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. 2017 Dec 8;77(12):845. doi: 10.1140/epjc/s10052-017-5317-4

Search for dark matter produced in association with heavy-flavor quark pairs in proton-proton collisions at s=13TeV

A M Sirunyan 1, A Tumasyan 1, W Adam 2, E Asilar 2, T Bergauer 2, J Brandstetter 2, E Brondolin 2, M Dragicevic 2, J Erö 2, M Flechl 2, M Friedl 2, R Frühwirth 2, V M Ghete 2, C Hartl 2, N Hörmann 2, J Hrubec 2, M Jeitler 2, A König 2, I Krätschmer 2, D Liko 2, T Matsushita 2, I Mikulec 2, D Rabady 2, N Rad 2, B Rahbaran 2, H Rohringer 2, J Schieck 2, J Strauss 2, W Waltenberger 2, C-E Wulz 2, V Chekhovsky 3, V Mossolov 3, J Suarez Gonzalez 3, N Shumeiko 4, S Alderweireldt 5, E A De Wolf 5, X Janssen 5, J Lauwers 5, M Van De Klundert 5, H Van Haevermaet 5, P Van Mechelen 5, N Van Remortel 5, A Van Spilbeeck 5, S Abu Zeid 6, F Blekman 6, J D’Hondt 6, I De Bruyn 6, J De Clercq 6, K Deroover 6, S Lowette 6, S Moortgat 6, L Moreels 6, A Olbrechts 6, Q Python 6, K Skovpen 6, S Tavernier 6, W Van Doninck 6, P Van Mulders 6, I Van Parijs 6, H Brun 7, B Clerbaux 7, G De Lentdecker 7, H Delannoy 7, G Fasanella 7, L Favart 7, R Goldouzian 7, A Grebenyuk 7, G Karapostoli 7, T Lenzi 7, J Luetic 7, T Maerschalk 7, A Marinov 7, A Randle-conde 7, T Seva 7, C Vander Velde 7, P Vanlaer 7, D Vannerom 7, R Yonamine 7, F Zenoni 7, F Zhang 7, A Cimmino 8, T Cornelis 8, D Dobur 8, A Fagot 8, M Gul 8, I Khvastunov 8, D Poyraz 8, S Salva 8, R Schöfbeck 8, M Tytgat 8, W Van Driessche 8, W Verbeke 8, N Zaganidis 8, H Bakhshiansohi 9, O Bondu 9, S Brochet 9, G Bruno 9, A Caudron 9, S De Visscher 9, C Delaere 9, M Delcourt 9, B Francois 9, A Giammanco 9, A Jafari 9, M Komm 9, G Krintiras 9, V Lemaitre 9, A Magitteri 9, A Mertens 9, M Musich 9, K Piotrzkowski 9, L Quertenmont 9, M Vidal Marono 9, S Wertz 9, N Beliy 10, W L Aldá Júnior 11, F L Alves 11, G A Alves 11, L Brito 11, C Hensel 11, A Moraes 11, M E Pol 11, P Rebello Teles 11, E Belchior Batista Das Chagas 12, W Carvalho 12, J Chinellato 12, A Custódio 12, E M Da Costa 12, G G Da Silveira 12, D De Jesus Damiao 12, S Fonseca De Souza 12, L M Huertas Guativa 12, H Malbouisson 12, C Mora Herrera 12, L Mundim 12, H Nogima 12, A Santoro 12, A Sznajder 12, E J Tonelli Manganote 12, F Torres Da Silva De Araujo 12, A Vilela Pereira 12, S Ahuja 13, C A Bernardes 13, T R Fernandez Perez Tomei 13, E M Gregores 13, P G Mercadante 13, C S Moon 13, S F Novaes 13, Sandra S Padula 13, D Romero Abad 13, J C Ruiz Vargas 13, A Aleksandrov 14, R Hadjiiska 14, P Iaydjiev 14, M Rodozov 14, S Stoykova 14, G Sultanov 14, M Vutova 14, A Dimitrov 15, I Glushkov 15, L Litov 15, B Pavlov 15, P Petkov 15, W Fang 16, X Gao 16, M Ahmad 17, J G Bian 17, G M Chen 17, H S Chen 17, M Chen 17, Y Chen 17, C H Jiang 17, D Leggat 17, Z Liu 17, F Romeo 17, S M Shaheen 17, A Spiezia 17, J Tao 17, C Wang 17, Z Wang 17, E Yazgan 17, H Zhang 17, J Zhao 17, Y Ban 18, G Chen 18, Q Li 18, S Liu 18, Y Mao 18, S J Qian 18, D Wang 18, Z Xu 18, C Avila 19, A Cabrera 19, L F Chaparro Sierra 19, C Florez 19, J P Gomez 19, C F González Hernández 19, J D Ruiz Alvarez 19, N Godinovic 20, D Lelas 20, I Puljak 20, P M Ribeiro Cipriano 20, T Sculac 20, Z Antunovic 21, M Kovac 21, V Brigljevic 22, D Ferencek 22, K Kadija 22, B Mesic 22, T Susa 22, M W Ather 23, A Attikis 23, G Mavromanolakis 23, J Mousa 23, C Nicolaou 23, F Ptochos 23, P A Razis 23, H Rykaczewski 23, M Finger 24, M Finger Jr 24, E Carrera Jarrin 25, Y Assran 26, M A Mahmoud 26, A Mahrous 26, R K Dewanjee 27, M Kadastik 27, L Perrini 27, M Raidal 27, A Tiko 27, C Veelken 27, P Eerola 28, J Pekkanen 28, M Voutilainen 28, J Härkönen 29, T Järvinen 29, V Karimäki 29, R Kinnunen 29, T Lampén 29, K Lassila-Perini 29, S Lehti 29, T Lindén 29, P Luukka 29, E Tuominen 29, J Tuominiemi 29, E Tuovinen 29, J Talvitie 30, T Tuuva 30, M Besancon 31, F Couderc 31, M Dejardin 31, D Denegri 31, J L Faure 31, F Ferri 31, S Ganjour 31, S Ghosh 31, A Givernaud 31, P Gras 31, G Hamel de Monchenault 31, P Jarry 31, I Kucher 31, E Locci 31, M Machet 31, J Malcles 31, J Rander 31, A Rosowsky 31, M Ö Sahin 31, M Titov 31, A Abdulsalam 32, I Antropov 32, S Baffioni 32, F Beaudette 32, P Busson 32, L Cadamuro 32, E 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PMCID: PMC6954044  PMID: 31985736

Abstract

A search is presented for an excess of events with heavy-flavor quark pairs (tt¯ and bb¯) and a large imbalance in transverse momentum in data from proton–proton collisions at a center-of-mass energy of 13TeV. The data correspond to an integrated luminosity of 2.2fb-1 collected with the CMS detector at the CERN LHC. No deviations are observed with respect to standard model predictions. The results are used in the first interpretation of dark matter production in tt¯ and bb¯ final states in a simplified model. This analysis is also the first to perform a statistical combination of searches for dark matter produced with different heavy-flavor final states. The combination provides exclusions that are stronger than those achieved with individual heavy-flavor final states.

Introduction

Astrophysical and cosmological observations [13] provide strong support for the existence of dark matter (DM), which could originate from physics beyond the standard model (BSM). In a large class of BSM models, DM consists of stable, weakly-interacting massive particles (WIMPs). In collider experiments, WIMPs (χ) could be pair-produced through the exchange of new mediating fields that couple to DM and to standard model (SM) particles. Following their production, the WIMPs would escape detection, thereby creating an imbalance of transverse momentum (missing transverse momentum, pTmiss) in the event.

If the new physics associated with DM respects the principle of minimal flavor violation [4, 5], the interactions of spin-0 mediators retain the Yukawa structure of the SM. This principle is motivated by the apparent lack of new flavor physics at the electroweak (EWK) scale. Because only the top quark has a Yukawa coupling of order unity, WIMP DM couples preferentially to the heavy top quark in models with minimal flavor violation. In high energy proton-proton collisions, this coupling leads to the production of tt¯+χχ¯ at lowest-order via a scalar (ϕ) or pseudoscalar (a) mediator (Fig. 1), and to the production of so-called mono-X final states through a top quark loop [614]. At the CERN Large Hadron Collider (LHC), the tt¯+χχ¯ process can be probed directly via the tt¯+pTmiss and bb¯+pTmiss signatures. The bb¯+pTmiss signature provides additional sensitivity to the bb¯+χχ¯ process for models in which mediator couplings to up-type quarks are suppressed, as can be the case in Type-II two Higgs doublet models [15].

Fig. 1.

Fig. 1

A leading order Feynman diagram describing the production of a pair of DM particles (χ) with heavy-flavor (top or bottom) quark pairs via scalar (ϕ) or pseudoscalar (a) mediators

This paper describes a search for DM produced with a tt¯ or bb¯ pair in pp collisions at s=13TeV with the CMS experiment at the LHC. A potential DM signal is extracted from simultaneous fits to the pTmiss distributions in the bb¯+pTmiss and tt¯+pTmiss search channels. Data from control regions enriched in SM tt¯, W+jets, and Z+jets processes are included in the fits, to constrain the major backgrounds. The top quark nearly always decays to a W boson and a b quark. The W boson subsequently decays leptonically (to charged leptons and neutrinos) or hadronically (to quark pairs). The dileptonic, lepton()+jets, and all-hadronic tt¯ final states consist, respectively, of events in which both, either, or neither of the W bosons decay leptonically. Each of these primary tt¯ final states are explored.

