Search for charged Higgs bosons through the violation of lepton universality in t\bar{t} events using pp collision data at \sqrt{s}=7~{}\mbox{TeV} with the ATLAS experiment

Search for charged Higgs bosons through the violation of lepton universality in events using collision data at with the ATLAS experiment

The ATLAS Collaboration
July 14, 2019
Abstract

In several extensions of the Standard Model, the top quark can decay into a bottom quark and a light charged Higgs boson , , in addition to the Standard Model decay . Since bosons decay to the three lepton generations equally, while may predominantly decay into , charged Higgs bosons can be searched for using the violation of lepton universality in top quark decays. The analysis in this paper is based on 4.6 fb of proton–proton collision data at collected by the ATLAS experiment at the Large Hadron Collider. Signatures containing leptons ( or ) and/or a hadronically decaying () are used. Event yield ratios between and , as well as between and , final states are measured in the data and compared to predictions from simulations. This ratio-based method reduces the impact of systematic uncertainties in the analysis. No significant deviation from the Standard Model predictions is observed. With the assumption that the branching fraction is 100%, upper limits in the range 3.2%–4.4% can be placed on the branching fraction for charged Higgs boson masses in the range 90–140 GeV. After combination with results from a search for charged Higgs bosons in decays using the +jets final state, upper limits on can be set in the range 0.8%–3.4%, for in the range 90–160 GeV.

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EUROPEAN ORGANISATION FOR NUCLEAR RESEARCH (CERN)                                                                                                         CERN-PH-EP-2012-347 Submitted to: JHEP   Search for charged Higgs bosons through the violation of lepton universality in events using collision data at with the ATLAS experiment The ATLAS Collaboration Abstract In several extensions of the Standard Model, the top quark can decay into a bottom quark and a light charged Higgs boson , , in addition to the Standard Model decay . Since bosons decay to the three lepton generations equally, while may predominantly decay into , charged Higgs bosons can be searched for using the violation of lepton universality in top quark decays. The analysis in this paper is based on 4.6 fb of proton–proton collision data at collected by the ATLAS experiment at the Large Hadron Collider. Signatures containing leptons ( or ) and/or a hadronically decaying () are used. Event yield ratios between and , as well as between and , final states are measured in the data and compared to predictions from simulations. This ratio-based method reduces the impact of systematic uncertainties in the analysis. No significant deviation from the Standard Model predictions is observed. With the assumption that the branching fraction is 100%, upper limits in the range 3.2%–4.4% can be placed on the branching fraction for charged Higgs boson masses in the range 90–140 GeV. After combination with results from a search for charged Higgs bosons in decays using the +jets final state, upper limits on can be set in the range 0.8%–3.4%, for in the range 90–160 GeV.

1 Introduction

Several non-minimal Higgs scenarios, e.g. Two Higgs Doublet Models (2HDM) Lee:1973iz () predict the existence of charged Higgs bosons ( and ).111In the following, charged Higgs bosons are denoted , with the charge-conjugate always implied. Hence, denotes a positively charged lepton. Their observation would clearly indicate physics beyond the Standard Model (SM), because this theory contains no elementary charged scalar particle. In several models, e.g. a type-II 2HDM describing the Higgs sector of the Minimal Supersymmetric extension of the Standard Model (MSSM) Fayet:1976et (); Fayet:1977yc (); Farrar:1978xj (); Fayet:1979sa (); Dimopoulos:1981zb (), the main production mode for charged Higgs bosons with a mass smaller than the top quark mass () is through top quark decays . The dominant source of top quarks at the Large Hadron Collider (LHC) is through production.222Since the cross section for production from events containing a single top quark is much smaller, this production mode is not considered here.

The combined LEP lower limit on the charged Higgs boson mass is about 90 GeV :2001xy (). Results from direct searches for charged Higgs bosons decaying via using 4.6 fb of LHC data were recently presented by the ATLAS collaboration ourpaper (), with upper limits on the branching fraction between 5% and 1% for charged Higgs boson masses ranging from 90 GeV to 160 GeV, respectively. Using about 2 fb of LHC data, the CMS collaboration established upper limits on in the range 4–2% for charged Higgs boson masses between 80 GeV to 160 GeV cmshpluspaper (). In all of these measurements, as well as in this paper (unless otherwise specified), the assumption is made.

