoa del Principado de Asturias (Spain); the Stavros Niarchos Foundation (Greece); the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University and the Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand);

the Kavli Foundation; the Nvidia Corporation; the SuperMicro Corporation; the Welch Foundation, contract C-1845; and the Weston Havens Foundation (U.S.A.).

Open Access. This article is distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits any use, distribution and reproduction in any medium, provided the original author(s) and source are credited.

References

[1] CMScollaboration, Measurement of double-differential cross sections for top quark pair production in pp collisions at√

s= 8TeV and impact on parton distribution functions,Eur.

Phys. J. C 77(2017) 459[arXiv:1703.01630] [^IN^SPIRE].

[2] CMScollaboration,Measurement of the t t production cross section, the top quark mass, and the strong coupling constant using dilepton events in pp collisions at √

s= 13TeV, Eur. Phys.

J. C 79(2019) 368[arXiv:1812.10505] [^IN^SPIRE].

(14)

JHEP04(2022)144

[3] CMScollaboration, Measurement of the inclusive t t cross section in pp collisions at

√s= 5.02TeV using final states with at least one charged lepton,JHEP 03(2018) 115 [arXiv:1711.03143] [^IN^SPIRE].

[4] ATLAScollaboration,Measurement of the top quark pair production cross-section with ATLAS in the single lepton channel,Phys. Lett. B 711(2012) 244[arXiv:1201.1889]

[^IN^SPIRE].

[5] ATLAScollaboration,Measurement of the t t production cross-section using eµ events with b-tagged jets in pp collisions at √

s= 7and8TeV with the ATLAS detector,Eur. Phys. J. C 74(2014) 3109 [Addendum ibid. 76(2016) 642] [arXiv:1406.5375] [^IN^SPIRE].

[6] CMScollaboration, Measurement of the t t production cross section in the eµ channel in proton-proton collisions at√

s= 7and8TeV,JHEP 08(2016) 029[arXiv:1603.02303] [^IN^SPIRE].

[7] CMScollaboration, Measurements of the t t production cross section in lepton+jets final states in pp collisions at8TeV and ratio of8 to7TeV cross sections,Eur. Phys. J. C 77 (2017) 15[arXiv:1602.09024] [^IN^SPIRE].

[8] ATLAScollaboration,Measurement of the t t production cross-section and lepton differential distributions in eµdilepton events from pp collisions at √

s= 13TeV with the ATLAS detector,Eur. Phys. J. C 80(2020) 528[arXiv:1910.08819] [^IN^SPIRE].

[9] CMScollaboration, Measurement of the top quark pair production cross section in proton-proton collisions at√

s= 13TeV, Phys. Rev. Lett.116(2016) 052002 [arXiv:1510.05302] [^IN^SPIRE].

[10] CMScollaboration, Measurement of the t t production cross section using events in the eµ final state in pp collisions at√

s= 13TeV,Eur. Phys. J. C 77(2017) 172 [arXiv:1611.04040] [^IN^SPIRE].

[11] CMScollaboration, Measurement of differential t t production cross sections in the full kinematic range using lepton+jets events from proton-proton collisions at√

s= 13TeV, Phys.

Rev. D 104(2021) 092013 [arXiv:2108.02803] [^IN^SPIRE].

[12] LHCb collaboration,Measurement of forward top pair production in the dilepton channel in pp collisions at √

s= 13TeV,JHEP 08 (2018) 174[arXiv:1803.05188] [^IN^SPIRE].

[13] CMScollaboration, Observation of top quark production in proton-nucleus collisions,Phys.

Rev. Lett.119(2017) 242001 [arXiv:1709.07411] [^IN^SPIRE].

[14] CMScollaboration, Evidence for top quark production in nucleus-nucleus collisions,Phys. Rev.

Lett.125(2020) 222001[arXiv:2006.11110] [^IN^SPIRE].

[15] CMScollaboration,Measurement of the inclusivet¯tproduction cross section in proton-proton collisions at √

s= 5.02TeV,10.17182/hepdata.102986(2021).

[16] CMScollaboration, The CMS experiment at the CERN LHC,2008JINST 3S08004[^IN^SPIRE].