Previous LHC searches for DM produced with heavy-flavor quark pairs were interpreted using effective field theories that parameterize the DM-SM coupling in terms of an interaction scale M [1618]. An earlier search by the CMS Collaboration investigated the +jets tt¯ final state using 19.7fb-1 of data collected at s=8TeV [19]. That search excluded values of M below 118GeV, assuming mχ=100GeV. The ATLAS Collaboration performed a similar search separately for the all-hadronic and +jets tt¯ final states and obtained comparable limits on M [20]. More recently, the limitations of effective field theory interpretations of DM production at the LHC has led to the development of simplified models that remain valid when the mediating particle is produced on-shell [21]. This analysis adopts the simplified model framework to provide the first interpretation of heavy-flavor search results in terms of the decays of spin-0 mediators with scalar or pseudoscalar couplings. This paper also reports the first statistical combination of dileptonic (ee, eμ, μμ), +jets (e, μ), and all-hadronic tt¯+χχ¯ searches, as well as the first combination of tt¯+χχ¯ and bb¯+χχ¯ search results.

The paper is organized as follows. Section 2 reviews the properties of the CMS detector and the particle reconstruction algorithms used in the analysis. Section 3 describes the modeling of tt¯+χχ¯ and bb¯+χχ¯ signal and SM background events, and Sect. 4 provides the selections applied to data and simulation. Section 5 discusses the techniques used to extract a potential DM signal in the tt¯+pTmiss and bb¯+pTmiss search channels. Section 6 describes the systematic uncertainties considered in the analysis. The results of the search and their interpretation within a simplified DM framework are presented in Sect. 7. Section 8 concludes with a summary of the results.

CMS detector and event reconstruction

The CMS detector [22] is a multipurpose apparatus optimized for the study high transverse momentum (pT) physics processes in pp and heavy ion collisions. A superconducting solenoid surrounds the central region, providing a magnetic field of 3.8\,T parallel to the beam direction. Charged particle trajectories are measured using the silicon pixel and strip trackers, which cover the pseudorapidity region of |η|<2.5. A lead tungstate crystal electromagnetic calorimeter (ECAL) and a brass and scintillator hadron calorimeter (HCAL) surround the tracking volume, and cover the region with |η|<3. Each calorimeter is composed of a barrel and two endcap sections. A steel and quartz-fiber Cherenkov forward hadron calorimeter extends the coverage to |η|<5. The muon system consists of gas-ionization detectors embedded in the steel flux return yoke outside the solenoid, and covers the region of |η|<2.4. The first level of the CMS trigger system is composed of special hardware processors that select the most interesting events in less than 4μs using information from the calorimeters and muon detectors. This system reduces the event rate from 40\,MHz to approximately 100\,kHz. The high-level trigger processor farm performs a coarse reconstruction of events selected by the first-level trigger, and applies additional selections to reduce the event rate to less than 1\,kHz for storage.

Event reconstruction is based on the CMS Particle Flow (PF) algorithm [23, 24], which combines information from all CMS subdetectors to identify and reconstruct the individual particles emerging from a collision: electrons, muons, photons, and charged and neutral hadrons. Interaction vertices are reconstructed using the deterministic annealing algorithm [25]. The primary vertex is selected as that with the largest sum of pT2 of its associated charged particles. Events are required to have a primary vertex that is consistent with being in the luminous region.

Jets are reconstructed by clustering PF candidates using the anti-kT algorithm [26, 27] with a distance parameter of 0.4. Corrections based on jet area are applied to remove the energy from additional collisions in the same or neighboring bunch crossing (pileup) [28]. Energy scale calibrations determined from the comparison of simulation and data are then applied to correct the four momenta of the jets [29]. Jets are required to have pT>30GeV, |η|<2.4, and to satisfy a loose set of identification criteria designed to reject events arising from spurious detector and reconstruction effects.

The combined secondary vertex b tagging algorithm (CSVv2) is used to identify jets originating from the hadronization of bottom quarks [30, 31]. Jets are considered to be b-tagged if the CSVv2 discriminant for that jet passes a requirement that roughly corresponds to efficiencies of 70% to tag bottom quark jets, 20% to mistag charm quark jets, and 1% to misidentify light-flavor jets as b jets. Efficiency scale factors in the range of 0.92–0.98, varying with jet pT, are applied to simulated events in order to reproduce the b tagging performance for bottom and charm quark jets observed in data. A scale factor of 1.14 is applied to simulation to reproduce the measured mistag rate for light-flavor quark and gluon jets.

The pTmiss variable is initially calculated as the magnitude of the vector sum of the pT of all PF particles. This quantity is adjusted by applying jet energy scale corrections. Detector noise, inactive calorimeter cells, and cosmic rays can give rise to events with severely miscalculated pTmiss. Such events are removed via a set of quality filters that take into account the timing and distribution of signals from the calorimeters, missed tracker hits, and global characteristics of the event topology.

Electron candidates are reconstructed by combining tracking information with energy depositions in the ECAL [32]. The energy of the ECAL clusters is required to be compatible with the momentum of the associated electron track. Muon candidates are reconstructed by combining tracks from the inner silicon tracker and the outer muon system [33]. Tracks associated with muon candidates must be consistent with a muon originating from the primary vertex, and must satisfy a set of quality criteria [33]. Electrons and muons are selected with pT>30GeV and |η|<2.1 for consistency with the coverage of the single-lepton triggers, and are required to be isolated from hadronic activity, to reject hadrons misidentified as leptons. Relative isolation is defined as the scalar pT sum of PF candidates within a ΔR=η2+ϕ2 cone of radius 0.4 or 0.3 centered on electrons or muons, respectively, divided by the lepton pT. Relative isolation is nominally required to be less than 0.035 (0.065) for electrons in the barrel (endcap), respectively, and less than 0.15 for muons. Identification requirements, based on hit information in the tracker and muon systems, and on energy depositions in the calorimeters, are imposed to ensure that candidate leptons are well-measured. These restrictive isolation and identification criteria are used to select events from the dileptonic tt¯, +jets tt¯, W(ν)+jets, and Z()+jets processes.

The efficiencies of the requirements for electrons (muons) with pT>30GeV range from 52 to 83% (91 to 96%), for increasing lepton pT. Less restrictive lepton isolation and identification requirements are used to reject events containing additional leptons with pT>10GeV. Efficiencies for these requirements range from 66 to 96% for electrons and 73 to 99% for muons, for increasing lepton pT. Electron and muon selection efficiency scale factors are applied in simulation to match the efficiencies measured in data using the tag-and-probe procedure [34]. Averaged over lepton pT, the electron and muon efficiency scale factors for the more restrictive selection requirements are 98 and 99%, respectively.

The “resolved top tagger” (RTT) is a multivariate discriminant that uses jet properties and kinematics to identify top quarks that decay into three resolved jets. The input observables are the values of the quark/gluon discriminant [35], which combines track multiplicity, jet shape, and fragmentation information for each jet, values of the b tagging discriminants, and the opening angles between the candidate b jet and the two jets from the candidate W boson. Within each jet triplet, the b candidate is considered to be the jet with the largest value of the b tagging discriminant. The RTT discriminant also utilizes the χ2 value of a simultaneous kinematic fit to the top quark and W boson masses [36]. The fit attempts to satisfy the mass constraints by allowing the jet momenta and energies to vary within their measured resolutions. The RTT is implemented as a boosted decision tree using the TMVA framework [37], and is trained on simulated +jets tt¯ events using correct (incorrect) jet combinations as signal (background).

The performance of the RTT discriminant is characterized with data enriched in SM +jets tt¯ events containing four or more jets. At least one of these jets is required to be b-tagged. The output discriminant for these events is plotted in Fig. 2. Each entry in the plot corresponds to the jet triplet with the highest RTT score in the event. Data are modeled using simulated +jets tt¯ signal events, and simulated events for each of the primary backgrounds (dileptonic tt¯, W+jets, single t). The simulation is split into three classes that correspond to correctly tagged jet triplets and the two possibilities for mistagging, as explained below. Simulation describes the data well. A jet triplet is considered as a tagged top quark decay when the RTT discriminant value is greater than zero.

Fig. 2.

Fig. 2

The distribution of the RTT discriminant in data enriched in +jets tt¯ events. Simulated +jets tt¯ events in which jets from the all-hadronic top quark decay are correctly chosen are labeled “tt¯(1) with matched jets”. Simulated +jets tt¯ events in which an incorrect combination of jets is chosen are labeled “tt¯(1) combinatorial”. Events from processes that do not contain a hadronically-decaying top quark, such as dileptonic tt¯, are labeled “other background”. The uncertainties shown in the ratios of data to simulation are statistical only. Jet triplets in the all-hadronic tt¯+pTmiss search are considered to be top quark tagged if their RTT discriminant value is larger than zero

There are three efficiencies associated with the RTT selection, which correspond to the three classes of events in Fig. 2: +jets tt¯ events in which the hadronically-decaying top quark is correctly identified (“tt¯(1) matched”), +jets tt¯ events in which an incorrect combination of jets is tagged (“tt¯(1) combinatorial”), and events with no hadronically-decaying top quarks that contain a mistagged jet triplet (“other background”). Dileptonic tt¯ events are used to extract the nonhadronic mistag rate in data. Then, +jets tt¯ events are used to extract the tagging and mistagging efficiencies for hadronically-decaying top quarks through a fit to the trijet mass distribution. Mass templates obtained from simulation are associated with each efficiency term in the fit. The efficiency of the RTT >0 selection for events determined to be tt¯(1) matched, tt¯(1) combinatorial, or other background are 0.97±0.03, 0.80±0.05, and 0.69±0.02, respectively. Corresponding data-to-simulation scale factors are found to be consistent with unity.

The bb¯+pTmiss search includes vetoes on hadronically-decaying τ leptons, which are reconstructed from PF candidates using the “hadron plus strips” algorithm [38]. The algorithm combines one or three charged pions with up to two neutral pions. Neutral pions are reconstructed by the PF algorithm from the photons that arise from π0γγ decay. Photons are reconstructed from ECAL energy clusters, which are corrected to recover the energy deposited by photon conversions and bremsstrahlung. Photons are identified and distinguished from jets and electrons using cut-based criteria that include the isolation and transverse shape of the ECAL deposit, and the ratio of HCAL/ECAL energies in a region surrounding the candidate photon.