This paper uses an alternative technique addzero () for searches in the mass range 90–160 GeV. Instead of using the shape of discriminating variables in order to search for a local excess of events above the predicted SM background, this analysis is based on the measurement of a ratio of event yields between two final states, which in turn allows for the cancellation of most of the systematic uncertainties. In top quark decays, bosons decay equally to leptons of the three generations, while may decay predominantly into . Hence, an excess of events with at least one hadronically decaying lepton () in the final state, as compared to the rate for events with only electrons and/or muons, is a signature for charged Higgs bosons. A measurement of event yield ratios for and , where stands for any number of neutrinos and where and are electrons and muons, with , is performed:

(1)

This study is performed in a model-independent way, and so exclusion limits are given in terms of , as well as in the scenario Carena:2002qg () of the MSSM. The results are based on 4.6 fb of data from collisions at , collected in 2011 with the ATLAS experiment Aad:2008zzm () at the LHC. These data, as well as the simulated samples used in the analysis, are the same as in ref. ourpaper () and are described briefly in section 2. Then, in section 3, an event selection aimed at collecting a data sample enriched in events is presented, together with the data-driven methods to estimate the backgrounds due to misidentified electrons, muons and hadronically decaying leptons. Exclusion limits in terms of and are discussed in section 4, based on the measured ratios among event yields in +lepton and dilepton final states. Finally, a summary is given in section 5.

2 ATLAS data and simulated events

The ATLAS detector Aad:2008zzm () consists of an inner tracking detector with coverage in pseudorapidity333 ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP) in the centre of the detector and the -axis along the beam pipe. The -axis points from the IP to the centre of the LHC ring, and the -axis points upwards. Cylindrical coordinates are used in the transverse plane, being the azimuthal angle around the beam pipe. The pseudorapidity is defined in terms of the polar angle as . up to , surrounded by a thin 2 T superconducting solenoid, a calorimeter system extending up to for the detection of electrons, photons and hadronic jets, and a large muon spectrometer extending up to that measures the deflection of muon tracks in the field of three superconducting toroid magnets. A three-level trigger system is used, which reduces the recorded event rate to about 300 Hz.

In ATLAS, electrons are reconstructed by matching clustered energy deposits in the electromagnetic calorimeter to tracks reconstructed in the inner detector, and muons are required to contain matching inner detector and muon spectrometer tracks. The combination of all sub-systems provides precise lepton measurements in the pseudorapidity range . Jets, as well as the magnitude of the missing transverse momentum, , are reconstructed using energy deposits over the full coverage of the calorimeters, up to . The anti- algorithm Cacciari:2008gp (); Cacciari:2005hq () with a radius parameter value of is used for jet reconstruction. At least 75% of the tracks associated to a jet (weighted by their transverse momenta) must point to the primary vertex, corresponding to the hardest interaction. This requirement on the “Jet Vertex Fraction” Abazov:2006yb () allows the identification of jets originating from the hard-scatter interaction. An algorithm combining impact-parameter information with the explicit observation of a secondary vertex sys_b () is used in order to identify jets initiated by -quarks, within . The working point chosen for this study corresponds to an average efficiency of about for -jets with in events and a rejection factor of about 130 for light-quark jets. In order to reconstruct hadronically decaying leptons, anti- jets with either one or three associated tracks, depositing in the calorimeter, are considered as candidates taus (). Dedicated algorithms are used to reject electrons and muons. The candidates are further required to have a visible transverse momentum and to be within . The hadronic decays are identified using a likelihood criterion designed to discriminate against quark- and gluon-initiated jets. The working point chosen for this study corresponds to an efficiency of about 30% for hadronically decaying leptons with in events, leading to a rejection factor of about 100–1000 for jets. Selected candidates fulfilling the identification criteria are referred to as “ jets”. When objects selected using the criteria above overlap geometrically, the following procedures are applied, in this order: muons are rejected if found within of any jet with ; a candidate is rejected if found within of a -tagged jet, or within of a selected muon or electron; jets are removed if they are within of a selected jet or electron.

The same full 2011 data set and simulated samples as the analysis in ref. ourpaper () are used, corresponding to an integrated luminosity of 4.6 fb, with an uncertainty of 3.9% lumi (); Aad:2011dr (). In addition to the SM pair production and decay of top quarks, ,444In the simulated SM events, all leptonic decay modes have the same branching fraction (10.8%). the background processes include the production of single top quark, +jets, +jets, diboson, and multi-jet events. Except for the last, which is estimated using data-driven methods, the SM backgrounds are determined using the simulated samples summarised in table 1. In addition to the SM background samples, three types of signal samples are produced with PYTHIA 6.425 Sjostrand:2006za () for : , and , where charged Higgs bosons decay as . TAUOLA 1.20 Was:2004dg () is used for decays, and PHOTOS 2.15 Barberio:1990ms () is used for photon radiation from charged leptons. All generated events are propagated through a detailed GEANT4 simulation Agostinelli:2002hh (); simu (), and they are reconstructed using the same algorithms as the data.