[17] GEANT4collaboration,Geant4— a simulation toolkit,Nucl. Instrum. Meth. A506(2003) 250 [^IN^SPIRE].

[18] S. Frixione, P. Nason and C. Oleari, Matching NLO QCD computations with parton shower simulations: thepowheg method,JHEP 11 (2007) 070[arXiv:0709.2092] [^IN^SPIRE].

[19] S. Alioli, P. Nason, C. Oleari and E. Re,A general framework for implementing NLO calculations in shower Monte Carlo programs: the powheg BOX, JHEP 06(2010) 043

[arXiv:1002.2581] [^IN^SPIRE].

(15)

JHEP04(2022)144

[20] S. Frixione, P. Nason and G. Ridolfi,A positive-weight next-to-leading-order Monte Carlo for heavy flavour hadroproduction,JHEP 09(2007) 126[arXiv:0707.3088] [^IN^SPIRE].

[21] T. Sjöstrand et al.,An introduction to pythia8.2,Comput. Phys. Commun.191(2015) 159 [arXiv:1410.3012] [^IN^SPIRE].

[22] CMScollaboration, Extraction and validation of a new set of CMS pythia8 tunes from underlying-event measurements,Eur. Phys. J. C 80(2020) 4[arXiv:1903.12179] [^IN^SPIRE].

[23] NNPDFcollaboration,Parton distributions from high-precision collider data,Eur. Phys. J. C 77(2017) 663[arXiv:1706.00428] [^IN^SPIRE].

[24] J. Alwall et al., The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations,JHEP 07(2014) 079

[25] R. Frederix and S. Frixione,Merging meets matching in mc@nlo,JHEP 12(2012) 061 [arXiv:1209.6215] [^IN^SPIRE].

[26] M. Czakon and A. Mitov,Top++: a program for the calculation of the top-pair cross-section at hadron colliders,Comput. Phys. Commun.185(2014) 2930 [arXiv:1112.5675] [^IN^SPIRE].

[27] M. Czakon, P. Fiedler and A. Mitov,Total top quark pair production cross section at hadron colliders throughO(α⁴_S),Phys. Rev. Lett.110(2013) 252004[arXiv:1303.6254] [^IN^SPIRE].

[28] N. Kidonakis,Theoretical results for electroweak-boson and single-top production,PoS DIS2015(2015) 170[arXiv:1506.04072] [^IN^SPIRE].

[29] K. Melnikov and F. Petriello,Electroweak gauge boson production at hadron colliders through O(α²_S),Phys. Rev. D 74(2006) 114017[hep-ph/0609070] [^IN^SPIRE].

[30] Particle Data Groupcollaboration,Review of Particle Physics,PTEP 2020(2020) 083C01[^IN^SPIRE].

[31] CMScollaboration, The CMS trigger system,2017JINST 12P01020[arXiv:1609.02366] [^IN^SPIRE].

[32] CMScollaboration, Performance of the CMS Level-1 trigger in proton-proton collisions at

√s= 13TeV,2020JINST 15 P10017[arXiv:2006.10165] [^IN^SPIRE].

[33] M. Cacciari, G.P. Salam and G. Soyez, The anti-k_T jet clustering algorithm,JHEP 04(2008) 063[arXiv:0802.1189] [^IN^SPIRE].

[34] M. Cacciari, G.P. Salam and G. Soyez,FastJetuser manual,Eur. Phys. J. C 72(2012) 1896 [arXiv:1111.6097] [^IN^SPIRE].

[35] CMScollaboration, Particle-flow reconstruction and global event description with the CMS detector,2017JINST 12 P10003[arXiv:1706.04965] [^IN^SPIRE].

[36] CMScollaboration,Jet energy scale and resolution in the CMS experiment in pp collisions at 8 TeV,2017JINST 12P02014[arXiv:1607.03663] [^IN^SPIRE].

[37] CMScollaboration,Jet algorithms performance in13TeV data,CMS-PAS-JME-16-003(2017).

[38] CMScollaboration, Electron and photon reconstruction and identification with the CMS experiment at the CERN LHC,2021JINST 16 P05014[arXiv:2012.06888] [^IN^SPIRE].