Modeling and simulation

The associated production of DM and heavy-flavor quark pairs provides rich detector signatures that include significant pTmiss accompanied by high-pT jets, bottom quarks, and leptons. The largest backgrounds in the tt¯+pTmiss and bb¯+pTmiss searches are SM tt¯ events, inclusive W boson production in which the W decays leptonically (W(ν)+jets), and inclusive Z boson production in which the Z decays to neutrinos (Z(νν¯)+jets). Simulated events are used throughout the analysis to determine signal and background expectations. Where possible, corrections determined from data are applied to the simulations.

Monte Carlo (MC) samples of SM tt¯ and single t backgrounds are generated at next-to-leading order (NLO) in quantum chromodynamics (QCD) using Powhegv2 and Powhegv1 [3941], respectively. As with all MC generators subsequently described, Powheg is interfaced with Pythia8.205 [42] for parton showering using the CUETP8M1 tune [43]. Samples of Z+jets, W+jets, and QCD multijet events are produced at leading order (LO) using MG5_amc@nlo v2.2.2 [44] with the MLM prescription [45] for matching jets from the matrix element calculation to the parton shower description. The W+jets and Z+jets samples are corrected using EWK and QCD NLO/LO K-factors calculated with MG5_amc@nlo as functions of the generated boson pT. The simulation of tt¯+γ, tt¯+W, and tt¯+Z events makes use of NLO matrix element calculations implemented in MG5_amc@nlo , and the FxFx [46] prescription to merge multileg processes. Diboson processes (WW, WZ, and ZZ) are generated at NLO using either MG5_amc@nlo or Powhegv2.

The signal processes are simulated using simplified models that were developed in the LHC Dark Matter Forum (DMF) [21]. The DM particles χ are assumed to be Dirac fermions, and the mediators are spin-0 particles with scalar (ϕ) or pseudoscalar (a) couplings. The coupling strength of the mediator to SM fermions is assumed to be gqq=gqyq where: yq=2mq/v is the SM Yukawa coupling, mq is the quark mass, and v=246GeV is the Higgs field vacuum expectation value. As per the recommendations of the LHC Dark Matter Working Group [47], gq is taken to be flavor universal and equal to 1. Likewise, the coupling strength of the mediator to DM, gχ, is set to 1 and is independent of the DM mass. The LHC DMF spin-0 models do not account for mixing between the ϕ scalar and the SM Higgs boson [48]. As is discussed in [21], the pTmiss spectra of both the scalar and pseudoscalar mediated processes broaden with increasing mediator mass. For mϕ/a larger than twice the top quark mass (mtop), the pTmiss distributions of the scalar and pseudoscalar processes are essentially identical. As mϕ/a decreases below 2mtop, the pTmiss spectra of the two processes increasingly differ, with the distribution of the scalar process peaking at lower pTmiss values [49, 50]. For all mediator masses, the total cross section of the scalar process is larger than that of the pseudoscalar equivalent [50]. This analysis focuses on the mχ=1GeV LHC DMF benchmark point, which provides a convenient signal reference for both low and high mass mediators.

The tt¯+χχ¯ and bb¯+χχ¯ signals are generated at LO in QCD using MG5_amc@nlo with up to one additional jet in the final state. Jets from the matrix element calculations are matched to the parton shower descriptions using the MLM prescription. Angular correlations in the decays of the top quarks are included using MadSpinv 2.2.2 [51]. Minimum decay widths are assumed for the mediators, and are calculated from the partial width formulas given in Ref. [52]. This calculation assumes that the spin-0 mediators couple only to SM quarks and the DM fermion χ. Simulated signal samples are produced for a DM mass of mχ=1GeV and for mediator masses in the range of 10–500GeV. The relative width of the scalar (pseudoscalar) mediator varies between 4 and 6% (4–8%) for this mediator mass range. The predicted rates of the bb¯+χχ¯ process, which is generated in the 4-flavor scheme, are adjusted to match the cross sections calculated in the 5-flavor scheme [21, 53].

All samples generated at LO and NLO use corresponding NNPDF3.0 [54] parton distribution function (PDF) sets. All signal and background samples are processed using a detailed simulation of the CMS detector based on Geant4 [55]. The samples are reweighted to account for the distribution of pileup observed in data.

Event selection

Signal events are expected to exhibit both large pTmiss from the production of two noninteracting DM particles and event topologies consistent with the presence of top quarks or b quark jets. Data are therefore collected using triggers that select events containing large pTmiss or high-pT leptons. Data for the dileptonic and +jets tt¯+pTmiss searches are obtained using single-lepton triggers that require an electron (muon) with pT27(20)GeV. These trigger selections are more than 90% efficient for PF-reconstructed electrons and muons that satisfy the pT, identification, and isolation requirements imposed. The trigger used for the bb¯+pTmiss and all-hadronic tt¯+pTmiss searches selects events based on the amount of pTmiss and HTmiss reconstructed using a coarse version of the PF algorithm. The HTmiss variable is defined as the magnitude of the vector sum of the pT of all jets in the event with pT>20GeV, |η|<5.0. Jets reconstructed from detector noise are removed in the HTmiss calculation by additionally requiring neutral hadron energy fractions of less than 0.9. The pTmiss and HTmiss requirements for this trigger are 120GeV. The trigger is nearly 100% efficient for events that satisfy subsequent selections based on fully-reconstructed PF pTmiss.

Additional selections, described in Sect. 4.1 and summarized in Table 1, are applied to define eight independent regions of data that are sensitive to DM signals: two bb¯+pTmiss, one +jets tt¯+pTmiss, three dileptonic tt¯+pTmiss, and two all-hadronic tt¯+pTmiss regions. Control regions (CRs) enriched in various background processes are also defined and are used to improve background estimates in the aforementioned signal regions (SRs). In the CRs, individual signal selection requirements are inverted to enhance background yields and to prevent event overlaps with the SRs. Collectively, the SRs and CRs associated with the individual tt¯+χχ¯ and bb¯+χχ¯ production and decay modes are referred to as “channels”. The bb¯+χχ¯ channel and the three tt¯+χχ¯ channels are used in simultaneous pTmiss fits (described in Sect. 5) to extract a potential DM signal. The fits allow the background-enriched CRs to constrain the contributions of SM tt¯, W+jets, and Z+jets processes within the CRs and SRs of each channel. The selections used to define the SRs and CRs are described in Sects. 4.1 and 4.2, respectively. Tables 1 and 2 briefly summarize these selections. Table 2 defines a CR labeling scheme that is extensively used in subsequent sections.

Table 1.

Overview of the selection criteria used to define the eight tt¯+pTmiss and bb¯+pTmiss signal regions. The signal region selections (including the definitions of the variables MT and MT2W) are described in detail in Sect. 4.1. Vetoes are applied in the dileptonic tt¯+pTmiss signal region to remove overlaps with the +jets tt¯+pTmiss and bb¯+pTmiss control regions. These control regions are summarized in Table 2 and discussed in Sect. 4.2

Signal regions Leptons Jets b jets pTmiss Other selections
Dileptonic tt¯+pTmiss ee 2 1 50GeV minΔϕ(pT,pTmiss)>1.2\,rad
m>20GeV
eμ |mee,μμ-mZ|>15GeV
Dileptonic tt¯ control region veto
μμ Z+jets control region veto
+jets tt¯+pTmiss e or μ 3 1 160GeV MT>160GeV
MT2W>200GeV
minΔϕ(pTjeti,pTmiss)>1.2\,rad
All-hadronic tt¯+pTmiss 0 4 2 200GeV 0,1RTT
minΔϕ(pTjeti,pTmiss)>1.0\,rad
6 1 2 RTT
minΔϕ(pTjeti,pTmiss)>0.4\,rad
bb¯+pTmiss 0 1 or 2 1 200GeV minΔϕ(pTjeti,pTmiss)>0.5\,rad
2 or 3 2

Table 2.

Overview of the selection criteria used to define the background control regions associated with the tt¯+pTmiss and bb¯+pTmiss signal regions. The control region selections are described in detail in Sect. 4.2

Label Associated signal region(s) Dominant background Leptons Jets b jets pTmiss Additional or modified selections
slA +jets tt¯+pTmiss Dileptonic tt¯+pTmiss ee,eμ,μμ 3 1 160GeV No selection on MT,MT2W,minΔϕ(pTjeti,pTmiss)
bbC/bbD/bbE/bbH/bbI/bbJ control region veto
slB W+jets e or μ 0 No selection on MT2W,minΔϕ(pTjeti,pTmiss)
hadA Hadronic tt¯+pTmiss,   0,1 RTT +jets tt¯+pTmiss e or μ 4 2 200GeV MT<160GeV, 0,1 RTT
hadB W/Z+jets 0 0 0,1 RTT
hadC W+jets e or μ 0 No selection on MT<160GeV, minΔϕ(pTjeti,pTmiss), 0,1 RTT
hadD Z+jets ee or μμ 0 60<m<120GeV
Hadronic tt¯+pTmiss,   2 RTT No selection on minΔϕ(pTjeti,pTmiss)
hadE +jets tt¯+pTmiss e or μ 6 1 MT<160GeV, 2RTT
hadF W/Z+jets 0 0 2RTT
hadG W+jets e or μ 0 No selection on MT<160GeV, minΔϕ(pTjeti,pTmiss) , 2RTT
bbA bb¯+pTmiss,   1 b tag W+jets e 1 or 2 1 200GeV 50<MT<160GeV
bbB +jets tt¯ μ No selection on minΔϕ(pTjeti,pTmiss)
bbC Z+jets ee 70<m<110GeV
bbD μμ No selection on minΔϕ(pTjeti,pTmiss)
bbE Dileptonic tt¯ eμ No selection on minΔϕ(pTjeti,pTmiss)
bbF bb¯+pTmiss,   2 b tag W+jets e 2 or 3 2 50<MT<160GeV
bbG +jets tt¯ μ No selection on minΔϕ(pTjeti,pTmiss)
bbH Z+jets ee 70<m<110GeV
bbI μμ No selection on minΔϕ(pTjeti,pTmiss)
bbJ Dileptonic tt¯ eμ No selection on minΔϕ(pTjeti,pTmiss)