Process Generator Cross section [pb]
SM with at least one lepton MC@NLO 4.01 Frixione:2002ik () 91          hathor ()
Single top quark -channel (with ) AcerMC 3.8     acer () 21          Kidonakis:2011wy ()
Single top quark -channel (with ) MC@NLO 4.01 Frixione:2002ik ()    Kidonakis:2010tc ()
Single top quark -channel (inclusive) MC@NLO 4.01 Frixione:2002ik () 16          Kidonakis:2010ux ()
ALPGEN  2.13 Mangano:2002ea ()  Gavin:2012kw ()
with ALPGEN  2.13 Mangano:2002ea ()  Gavin:2010az ()
HERWIG 6.520 hw () 17          Campbell:2011bn ()
HERWIG 6.520 hw ()    Campbell:2011bn ()
HERWIG 6.520 hw ()    Campbell:2011bn ()
signal with PYTHIA 6.425  Sjostrand:2006za () 9.9
Table 1: Cross sections for the simulated processes and the generators used to model them. All background cross sections are normalised to next-to-next-to-leading-order (NNLO) predictions, except for diboson event production where the next-to-leading-order prediction (NLO) is used. For the diboson events, a filter is applied at the generator level, by requiring at least one electron or muon with and .

3 Event selection and background determination

This analysis uses events passing a single-lepton trigger with an threshold of 20 GeV or 22 GeV for electrons and a threshold of 18 GeV for muons. In order to select a sample enriched in events, the following requirements are made:

  • one charged lepton () having () or () and matched to the corresponding trigger object;

  • at least two jets having and , including exactly two -tags;

  • either exactly one jet with and with no additional charged lepton, or exactly one additional charged lepton with or above 25 GeV and a different flavour than the trigger-matched lepton;

  • .

At this stage, the selected events are classified into two categories according to the single-lepton trigger that they fire: an electron trigger (EL) or a muon trigger (MU). Each category contains +lepton and dilepton () events. The lepton appearing first in the final state is, by convention, matched to the corresponding trigger object. The EL category therefore consists of and events, while the MU category contains and events. Events firing both a single-electron trigger and a single-muon trigger are assigned to both categories, and accounted for in the combined limit setting, see section 4.3.

The analysis uses the generalised transverse mass  Gross:2009wia () as a selection variable. By construction, it gives an event-by-event lower bound on the mass of the charged ( or Higgs) boson produced in the top quark decay. Hence, it is larger than the true charged Higgs boson mass and smaller than . For incorrect pairings of jets or leptons with -jets, the numerical determination of may fail, hence only events with are kept in the following.

3.1 Backgrounds due to misidentified electrons and muons

A significant background for the search described in this paper consists of events with reconstructed electrons and muons arising from the semileptonic decay of hadrons with - or -quarks, from the decay-in-flight of or mesons and, in the case of electrons, from mesons, photon conversions or shower fluctuations. These are referred to as “misidentified leptons” in the following. Two data samples are defined, which differ only in the lepton identification criteria. The tight sample corresponds to the selection used in the analysis and contains mostly events with real leptons. The loose sample is obtained by loosening the isolation and identification requirements, and it contains mostly events with misidentified leptons.555By construction, the tight sample is a subset of the loose sample. The efficiencies and for a real or misidentified lepton, respectively, to be detected as a tight lepton, are determined from data, with the same method as in ref. ourpaper (). In the final parameterisation of and , dependencies on the pseudorapidity of the lepton, its distance to the nearest jet and the leading jet are taken into account. Based on these efficiencies, the number of misidentified leptons passing the final requirements can be calculated by weighting each event in the data sample with one loose lepton, according to the following per-lepton weights :

  • for a loose but not tight lepton, ;

  • for a tight lepton, .