[39] CMScollaboration, Performance of the CMS muon detector and muon reconstruction with proton-proton collisions at√

s= 13TeV, 2018JINST 13P06015[arXiv:1804.04528] [^IN^SPIRE].

(16)

JHEP04(2022)144

[40] CMScollaboration, Measurement of the Higgs boson production rate in association with top quarks in final states with electrons, muons, and hadronically decaying tau leptons at

√s= 13TeV,Eur. Phys. J. C 81(2021) 378[arXiv:2011.03652] [^IN^SPIRE].

[41] CMScollaboration,Identification of heavy-flavour jets with the CMS detector in pp collisions at13TeV,2018JINST 13P05011[arXiv:1712.07158] [^IN^SPIRE].

[42] J. Butterworth et al., PDF4LHC recommendations for LHC Run II,J. Phys. G 43(2016) 023001[arXiv:1510.03865] [^IN^SPIRE].

[43] CMScollaboration, Measurement of the inelastic proton-proton cross section at√

s= 13TeV, JHEP 07(2018) 161[arXiv:1802.02613] [^IN^SPIRE].

[44] CMScollaboration,Luminosity measurement in proton-proton collisions at 5.02TeV in 2017 at CMS,CMS-PAS-LUM-19-001(2021).

[45] L. Lyons, D. Gibaut and P. Clifford,How to combine correlated estimates of a single physical quantity,Nucl. Instrum. Meth. A 270(1988) 110[^IN^SPIRE].

[46] A. Valassi and R. Chierici,Information and treatment of unknown correlations in the combination of measurements using the BLUE method,Eur. Phys. J. C 74(2014) 2717

[47] L. Lista,The bias of the unbiased estimator: a study of the iterative application of the BLUE method,Nucl. Instrum. Meth. A764(2014) 82 [Erratum ibid.773(2015) 87]

[48] S. Bailey, T. Cridge, L.A. Harland-Lang, A.D. Martin and R.S. Thorne, Parton distributions from LHC, HERA, Tevatron and fixed target data: MSHT20 PDFs,Eur. Phys. J. C 81(2021) 341 [arXiv:2012.04684] [^IN^SPIRE].

[49] S. Dulat et al., New parton distribution functions from a global analysis of quantum chromodynamics,Phys. Rev. D 93(2016) 033006[arXiv:1506.07443] [^IN^SPIRE].

[50] S. Alekhin, J. Blümlein, S. Moch and R. Placakyte, Parton distribution functions,α_s, and heavy-quark masses for LHC Run II, Phys. Rev. D96 (2017) 014011[arXiv:1701.05838] [^IN^SPIRE].

(17)

JHEP04(2022)144

The CMS collaboration

Yerevan Physics Institute, Yerevan, Armenia A. Tumasyan

Institut für Hochenergiephysik, Vienna, Austria

W. Adam , J.W. Andrejkovic, T. Bergauer , S. Chatterjee , M. Dragicevic , A. Escalante Del Valle , R. Frühwirth¹, M. Jeitler¹ , N. Krammer, L. Lechner , D. Liko, I. Mikulec, P. Paulitsch, F.M. Pitters, J. Schieck¹ , R. Schöfbeck , M. Spanring , S. Templ , W. Waltenberger , C.-E. Wulz¹

Institute for Nuclear Problems, Minsk, Belarus V. Chekhovsky, A. Litomin, V. Makarenko

Universiteit Antwerpen, Antwerpen, Belgium

M.R. Darwish², E.A. De Wolf, T. Janssen , T. Kello³, A. Lelek , H. Rejeb Sfar, P. Van Mechelen , S. Van Putte, N. Van Remortel

Vrije Universiteit Brussel, Brussel, Belgium

F. Blekman , E.S. Bols , J. D’Hondt , M. Delcourt, H. El Faham , S. Lowette , S. Moortgat , A. Morton , D. Müller , A.R. Sahasransu , S. Tavernier , W. Van Don- inck, P. Van Mulders