Signal region selections

Dileptonic tt¯+pTmiss Events in the dileptonic tt¯ SR are required to contain exactly two leptons that satisfy stringent identification and isolation requirements. One of the leptons must have pT>30GeV, while the second must have pT>10GeV. Events containing additional, loosely identified leptons with pT>10GeV are rejected. Events are also required to have pTmiss>50GeV, and to contain two or more jets, at least one of which must satisfy b tagging requirements. Overlaps between the dileptonic SR and the dileptonic and Z+jets CRs of the +jets tt¯+pTmiss and bb¯+pTmiss channels (discussed in Sect. 4.2) are removed by vetoing events that satisfy the selections for those CRs. These vetoes remove 2.5% of the events from the dileptonic tt¯+pTmiss SR. The azimuthal opening angle between the pT vector of the dilepton system and the pTmiss vector, Δϕ(pT,pTmiss), is required to be larger than 1.2 radians. This requirement preferentially selects events consistent with a tt¯ system recoiling against the invisibly decaying DM mediator. The dilepton mass, m, is required to be larger than 20GeV. In dielectron and dimuon events, m is also required to be at least 15GeV away from the Z boson mass [56]. These requirements reduce backgrounds from low-mass dilepton resonances and from leptonic Z boson decays.

Events that satisfy these criteria are divided among three SR categories that correspond to the flavor assignments of the two selected leptons: ee, eμ, and μμ. Signal efficiencies for the dileptonic tt¯+pTmiss SR event selections range from 6×10-3 to 10-2 for mediator masses between 10GeV and 500GeV. The denominator used in the efficiency calculation is the total number of signal events, irrespective of the tt¯ final state. The low efficiencies result primarily from the small dileptonic branching fraction.

+jetstt¯+pTmiss Events in the +jets tt¯ SR are selected by requiring pTmiss>160GeV, exactly one lepton, and three or more jets, of which at least one must satisfy the b tagging criteria. The lepton is required to have pT>30GeV, and to pass tight identification criteria. Events must not contain additional leptons with pT>10GeV that satisfy a looser set of identification requirements. To reduce SM +jets tt¯ and W+jets backgrounds, the transverse mass, calculated from pTmiss and the lepton momentum (pT) as:

MT=2pTpTmiss(1-cosΔϕ(pT,pTmiss)), 1

is required to be larger than 160GeV.

Following these selections, the remaining background events primarily consist of dileptonic tt¯ final states in which one of the leptons is not identified. Because of the requirement of pTmiss>160GeV, this background tends to contain events with Lorentz-boosted top quark decays in which the b jet is closely aligned with the direction of the neutrino. This background is suppressed by requiring that the smallest azimuthal angle formed from the missing transverse momentum vector and each of the two highest pT jets in the event, minΔϕ(pTjeti,pTmiss) where i=1,2, be larger than 1.2 radians. In addition, the MT2W variable [57] is required to be larger than 200GeV. This variable is defined as:

MT2W=minmyconsistent with:p1T+p2T=pTmiss,p12=0,(p1+pl)2=p22=MW2,(p1+pl+pb1)2=(p2+pb2)2=my2 2

where my is the mass of two parent particles that each decay to bW(ν). One of the W decays is assumed to produce a lepton that is not reconstructed. For the W decay that does produce a reconstructed lepton, the neutrino and lepton 4-momenta are denoted p1 and p, respectively. The 4-momentum of the W that produces the unreconstructed lepton is denoted p2, while the momenta of the two b candidates are referred to as pb1 and pb2. Assuming perfect measurements, the MT2W has a kinematic end-point at mtop   for tt¯ events, whereas signal events lack this feature because both the neutrino and DM particles contribute to pTmiss.

The efficiency of the +jets tt¯+pTmiss SR event selections for the tt¯+χχ¯ process range from 10-4 for mediator masses of the order of 10GeV, to 10-3 for masses of about 500GeV. Signal efficiencies are low because of the stringent pTmiss requirement applied. The efficiency improves with increasing mediator mass because of the broadening of the pTmiss spectrum.

All-hadronic tt¯+pTmiss Any event with a loosely identified lepton with pT>10GeV is vetoed from the all-hadronic tt¯+pTmiss SRs. The pTmiss value must be larger than 200GeV, and four or more jets are required, at least one of which must satisfy b tagging criteria. Spurious pTmiss can arise in multijet events due to jet energy mismeasurement. In such cases, the reconstructed pTmiss tends to align with one of the jets. Multijet background is suppressed by requiring that minΔϕ(pTjeti,pTmiss)>0.4 or 1 radian (depending on the number of RTT tags, as described below) for all jets in the event. The minΔϕ(pTjeti,pTmiss) selections also help to reduce +jets tt¯ background, for which the pTmiss vector is typically aligned with a b jet.

Following these selection requirements, the dominant residual background is +jets SM tt¯ production. By contrast, selected signal typically includes events in which both top quarks decay hadronically. The resolved top quark tagger (RTT, introduced in Sect. 2) is employed to suppress the +jets background by identifying potential hadronic top quark decays. The RTT is applied to the all-hadronic search region to define a category of events with two hadronic top quark decays. In this double-tag (2 RTT) category, one or more b-tagged jets are required and minΔϕ(pTjeti,pTmiss)>0.4 radians is imposed for all jets in the event. The 2 RTT category implicitly requires at least six jets in the event. A second category is defined for events with 0 or 1 top quark tags (0, 1 RTT), four or more jets with at least two b-tagged jets, and a tighter requirement of minΔϕ(pTjeti,pTmiss)>1 radian.

The selection efficiency for tt¯+χχ¯ events in the all-hadronic tt¯+pTmiss SRs ranges from 10-3 for mediator masses of the order of 10GeV to 10-1 for masses near 500GeV. These values are larger than the corresponding efficiencies of the dileptonic and +jets SR selections because of the larger branching fraction to the all-hadronic final state.

bb¯+pTmiss Events with pTmiss>200GeV are selected for the SRs of this final state. Events containing identified and isolated electrons or muons with pT larger than 10GeV or identified τ leptons with pT>18GeV are rejected. Multijet background is reduced by requiring minΔϕ(pTjeti,pTmiss)>0.5 radians for all jets in the event.

Following these selections, two exclusive event categories are defined using the number of jets and b-tagged jets in the event. The single b-tagged jet category provides high efficiency for bb¯+χχ¯ signal and requires at most two jets. At least one of these jets must have pT>50GeV, and exactly one must satisfy b tagging requirements. The second category allows exactly two b-tagged jets. This SR selects bb¯+χχ¯ signal and partially recovers tt¯+χχ¯ events that are not selected in the all-hadronic tt¯+pTmiss categories. At most three jets are allowed in the 2 b tag SR, and at least two of these jets must have pT>50GeV.

The efficiency of the bb¯+pTmiss SR event selections for the bb¯+χχ¯ process range from 10-6 for mediator masses of the order of 10GeV, to 10-2 for masses of 500GeV. The selection efficiency for the tt¯+χχ¯ process is found to be less dependent on the mediator mass, and varies from 10-4 to 10-3 for the same mass range.

Background control region selections

Figure 3 shows the simulated background yields in each of the SRs following the selections of Sect. 4.1. Clearly, the dominant backgrounds in the SRs are from the SM tt¯, W+jets, and Z+jets processes. The estimation of backgrounds in the SRs is improved through the use of corresponding data CRs enriched in these processes. Independent CRs are defined for each of the +jets tt¯+pTmiss, all-hadronic tt¯+pTmiss and bb¯+pTmiss SRs. In some cases, multiple CRs are used to constrain a given background process in a SR. In this section we describe the main tt¯, W+jets, and Z+jets backgrounds and the selections used to define the CRs. The CR selections are designed to ensure that these regions are both mutually exclusive and exclusive of the SRs as well. The contributions of multijet, diboson, single t, and tt¯+Z/W/γ processes in the SRs are either subdominant or insignificant after the SR selections. The residual backgrounds from these processes are modeled with simulation. Dilepton background events from Drell–Yan and processes in which jets are misidentified as leptons are estimated using the sideband techniques described in Ref. [58].

Fig. 3.

Fig. 3

Simulation-derived background expectations in the tt¯+pTmiss and bb¯+pTmiss signal regions

The remainder of this section describes how the contributions of SM backgrounds in the SRs are estimated using the CRs. The discussion utilizes the CR labeling convention defined in Table 2, for ease of reference. The CRs for the +jets tt¯+pTmiss SR are denoted slA and slB, those for the all-hadronic tt¯+pTmiss SRs are hadA–hadG, and those for the bb¯+pTmiss SRs are bbA–bbJ.

Section 5 describes how the CRs are simultaneously fit with the SRs to constrain the predicted normalization of the tt¯, W+jets, and Z+jets background processes. Figures 6, 7 and 8 compare the integrated yields in each CR before and after background-only fits to the CR pTmiss distributions. Reasonable agreement is found between the observed and predicted CR yields. In general, the expected and observed pTmiss distributions in the CRs also agree. Regions for which the distributions of data and of the initial (“prefit”) MC disagree are noted in the text.

Fig. 6.