3.2 Backgrounds due to misidentified jets

About 51% of the simulated events in the +lepton final state contain a jet matched to a hadronically decaying lepton at the generator level. In the other events, the jet is called “misidentified”. It originates from leptons (, ) in 3% of the simulated events and hadronic objects (initiated by light quarks, -quarks or gluons) in 46%. Data-driven methods are used in order to determine the probability of misidentification from electrons and hadronic jets. In the case of electrons, the misidentification probabilities are measured using a control region in the data taus () and then applied to the simulated events, as in the analysis in ref. ourpaper (). The majority of misidentified jets in the final event selection originate from jets, for which the misidentification probability depends on the initial parton (light quark, heavy-flavour quark or gluon). All jet types occur in events, and it is not possible to accurately predict the fraction of each of them, potentially leading to a large systematic uncertainty on the jet misidentification probability. However, the influence of all jet types other than light-quark jets can effectively be eliminated by categorising all events in terms of the charge of the lepton relative to the jet as opposite-sign (OS) or same-sign (SS) events. All processes with gluon and -quark jets produce positively and negatively charged misidentified objects at the same rate. On the other hand, the light-quark jet component in SS events represents both charge misreconstruction and quarks which fragment such that the leading charged particle does not have the same charge as the initial quark. Giving a negative weight to the SS events therefore cancels, on average, the gluon and heavy-flavour-quark jet contributions from the OS events, leaving only light-quark jets misidentified as jets.

The rate at which light-quark jets are misidentified as candidates is derived using a region enriched with + 2 jets events666The leading process in this control region is . in the data, selected by requiring:

  • exactly one electron or muon with or larger than 25 GeV;

  • at least one candidate;

  • at least two jets in addition to the candidate(s), none of them being -tagged;

  • .

In order to reduce the contribution from events with a true lepton, mostly from +jets events, a requirement on the transverse mass is made:

(2)

where is the azimuthal angle between the lepton and the direction of the missing momentum. The + 2 jets events are classified as OS and SS events using the charges of the lepton and the candidate. Figure 1 shows the distribution for OS, SS and OS-SS events fulfilling the + 2 jets selection. This demonstrates the cancellation of heavy-flavour-quark and gluon contributions.

The number of tracks associated to jets misidentified as candidates is found to be poorly modelled in simulation. Events in the data tend to have fewer candidates with one or three tracks (this explains the differences between data and simulation in figure 1). In order to correct the candidate selection efficiencies in simulation, track multiplicity scale factors are derived using OS-SS events fulfilling the + 2 jets selection, and are then applied to all jets misidentified as candidates in the simulation: for 1-track candidates; for 3-track candidates, where the errors are only statistical.

The probability for a light-quark jet to be misidentified as a jet is measured in the data and is binned in , the number of associated tracks (one or three), and the number of tracks found within of the candidate. For each bin, the jet misidentification probability is defined as the number of objects passing the identification based on the likelihood criterion divided by the number prior to requiring identification. OS events are given a weight +1 and SS events are given a weight , in both the numerator and denominator of the jet misidentification probability. After OS-SS subtraction, the selected events mostly contain candidates coming from light-quark jets and, to a much lesser extent, electrons, muons, and true hadronically decaying leptons. Figure 2 shows the measured values of the jet misidentification probability in + 2 jets events selected from the data, after OS-SS subtraction. These are used to scale all simulated events in the signal region. Events fulfilling the requirements listed in the beginning of this section, in which the selected object originates from a jet (of any type), are weighted by the misidentification probabilities. An additional weighting factor (+1 for OS events and for SS events) is then used to perform the OS-SS subtraction.

Figure 1: Distributions of the transverse mass for events fulfilling the + 2 jets selection, without the requirement . Each colour corresponds to a type of generator-level particle matched to a candidate (i.e. the highest energy particle within a cone of radius around the candidate is considered). The SS events are (a) given a weight of and (b) subtracted from the OS events. All simulated SM processes are considered.
Figure 2: Probability for a light-quark jet to be misidentified as a 1-track or 3-track jet, measured in a region enriched with OS-SS + 2 jets events in the data, as a function of (a) and (b) the number of tracks found within of the jet.

4 Results

4.1 Computation of event yield ratios

For each of the four final states considered here (, , and ), the OS-SS event yield can be split into two contributions: from events (where the top quarks may decay into both and ) and from all other SM processes except . The contributions from events are expressed as a function of the cross section , the integrated luminosity , the branching fraction , as well as the selection efficiencies , , and for, respectively, , , and events, in each of the four final states considered here:

(3)

In turn, event yield ratios are defined as:

(4)

The event yields in the +lepton and dilepton final states are summarised in table 2 for the background-only hypothesis, as well as in the presence of a 130 GeV charged Higgs boson in the top quark decay. The predicted values in the SM-only hypothesis and the measured values of the ratios and are summarised in table 3. Note that the event yields for dilepton final states become smaller in the presence of a charged Higgs boson in top quark decays, despite the fact that a lepton decays into an electron or muon more often than a boson. This results from the fact that electrons and muons produced in the decay chain are, on average, softer than those coming from .