Université Libre de Bruxelles, Bruxelles, Belgium

D. Beghin, B. Bilin , B. Clerbaux , G. De Lentdecker, L. Favart , A. Grebenyuk, A.K. Kalsi , K. Lee, M. Mahdavikhorrami, I. Makarenko , L. Moureaux , L. Pétré, A. Popov , N. Postiau, E. Starling , L. Thomas , M. Vanden Bemden, C. Van- der Velde , P. Vanlaer , D. Vannerom , L. Wezenbeek

Ghent University, Ghent, Belgium

T. Cornelis , D. Dobur, J. Knolle , L. Lambrecht, G. Mestdach, M. Niedziela , C. Roskas, A. Samalan, K. Skovpen , M. Tytgat , W. Verbeke, B. Vermassen, M. Vit Université Catholique de Louvain, Louvain-la-Neuve, Belgium

A. Bethani , G. Bruno, F. Bury , C. Caputo , P. David , C. Delaere , I.S. Doner- tas , A. Giammanco , K. Jaffel, Sa. Jain , V. Lemaitre, K. Mondal , J. Prisciandaro, A. Taliercio, M. Teklishyn , T.T. Tran, P. Vischia , S. Wertz

Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil G.A. Alves , C. Hensel, A. Moraes

Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil

W.L. Aldá Júnior , M. Alves Gallo Pereira , M. Barroso Ferreira Filho, H. BRANDAO MALBOUISSON, W. Carvalho , J. Chinellato⁴, E.M. Da Costa , G.G. Da Silveira⁵ , D. De Jesus Damiao , S. Fonseca De Souza , D. Matos Figueiredo, C. Mora Herrera , K. Mota Amarilo, L. Mundim , H. Nogima, P. Rebello Teles , A. San- toro, S.M. Silva Do Amaral , A. Sznajder , M. Thiel, F. Torres Da Silva De Araujo , A. Vilela Pereira

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Universidade Estadual Paulista (a), Universidade Federal do ABC (b), São Paulo, Brazil

C.A. Bernardes⁵ , L. Calligaris , T.R. Fernandez Perez Tomei , E.M. Gregores , D.S. Lemos , P.G. Mercadante , S.F. Novaes , Sandra S. Padula

Institute for Nuclear Research and Nuclear Energy, Bulgarian Academy of Sci- ences, Sofia, Bulgaria

A. Aleksandrov, G. Antchev , R. Hadjiiska, P. Iaydjiev, M. Misheva, M. Rodozov, M. Shopova, G. Sultanov

University of Sofia, Sofia, Bulgaria

A. Dimitrov, T. Ivanov, L. Litov , B. Pavlov, P. Petkov, A. Petrov Beihang University, Beijing, China

T. Cheng , Q. Guo, T. Javaid⁶, M. Mittal, H. Wang, L. Yuan Department of Physics, Tsinghua University, Beijing, China

M. Ahmad , G. Bauer, C. Dozen⁷ , Z. Hu , J. Martins⁸ , Y. Wang, K. Yi⁹^,¹⁰ Institute of High Energy Physics, Beijing, China

E. Chapon , G.M. Chen⁶ , H.S. Chen⁶ , M. Chen , F. Iemmi, A. Kapoor , D. Leggat, H. Liao, Z.-A. Liu⁶ , V. Milosevic , F. Monti , R. Sharma , J. Tao , J. Thomas- Wilsker, J. Wang , H. Zhang , S. Zhang⁶, J. Zhao

State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, China

A. Agapitos, Y. An, Y. Ban, C. Chen, A. Levin , Q. Li , X. Lyu, Y. Mao, S.J. Qian, D. Wang , Q. Wang , J. Xiao

Sun Yat-Sen University, Guangzhou, China M. Lu, Z. You

Institute of Modern Physics and Key Laboratory of Nuclear Physics and Ion- beam Application (MOE) — Fudan University, Shanghai, China

X. Gao³, H. Okawa

Zhejiang University, Hangzhou, China, Zhejiang, China Z. Lin , M. Xiao

Universidad de Los Andes, Bogota, Colombia C. Avila , A. Cabrera , C. Florez , J. Fraga Universidad de Antioquia, Medellin, Colombia

J. Mejia Guisao, F. Ramirez, J.D. Ruiz Alvarez , C.A. Salazar González

University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Split, Croatia

D. Giljanovic, N. Godinovic , D. Lelas , I. Puljak