Fig. 6

Observed data, and prefit and fitted background-only event yields in the control regions associated with the +jets tt¯+pTmiss signal region. The 2 lepton, 0 b tag region (slA in Table 2) is used to constrain the dileptonic tt¯ background in the +jets tt¯+pTmiss signal region, while the 1 lepton, 0 b tag control region (slB) constrains W+jets background. The lower panel shows the ratios of observed to fitted background yields. In both panels, the statistical uncertainties of the data are indicated as vertical error bars and the fit uncertainties as hatched bands. Prefit yields and the ratios of prefit to fitted background expectations are shown as dashed magenta histograms

Fig. 7.

Fig. 7

Observed data, and prefit and fitted background-only event yields in the control regions associated with the 0,1 RTT (upper) and 2 RTT (lower) all-hadronic tt¯+pTmiss signal regions. The 1 lepton, 2 b tag control region (hadA in Table 2) constrains +jets tt¯ background in the 0,1 RTT signal region. This process is constrained in the 2 RTT signal region using the 1 lepton, 1 b tag control region (hadE). The 1 lepton, 0 b tag control regions (hadB, hadC, hadF, hadG) constrain W+jets and Z+jets backgrounds, while the 2 lepton, 0 b tag control region (hadD) provides an additional constraint on the Z+jets background. The lower panels show the ratios of observed to fitted background yields. In both panels, the statistical uncertainties of the data are indicated as vertical error bars and the fit uncertainties as hatched bands. Prefit yields and the ratios of prefit to fitted background expectations are shown as dashed magenta histograms

Fig. 8.

Fig. 8

Observed data, and prefit and fitted background-only event yields in the control regions associated with the bb¯+pTmiss signal region with 1 b tag (upper) and with 2 b tags (lower). The 1 lepton, 1 b control regions (bbA, bbB, bbF and bbG in Table 2) are used to constrain W+jets and tt¯ backgrounds in the bb¯+pTmiss signal regions. The dileptonic control regions (bbC-bbE, bbH-bbJ) are used to constrain Z+jets and tt¯ backgrounds. The lower panels show the ratio of observed to fitted background yields. In both panels, the statistical uncertainties of the data are indicated as vertical error bars and the fit uncertainties as hatched bands. Prefit yields and the ratios of prefit to fitted background expectations are shown as dashed magenta histograms

Dileptonic tt¯ Dileptonic tt¯ background in the +jets tt¯ SR consists of events in which only one of the leptons is identified. A dileptonic CR (slA) for the +jets tt¯+pTmiss search region is defined by requiring an additional lepton with respect to the +jets selection, and by removing the selections on MT, MT2W, and minΔϕ(pTjeti,pTmiss). Both leptons from dileptonic tt¯ decays in the +jets SR are typically within the detector acceptance. The lepton momenta are therefore included in the pT vector sum for this CR, so as to simulate the pTmiss distribution expected for the dileptonic tt¯ background in the +jets SR. Mutual exclusion with the dileptonic tt¯ and Z+jets CRs of the bb¯+pTmiss search region (described below) is ensured by vetoing events that additionally satisfy the selection requirements of those CRs.

The tt¯ background in the bb¯+pTmiss SRs consists of dileptonic and +jets tt¯ events in which no leptons are identified. Dileptonic tt¯ CRs (bbE, bbJ) are formed for the 1 b tag and 2 b tag bb¯+pTmiss SRs by requiring two opposite-charge, different-flavor leptons with pT>30GeV. Tight (loose) identification and isolation criteria are imposed on the leading pT (subleading pT) lepton. In contrast to the dileptonic background in the +jets tt¯+pTmiss SR, the leptons from tt¯ in the bb¯+pTmiss SRs typically fall outside of the detector acceptance. The momentum of the selected leptons in the bb¯+pTmiss CRs is therefore subtracted from the pTmiss observable in order to mimic the pTmiss distribution in the SR. The SR requirements on minΔϕ(pTjeti,pTmiss), which primarily remove multijet background, are not imposed. All other selections from the bb¯+pTmiss SRs are applied.

Dileptonic tt¯ production is the dominant SM background in the dileptonic tt¯+pTmiss SRs. Corresponding CRs are not employed for this search channel because dileptonic tt¯ events are found to be well-modeled by simulation and are selected with high efficiency in the dileptonic SR.

+jetstt¯ The most significant source of background in the hadronic tt¯+pTmiss SRs is +jets tt¯ production. This process contributes to the hadronic tt¯+pTmiss search when the lepton is not identified. Control regions for +jets tt¯ (hadA, hadE) are defined by selecting events with exactly one identified lepton with pT>30GeV, and by requiring MT<160GeV in order to avoid overlaps with the SR of the +jets channel. All other requirements used to define the hadronic SRs are applied, and the CR is split into 0,1 RTT and 2 RTT categories.

The dileptonic tt¯ CRs for the bb¯+pTmiss search (described above) provide stringent constraints on tt¯ backgrounds in the corresponding SRs. Additional constraints on tt¯ background in this channel are provided through four single-lepton CRs (bbA, bbB, bbF, and bbG). A single-electron (muon) CR for the 1 b tag SR requires exactly one electron (muon) with pT>30GeV. The lepton must satisfy tight isolation and identification criteria. The MT observable calculated from the lepton momenta and pTmiss must satisfy 50<MT<160GeV. Except for the requirement on minΔϕ(pTjeti,pTmiss), each of the selection criteria for the 1 b tag signal category must also be satisfied. Analogous CRs for the 2 b tag signal category are formed by applying the corresponding signal selection criteria. As in the dileptonic tt¯ CRs for the bb¯+pTmiss searches, the lepton is removed from the pTmiss calculation.

W+jets A W+jets CR for the +jets tt¯+pTmiss search (slB) is created by requiring zero b tags. The MT>160GeV requirement from the +jets signal selection is maintained, however, the cuts on MT2W and minΔϕ(pTjeti,pTmiss) are removed.

Control regions enriched in both W+jets and Z+jets (hadB, hadF) are formed for the all-hadronic tt¯+pTmiss categories by modifying the SR selections to require zero b tags. In addition, dedicated W+jets CRs (hadC, hadG) are defined by requiring the presence of an isolated, identified lepton with pT>30GeV and MT<160GeV. The W/Z+jets and W+jets CRs are both categorized using the number of RTTs, as in the corresponding SRs. The prefit yields and pTmiss distributions in the hadB and hadC regions are observed to differ from those of data. The discrepancy is due to a mismodeling of hadronic activity in the simulation, which leads to an overestimation of the selection efficiency for the Z+jets and W+jets processes. Reasonable agreement is achieved through the fit, as is shown in Figs 4. and 7.

Fig. 4.

Fig. 4

Observed data, and prefit and fitted background-only pTmiss  distributions in two control regions (hadB and hadC in Table 2) for the 0,1 RTT hadronic tt¯+pTmiss signal region with 0 leptons (upper) and with 1 lepton (lower) and 0 b tags. The 0 lepton control region is used to constrain W+jets and Z+jets backgrounds. The 1 lepton CR provides an additional constraint on W+jets background. The last bin contains overflow events. The lower panels show the ratios of observed data to fitted background yields. In both panels, the statistical uncertainties of the data are indicated as vertical error bars and the fit uncertainties are indicated as hatched bands. Prefit yields and the ratios of prefit to fitted background expectations are shown as dashed magenta histograms

The W+jets process contributes the second-largest background in the 1 b tag SR of the bb¯+pTmiss channel. This background is constrained via the single-lepton CRs (bbA, bbB, bbF, bbG) of the bb¯+pTmiss channel, which were introduced previously in the context of constraints on +jets tt¯ backgrounds.

Z+jets The Z(νν¯)+jets process is a significant source of background in the all-hadronic tt¯+pTmiss SRs. This background is partially controlled via the W/Z+jets CRs (hadB, hadF) described previously. An additional constraint is derived from a distinct Z()+jets CR (hadD), in which two oppositely-charged, same-flavor leptons are required to pass tight isolation and identification requirements. The mass of the lepton pair must fall between 60 and 120 GeV. A prediction for the pTmiss distribution in the hadronic SRs is obtained by subtracting the lepton momenta in the pTmiss calculation. The Z()+jets CR is not categorized in the number of RTTs because of the negligible yields obtained with two RTT tags. The selections for jets and pTmiss used in the 0,1 RTT SR are applied in the Z()+jets CR, with those on pTmiss applied to lepton-subtracted pTmiss. The requirements on minΔϕ(pTjeti,pTmiss) and b tags are removed to increase Z+jets yields. Figure 5 demonstrates that the lepton-subtracted pTmiss distribution observed in the Z()+jets CR of the all-hadronic channel is not well described by the prefit expectation. Agreement substantially improves following the fit.

Fig. 5.

Fig. 5

Observed data, and prefit and fitted background-only, lepton-subtracted pTmiss  distributions in the dileptonic control region (hadD in Table 2) for the all-hadronic tt¯+pTmiss signal regions. This control region is used to constrain Z(νν¯)+jets background. The selections for jets and pTmiss used in the 0,1 RTT signal region are applied, with those on pTmiss applied to lepton-subtracted pTmiss. The signal region requirements on minΔϕ(pTjeti,pTmiss) and b tags are removed to increase Z+jets yields. The last bin contains overflow events. The lower panel shows the ratios of observed data to fitted background yields. In both panels, the statistical uncertainties of the data are indicated as vertical error bars and the fit uncertainties are indicated as hatched bands. Prefit yields and the ratios of prefit to fitted background expectations are shown as dashed magenta histograms

The Z(νν¯)+jets process is also a significant background in the bb¯+pTmiss SRs. This background is constrained with four distinct CRs: bbC, bbD, bbH, and bbI. The Z(ee) and Z(μμ) CRs require two electrons and two muons with pT>30GeV, respectively. The isolation and identification criteria applied on the leading-pT lepton are identical to those used in the W+jets CRs for the bb¯+pTmiss channel. The subleading lepton is required to satisfy a looser set of isolation and identification criteria, as in the dileptonic CRs. The leptons must be consistent with the decay of a Z boson; opposite-charge, same-flavor requirements are imposed, and the leptons must satisfy a constraint on the dilepton mass of 70<m<110GeV. As in the W+jets and dileptonic tt¯ CRs, events must also satisfy all but the minΔϕ(pTjeti,pTmiss) selection criteria of the corresponding 1 b tag or 2 b tag signal category. As in the Z+jets CR for all-hadronic tt¯ channel, lepton momenta are subtracted in the pTmiss calculation to approximate the distribution of pTmiss from Z(νν¯)+jets expected in the bb¯+pTmiss SRs.

Signal extraction

A potential DM signal could be revealed as an excess of events relative to SM expectations in a region of high pTmiss. The shape of the observed pTmiss  distribution provides additional information that is used in this analysis to improve the sensitivity of the search. A potential signal is searched for via simultaneous template fits to the pTmiss  distributions in the SRs and the associated CRs defined in Sects. 4.1 and 4.2. Signal and background pTmiss templates are derived from simulation and are parameterized to allow for constrained shape and normalization variations in the fits.

The fits are performed using the RooStats statistical software package [59]. The effects of uncertainties in the normalizations and in the pTmiss shapes of signal and background processes are represented as nuisance parameters. Uncertainties that only affect normalization are modeled using nuisance parameters with log-normal probability densities. Uncertainties that affect the shape of the pTmiss distribution, which may also include an overall normalization effect, are incorporated using a template “morphing” technique. These treatments, as well as the approach used to account for MC statistical uncertainties on template predictions, follow the procedures described in Ref. [60].

Within each search channel, additional unconstrained nuisance parameters scale the normalization of each dominant background process (tt¯, W+jets, and Z+jets) across the SRs and CRs. For example, a single parameter is associated with the contribution of the +jets tt¯ process in the all-hadronic tt¯+pTmiss SRs and CRs. A separate parameter is associated with the +jets tt¯ background in the bb¯+pTmiss SRs and CRs. These nuisance parameters allow the data in the background-enriched CRs to constrain the background estimates in the SRs to which they correspond. Because separate nuisance parameters are used for each search channel, a given normalization parameter cannot affect background predictions in unassociated search channels. The yields and pTmiss shapes of subdominant backgrounds vary in the fit only through the constrained nuisance parameters. Signal yields in the SRs and associated CRs are scaled simultaneously by signal strength parameters (μ), defined as the ratio of the signal cross section to the theoretical cross section, μ=σ/σTH. The μ parameters scale signal normalization coherently across regions, and thus account for signal contamination in the CRs.

Signal extraction is performed for the individual search channels as well as for their combination. The separate fits to the individual signal and associated CRs provide independent estimates of bb¯+χχ¯ and tt¯+χχ¯ contributions in each channel. In this fitting scenario, separate signal strength parameters are used for each of the search channels. The bb¯+χχ¯ process is considered as a potential signal in the 1 b tag and 2 b tag regions of the bb¯+pTmiss channel. The tt¯+χχ¯ process is searched for in all SRs of the bb¯+pTmiss and tt¯+pTmiss channels separately. The contribution of the bb¯+χχ¯ process in the all-hadronic tt¯+pTmiss channel is negligible due to the jet multiplicity requirement. An inclusive fit to all signal and CRs is also performed. This fit uses a single signal strength parameter to extract the combined contribution of tt¯+χχ¯ and bb¯+χχ¯ in data. Additional details on the per-channel and combined fits are provided in Sect. 7.

Systematic uncertainties

Table 3 summarizes the uncertainties considered in the signal extraction fits. The procedures used to evaluate the uncertainties are described later in this section. Normalization uncertainties are expressed relative to the predicted central values of the corresponding nuisance parameters. These uncertainties are used to specify the widths of the associated log-normal probability densities. The integrated luminosity, b tagging efficiency, pTmiss trigger efficiency, pileup, and multijet/single t background normalization uncertainties are taken to be fully correlated across SRs and CRs. Shape uncertainties are expressed in Table 3 as the change in the prefit yields of the lowest and highest pTmiss bins resulting from a variation of the corresponding nuisance by ± 1 standard deviation (s.d.). These uncertainties are propagated to the fit by using the full pTmiss spectra obtained from ±1 s.d. variations of the corresponding nuisance parameters [60]. The PDF and jet energy scale shape uncertainties are taken to be fully correlated across SRs and CRs. In general, the uncertainty estimation is performed in the same way for signal and background processes; however, the uncertainty from missing higher-order corrections for signal processes, which is approximately 30% at LO in QCD, is not considered to facilitate a comparison with other CMS DM results.

Table 3.

Summary of systematic uncertainties in the signal regions of each search channel. The values given for uncertainties that are not process specific correspond to the dominant background in each signal region (i.e. Z+jets in the 1 b tag bb¯+pTmiss region, and tt¯ in all others). The systematic uncertainties are categorized as affecting either the normalization or the shape of the pTmiss distribution. For shape uncertainties, the ranges quoted give the uncertainty in the yield for the lowest pTmiss bin and for the highest pTmiss bin. Sources of systematic uncertainties that are common across channels are considered to be fully correlated in the channel combination fit

Uncertainty Dileptonic Dileptonic Dileptonic +jets All-hadronic All-hadronic 1 b tag 2 b tag
tt¯(ee)+pTmiss tt¯(eμ)+pTmiss tt¯(μμ)+pTmiss tt¯(e,μ)+pTmiss tt¯(0,1RTT)+pTmiss tt¯(2RTT)+pTmiss bb¯+pTmiss bb¯+pTmiss
Normalization uncertainties (%)
   Integrated luminosity 2.7 2.7 2.7 2.7
   Pileup 0.2 1.4 0.4 0.6
   W/Z+jets heavy flavor fraction 20 20
   Drell–Yan bkg. normalization 64 43
   Single t bkg. normalization 20 20 20 15
   Multijet bkg. normalization 100 50
   Misid. lepton normalization 200 30 48
   RTT efficiency 4
   b tagging efficiency 2.2 2.9 7.5 2.3 12
   Lepton efficiency 4 2
   pTmiss trigger efficiency 2 0.3
   Lepton trigger efficiency 1 2
Shape uncertainties (%)
   PDFs 1.6–2.2 1.8–2.9 1.6–4.9 1.9–3.4 1.0–2.0 0.2–0.8
   Jet energy scale 0.6–14 13–21 10–75 11–24 1.3–2.6
   Top quark pT reweighting 0.9–17 10–12 13–23 15–18
   Diboson μR,μF 4.1–12 12–15 10–18 3.2–23 15–15
   tt¯+Z/Wγ μR,μF 11–25 14–26 11–25 10–15
   tt¯ μR,μF 13–23 19–38 13–25 22–37
   W/Z+jets μR 7.8–8.8 6.9–10 4.4–5.6
   W/Z+jets μF 1.4–2.6 0.2–3.5 2.8–11
   W/Z+jets EWK correction 14–20 4.2–14 4.8–21

The following sources of uncertainty correspond to constrained normalization nuisance parameters in the fit:

  • Integrated luminosity An uncertainty of 2.7% is used for the integrated luminosity of the data sample [61].

  • Pileup modeling Systematic uncertainties due to pileup modeling are taken into account by varying the total inelastic cross section used to calculate the data pileup distributions by ± 5%. Normalization differences in the range of 0.2–1.4% result from reweighting the simulation accordingly.

  • W/Z + heavy-flavor fraction The uncertainty in the fraction of W/Z + heavy-flavor jets is assigned to account for the usage of CRs dominated by light-flavor jets in constraining the prediction of W+jets and Z+jets in SRs that require b tags. The flavor fractions for the W+jets and Z+jets processes are allowed to vary independently within 20% [6265].

  • Drell–Yan background: The uncertainties in the data-driven Drell–Yan background estimates for the dileptonic channels are 64% (ee) and 43% (μμ). These uncertainties are dominated by the statistical uncertainties in quantities used to extrapolate yields from a region near the Z boson mass to regions away from it. Again, these relatively large uncertainties have little effect on the sensitivity of the search.

  • Multijet background normalization Uncertainties of 50–100% (depending on the SR) are applied in the normalization of multijet backgrounds to cover tail effects that are not well modeled by the simulation.

  • Misidentified-lepton background The sources of uncertainty in the misidentified-lepton background for the dileptonic search stem from the uncertainty in the measured misidentification rate, and from the statistical uncertainty of the single-lepton control sample to which the rate is applied. The uncertainties per channel are 200% (ee), 48% (eμ), 30% (μμ), and are dominated by the statistical uncertainty associated with the single-lepton control sample. Because the misidentified lepton background is small, these relatively large uncertainties do not significantly degrade the sensitivity of the search.

  • RTT efficiency Jet energy scale and resolution uncertainties are propagated to the RTT efficiency scale factors by using modified shape templates in the efficiency extraction fit. A systematic uncertainty due to the choice of parton showering scheme is estimated by comparing the efficiencies obtained with default and alternative pTmiss templates. The default simulation is showered using Pythia8.205, which implements dipole-based parton showering. The alternative templates are derived from simulated events that are showered with Herwig [66], which uses an angular-ordered shower model. Overall, statistical plus systematic uncertainties of 6, 3, and 3% are assigned for the hadronic tag, hadronic mistag, and nonhadronic mistag scale factors, respectively. These correspond to an overall normalization uncertainty for the tt¯+pTmiss SRs of 4%.

  • b tagging efficiency The b tagging efficiency and its uncertainty are measured using independent control samples. Uncertainties from gluon splitting, the b quark fragmentation function, and the selections used to define the control samples are propagated to the efficiency scale factors [31]. The corresponding normalization uncertainty ranges from 2.2 to 12%.

  • Lepton identification and trigger efficiency: The uncertainty in lepton identification and triggering efficiency is measured with samples of Z bosons decaying to dielectrons and dimuons [34]. The corresponding normalization uncertainty ranges from 2 to 4%.

  • pTmiss trigger Uncertainties of 0.3–2% (depending on the SR) are associated with the efficiency scale factors of the pTmiss trigger. The efficiency of this trigger is measured using data collected with the single-lepton triggers. For values of pTmiss>200GeV, these data primarily consist of W+jets events.

The following sources of uncertainty correspond to constrained pTmiss  shape nuisance parameters in the fit:

  • PDF uncertainties Uncertainties due to the choice of PDFs are estimated by reweighting the samples with the ensemble of PDF replicas provided by NNPDF3.0 [67]. The standard deviation of the reweighted pTmiss shapes is used as an estimate of the uncertainty.

  • Jet energy scale Reconstructed jet four-momenta in the simulation are simultaneously varied according to the uncertainty in the jet energy scale [29]. Jet energy scale uncertainties are coherently propagated to all observables including pTmiss.

  • Top quark pT reweighting Differential measurements of top quark pair production show that the measured pT spectrum of top quarks is softer than that of simulation. Scale factors to cover this effect have been derived in previous CMS measurements [68] and are applied to all simulated SM tt¯ samples by default. The uncertainty in the top quark pT spectrum is estimated from a comparison with the spectrum obtained without reweighting.

  • Higher-order QCD corrections The uncertainties due to missing higher-order QCD corrections in the LO samples are estimated by generating alternative event samples in which the factorization and renormalization scale parameters (μF,μR) are simultaneously increased or decreased by a factor of two. These uncertainties are correlated across the bins of the pTmiss distribution. Uncertainties in the NLO K-factors applied to W+jets and Z+jets simulation are determined by recalculating the K-factor with μF and μR independently varied by a factor of two up or down.

  • EWK corrections Uncertainties in the K-factors applied to W+jets and Z+jets simulation from missing higher-order EWK corrections are estimated by taking the difference in results obtained with and without the EWK correction applied.

  • Simulation statistics: Shape uncertainties due to the limited sizes of the simulated signal and background samples are included via the method of Barlow and Beeston [60, 69]. This approach allows each bin of the pTmiss distributions to independently fluctuate according to Poisson statistics.

Results and interpretation

Separate signal strength parameters are first determined from fits to each of the bb¯+pTmiss and tt¯+pTmiss channels. These fits use the predicted cross sections and pTmiss shapes from the LHC DMF signal models with gq=gχ=1. The fits result in independent upper limits on signal yields for the bb¯+χχ¯ and tt¯+χχ¯ processes, which are reported in Sect. 7.1.

Next, all SRs and CRs are simultaneously fit under the hypothesis of combined tt¯+χχ¯ and bb¯+χχ¯ contributions. In this case, a single signal strength parameter is used, which results in a combined best fit estimate of the tt¯+χχ¯ and bb¯+χχ¯ signal yields. Again, cross section predictions for tt¯+χχ¯ and bb¯+χχ¯ assume gq=gχ=1. Results from this fit are reported in Sect. 7.2.

The most interesting DM scenarios to explore at the LHC involve on-shell mediator decays to χχ¯, which corresponds to mϕ/a>2mχ. Kinematic variables and cross sections are independent of mχ in this regime [21]. The mχ<10GeV region is of particular interest because of the strong phenomenological and theoretical motivations for low-mass DM [70] and the relative strength of collider experiments in this mass range [71]. For these reasons, the DM mass has been fixed to mχ=1GeV in all signal extraction fits. The results obtained with mχ=1GeV are valid for other values of mχ<mϕ/a/2 provided they are not too near the kinematic threshold.

Individual search results

Table 4 provides the background yields in the SRs obtained from background-only fits to the bb¯+pTmiss and individual tt¯+pTmiss search channels. Relative nuisance parameter shifts – defined as (pfit-pprefit)/σp, where p represents the parameter value and σp its fit uncertainty – do not indicate any particular tension in these fits. The largest shifts correspond to the nuisance parameters for the EWK correction for the W+jets and Z+jets processes in the bb¯+pTmiss channel (+0.8), to the μF,μR scale uncertainty in the tt¯ process in the +jets tt¯+pTmiss channel (+0.6), and to the lepton efficiency in the all-hadronic tt¯+pTmiss channel (-1.9). The nuisance parameter shifts account for residual mismodeling of the yields by the simulation in the background-enriched regions. The background-only fitted pTmiss distributions in the eight SRs are shown in Figs. 9 and 10.

Table 4.

Fitted background yields for a background-only hypothesis in the tt¯+pTmiss and bb¯+pTmiss signal regions. The yields are obtained from separate fits to the bb¯+pTmiss and individual tt¯+pTmiss search channels. Prefit yields for DM produced via a pseudoscalar mediator with mass ma=50GeV and a scalar mediator with mass mϕ=100GeV are also shown. Mediator couplings are set to gq=gχ=1, and a DM particle of mass mχ=1GeV is assumed. Uncertainties include both statistical and systematic components

Channel Dileptonic +jets All-hadronic bb¯+pTmiss
tt¯+pTmiss tt¯+pTmiss tt¯+pTmiss
Signal region ee eμ μμ e,μ 0,1 RTT 2 RTT 1 b tag 2 b tags
tt¯ 1133±29 4228±73 2412±51 24.6±2.2 203±18 152±13 284±28 145±11
W+jets 6.4±1.6 23.1±4.5 11.9±1.3 829±59 38.5±5.5
Z+jets 14±12 2.5±4.7 32±15 0.10±0.04 44±11 13.0±1.3 1613±64 110.7±6.7
Single t 57±12 182±36 104±22 7.0±2.0 19.1±2.0 7.3±1.4 105±16 23.6±4.0
Diboson 2.0±0.4 4.0±0.6 3.1±0.5 1.7±0.4 3.3±0.3 1.0±0.3 38.7±6.6 9.2±1.6
Multijets 0.10±0.08 2.9±2.2 52±22 0.5±0.2
Misid. lepton 2.5±7.7 24±11 29.0±8.7
Background 1208±32 4439±71 2580±52 39.8±3.4 293±21 188±12 2922±77 327±12
Data 1203 4436 2585 45 305 181 2919 337
ma=50GeV
   tt¯+χχ¯ 1.19±0.37 3.48±0.73 1.62±0.36 5.9±1.0 7.5±1.5 8.4±1.8 1.21±0.38 1.34±0.34
   bb¯+χχ¯ 0±0 0±0 0±0 0±0 0.01±0.05 0±0 3.44±0.94 0.55±0.22
mϕ=100GeV
   tt¯+χχ¯ 1.27±0.49 6.3±1.1 2.51±0.76 4.44±0.95 7.3±2.0 10.2±3.1 2.22±0.53 2.11±0.64
   bb¯+χχ¯ 0±0 0±0 0±0 0±0 0.16±0.16 0.04±0.14 2.21±0.66 0.49±0.15

Fig. 9.

Fig. 9

The pTmiss distributions in the following signal regions: dileptonic tt¯+pTmiss in the ee signal region (upper left), in the μμ region (upper right), in the eμ region (lower left), and in +jets tt¯+pTmiss region (lower right). The pTmiss distributions of background correspond to background-only fits to the individual tt¯+pTmiss signal regions and associated background control regions. The prefit pTmiss distribution of an example signal (pseudoscalar mediator, ma=300GeV and mχ=1GeV) is scaled up by a factor of 20. The last bin contains overflow events. The lower panels of each plot show the ratio of observed data to fitted background. The uncertainty bands shown in these panels are the fitted values, and the magenta lines correspond to the ratio of prefit to fitted background expectations

Fig. 10.

Fig. 10

The pTmiss distributions in the following signal regions: all-hadronic tt¯+pTmiss with 0 or 1 RTTs (upper left), all-hadronic tt¯+pTmiss with 2 RTTs (upper right), bb¯+pTmiss with 1 b tag (lower left), and bb¯+pTmiss with 2 b tags (lower right). The pTmiss distributions of background correspond to background-only fits to the individual tt¯+pTmiss and bb¯+pTmiss signal regions and associated background control regions. The prefit pTmiss distribution of an example signal (pseudoscalar mediator, ma=300GeV and mχ=1GeV) is scaled up by a factor of 20. The last bin contains overflow events. The lower panels of each plot show the ratio of observed data to fitted background. The uncertainty bands shown in these panels are the fitted values, and the magenta lines correspond to the ratio of prefit to fitted background expectations

The fitted background-only pTmiss distributions of the individual search channels are assessed using the likelihood ratio for the saturated model, which provides a generalization of the χ2 goodness-of-fit test [72, 73]. Pseudodata are generated from the fitted MC yields to determine the distribution of the likelihood ratio. The p-values obtained are larger than 0.5 for each channel except for the all-hadronic tt¯+pTmiss channel, for which a low p-value of 0.01 is determined. This value appears to result from the scatter in the 0,1 RTT CRs. No significant excess in the individual search channels is observed.

Upper limits are set on the bb¯+χχ¯ and tt¯+χχ¯ production cross sections. The limits are calculated using a modified frequentist approach (CLs) with a test statistic based on the profile likelihood in the asymptotic approximation [7476]. For each signal hypothesis, 95% confidence level (CL) upper limits on the signal strength parameter μ are determined. Tables 5 and 6 list the expected limits on μ obtained for various signal hypotheses. Figure 11 shows the expected and observed limits on μ as a function of the mediator mass for mχ=1GeV.

Table 5.

Observed and expected 95% CL upper limits on the ratios (μ) of the observed tt¯+χχ¯ and bb¯+χχ¯ cross sections to the simplified model expectations. The limits correspond to separate fits to the bb¯+pTmiss and individual tt¯+pTmiss search channels. DM mediators with scalar couplings of gq=gχ=1 are assumed

mϕ, mχ (GeV ) μ(tt¯+ϕtt¯χχ¯) μ(bb¯+ϕbb¯χχ¯)
Dileptonic +jets All-hadronic bb¯+pTmiss bb¯+pTmiss
tt¯+pTmiss tt¯+pTmiss tt¯+pTmiss
Obs. Exp. Obs. Exp. Obs. Exp. Obs. Exp. Obs. Exp.
10, 1 8.3 7.5 3.5 2.0 1.8 2.0 5.0 5.4 1.0×103 789
20, 1 16 11 2.4 1.5 2.0 2.3 12 8.7 87 73
50, 1 21 17 2.6 2.3 2.2 2.7 9.0 8.6 57 36
100, 1 39 30 4.9 3.8 2.5 3.0 31 27 106 80
200, 1 78 82 8.8 7.5 3.9 5.7 55 61 287 287
300, 1 134 129 14 14 7.2 10 136 105 525 544
500, 1 716 609 57 59 29 39 777 608 2.9×103 3.0×103

Table 6.

Same as Table 5, but for DM mediators with pseudoscalar couplings. Again, mediator couplings correspond to gq=gχ=1

ma, mχ (GeV ) μ(tt¯+att¯χχ¯) μ(bb¯+abb¯χχ¯)
Dileptonic +jets All-hadronic bb¯+pTmiss bb¯+pTmiss
tt¯+pTmiss tt¯+pTmiss tt¯+pTmiss
Obs. Exp. Obs. Exp. Obs. Exp. Obs. Exp. Obs. Exp.
10, 1 51 26 4.5 3.6 2.2 2.4 26 21 1.5×104 1.2×104
20, 1 55 26 3.8 3.0 2.6 3.1 42 35 141 117
50, 1 24 23 2.9 2.7 2.5 3.0 54 41 95 68
100, 1 38 29 3.6 3.7 2.4 3.3 60 37 116 81
200, 1 89 64 7.0 6.3 4.4 4.9 58 68 262 214
300, 1 133 123 11 10 5.3 6.9 105 95 625 611
500, 1 1.0×103 729 59 56 32 42 626 697 3.8×103 4.4×103

Fig. 11.

Fig. 11

The ratio (μ) of 95% CL upper limits on the bb¯+χχ¯ and tt¯+χχ¯ cross sections to simplified model expectations. The limits are obtained from fits to the individual bb¯+pTmiss and tt¯+pTmiss search channels for the hypothesis of a scalar mediator (upper) or a pseudoscalar mediator (lower). A fermionic DM particle with a mass of 1GeV is assumed in both panels. Mediator couplings correspond to gq=gχ=1

The all-hadronic and +jets tt¯+pTmiss channels provide the highest sensitivity to the tt¯+χχ¯ process for all mediator masses considered. Expected limits on the tt¯+χχ¯ process from the bb¯+pTmiss channel are comparable with those of the dileptonic tt¯+pTmiss channel. The only relevant search channel for the bb¯+χχ¯ process is bb¯+pTmiss, from which observed upper limits of μ26 are obtained for the pseudoscalar mediator hypothesis (see Table 6). The relatively weak sensitivity of the bb¯+pTmiss channel in the search is due, in part, to the specific signal model considered; the performance of this channel would improve in models in which the mediator couplings to up-type quarks are suppressed.

In all search channels, the expected sensitivity to low-mass scalar mediators is better than that for low-mass pseudoscalars. This reflects the higher predicted cross section for the low-mass scalar, which is approximately 40 times larger than that of the pseudoscalar for a mediator mass of 10GeV  [50]. Scalar and pseudoscalar cross sections become comparable at mediator masses of around 200GeV and above. The expected scalar limits therefore rise quickly with increasing mass, while the limits for the pseudoscalar mediator change less, as can be seen from Tables 5 and 6.

Combined search results

Signal region yields obtained from a simultaneous background-only fit of all of the search channels are similar to those listed in Table 4. Fitted pTmiss distributions in the eight SRs are nearly indistinguishable from those of Figs. 9 and 10. The nuisance parameter shifts in the combined fit are consistent with those of the individual channel fits, while the fit uncertainty in the b tagging efficiency nuisance parameter becomes more tightly constrained. The p value of the saturated likelihood goodness-of-fit test is 0.11, which indicates no significant deviation with respect to background predictions.

A simultaneous signal+background fit is performed using all SRs and CRs, and 95% CL upper limits are set on the cross section ratio μ for DM produced in association with heavy-flavor quark pairs. Table 7 provides limits obtained for the scalar and pseudoscalar mediator hypotheses. These limits are presented graphically in Fig. 12. The combination of tt¯+pTmiss and bb¯+pTmiss search channels enhances sensitivity to both the scalar and the pseudoscalar mediator scenarios.

Table 7.

Observed and expected 95% CL upper limits on the ratio (μ) of the combined tt¯+χχ¯ and bb¯+χχ¯ cross sections to the simplified model expectation. The limits are obtained from a combined fit to all signal and background control regions. DM mediators with scalar or pseudoscalar couplings are assumed. Mediator couplings correspond to gq=gχ=1

mϕ/a, mχ (GeV ) μ(tt¯/bb¯+ϕtt¯χχ¯/bb¯χχ¯) μ(tt¯/bb¯+atott¯χχ¯/bb¯χχ¯)
Obs. Exp. [−1 s.d., +1 s.d.] Obs. Exp. [−1 s.d., +1 s.d.]
10, 1 1.5 1.2 [0.8, 1.9] 1.8 1.9 [1.3, 2.8]
20, 1 1.8 1.3 [0.9, 1.9] 2.0 2.0 [1.4, 3.0]
50, 1 1.4 1.5 [1.0, 2.2] 1.6 2.0 [1.4, 2.9]
100, 1 2.0 2.1 [1.5, 3.2] 1.9 2.5 [1.7, 3.7]
200, 1 3.1 4.5 [3.1, 6.7] 3.3 3.9 [2.7, 5.9]
300, 1 5.6 8.3 [5.8, 12] 4.5 6.0 [4.1, 8.9]
500, 1 24 34 [23, 51] 25 36 [24, 54]

Fig. 12.

Fig. 12

The ratios (μ) of the 95% CL upper limits on the combined tt¯+χχ¯ and bb¯+χχ¯ cross section to simplified model expectations. The limits are obtained from combined fits to the tt¯+pTmiss and bb¯+pTmiss signal and background control regions for the hypothesis of a scalar mediator (upper) and a pseudoscalar mediator (lower). A fermionic DM particle with a mass of 1GeV is assumed in both panels. Mediator couplings correspond to gq=gχ=1

Signal cross sections may be scaled to larger values of gq and gχ using the relationship given in Ref. [21]. This simple scaling approximation is valid as long as the mediator width remains below 20% of its mass. With gq=gχ=1.5, the relative width of the 500GeV scalar (pseudoscalar) mediator is 14% (18%). The relative width decreases with decreasing mediator mass. For coupling values of gq=gχ=1.5, the pTmiss distributions of the various mediator hypotheses are also unchanged with respect to those obtained with gq=gχ=1, thus the limits of Fig. 7 may be scaled accordingly [21]. Assuming coupling values of gq=gχ=1.5, the observed (expected) 95% CL exclusions are mϕ<124(105)GeV for a scalar mediator, and ma<128(76)GeV for a pseudoscalar mediator.

Summary

A search for an excess of events with large missing transverse momentum (pTmiss) produced in association with a pair of heavy-flavor quarks has been performed with a sample of proton-proton interaction data at a center-of-mass energy of 13 TeV. The data correspond to an integrated luminosity of 2.2fb-1 collected with the CMS detector at the CERN LHC. The analysis explores bb¯+pTmiss and the dileptonic, +jets, and all-hadronic tt¯+pTmiss final states. A resolved top quark tagger is used to categorize events in the all-hadronic channel. No significant deviation from the standard model background prediction is observed. Results are interpreted in terms of dark matter (DM) production, and constraints are placed on the parameter space of simplified models with scalar and pseudoscalar mediators. The DM search channels are considered both individually and, for the first time, in combination. The combined search excludes production cross sections larger than 1.5 or 1.8 times the values predicted for a 10GeV scalar mediator or a 10GeV pseudoscalar mediator, respectively, for couplings of gq=gχ=1. The limits presented are the first achieved on simplified models of dark matter produced in association with heavy-flavor quark pairs.

Acknowledgements

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 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 and the CMS detector provided by the following funding agencies: BMWFW and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES and CSF (Croatia); RPF (Cyprus); SENESCYT (Ecuador); MoER, ERC IUT, and ERDF (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NIH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MBIE (New Zealand); PAEC (Pakistan); MSHE and NSC (Poland); FCT (Portugal); JINR (Dubna); MON, RosAtom, RAS, RFBR and RAEP (Russia); MESTD (Serbia); SEIDI, CPAN, PCTI and FEDER (Spain); Swiss Funding Agencies (Switzerland); MST (Taipei); ThEPCenter, IPST, STAR, and NSTDA (Thailand); TUBITAK and TAEK (Turkey); NASU and SFFR (Ukraine); STFC (UK); DOE and NSF (USA). Individuals have received support from the Marie-Curie program and the European Research Council and Horizon 2020 Grant, contract No. 675440 (European Union); the Leventis Foundation; the A. 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 Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Council of Science and Industrial Research, India; the HOMING PLUS program of the Foundation for Polish Science, cofinanced from European Union, Regional Development Fund, the Mobility Plus program of the Ministry of Science and Higher Education, the National Science Center (Poland), contracts Harmonia 2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543, 2014/15/B/ST2/03998, and 2015/19/B/ST2/02861, Sonata-bis 2012/07/E/ST2/01406; the National Priorities Research Program by Qatar National Research Fund; the Programa Clarín-COFUND del Principado de Asturias; the Thalis and Aristeia programs cofinanced by EU-ESF and the Greek NSRF; the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University and the Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand); and the Welch Foundation, contract C-1845.

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