Sample OS-SS event yields
Misidentified electrons or muons
+jets & diboson
Single top quark
SM
Data 144 1247
with (130 GeV)
Prediction with signal

Misidentified electrons or muons
+jets & diboson
Single top quark
SM
Data 153 929
with (130 GeV)
Prediction with signal
Table 2: Expected OS-SS event yields after all selection cuts in +lepton and dilepton channels, compared with 4.6 fb of ATLAS data. The numbers shown for a hypothetical 130 GeV signal correspond to . The contribution of events to the background is scaled accordingly. Statistical and systematic uncertainties are combined.
Ratio
SM value
Measured value
Table 3: Predicted (in the SM-only hypothesis) and measured values of the event yield ratios and . For the values of the ratios predicted using simulation, the statistical and systematic uncertainties are combined.

Figure 3 shows the variation of the event yields , , and with , for a charged Higgs boson mass of 130 GeV. The presence of in a fraction of the top quark decays leads to an increase of the number of events with a lepton and a jet. In combination with a small decrease of the number of dilepton events, this leads to an increase of the ratios and . The sensitivity of this analysis to charged Higgs bosons is determined by the rate at which the ratios and change with , which depends on the selection efficiencies , , and, in turn, on the charged Higgs boson mass. For , the rate at which the ratios and change with is found to be two (five) times smaller than for . Indeed, the selection efficiencies , , are reduced for values in the vicinity of , because the -jet arising from becomes softer when the mass difference is smaller.

Figure 3: Relative variation with of (a) the event yields , and their ratio, as well as (b) , and their ratio, assuming the presence of a 130 GeV charged Higgs boson in events.

4.2 Systematic uncertainties

Systematic uncertainties arise from the simulation of the electron and muon triggers, from the reconstruction and identification efficiencies of the physics objects, as well as from the energy/momentum scale and resolution for these objects. In order to assess their impact, the selection cuts of this analysis are re-applied after shifting a particular parameter by its standard deviation uncertainty, while other parameters are fixed. The largest instrumental systematic uncertainties are for jets. In comparison, the systematic uncertainties arising from the reconstruction and identification of electrons, muons and jets are small. All instrumental systematic uncertainties are propagated to the reconstructed .

The cross section used in this analysis is  pb hathor (). To estimate systematic uncertainties arising from the generation and the parton shower model, the acceptance is computed for events produced with either MC@NLO interfaced to HERWIG and JIMMY jm () for the hadronisation and the underlying event, or POWHEG Frixione:2007vw () interfaced to PYTHIA. Systematic uncertainties on initial- and final-state radiation are computed using samples generated with AcerMC interfaced to PYTHIA, where the relevant parameters in PYTHIA are varied in a range given by current experimental data isrfsr (). These systematic uncertainties are dominated by the difference in modelling the numbers of tracks and in, respectively, the core and isolation regions of the jets misidentified as candidates. The various simulated samples are reweighted so that the and the distributions match777Both variables are reweigthed in a correlated way. before the systematic uncertainties on the generation, the parton shower model, as well as initial- and final-state radiation, are evaluated.

For the signal samples, which are generated with PYTHIA (i.e. without higher-order corrections), no alternative generator is available, hence the systematic uncertainty is set to the relative difference in acceptance between events generated with MC@NLO interfaced to HERWIG/JIMMY and with AcerMC, which is also a leading-order generator, interfaced to PYTHIA. For the systematic uncertainty coming from initial- and final-state radiation, the same simulated samples as for the SM events are used. In the evaluation of the systematic uncertainties for the signal samples, only jets matched to true hadronically decaying leptons in the generated events are considered.

For the backgrounds with misidentified leptons, the largest systematic uncertainties arise from the sample dependence: the misidentification probabilities are calculated in a control region dominated by gluon-initiated events, but later used in a data sample with a higher fraction of quark-initiated events. The total systematic uncertainty on the backgrounds with misidentified leptons is 38% for electron-triggered events and 49% for muon-triggered events. It corresponds to the relative variation of the number of events with exactly one trigger-matched lepton and two jets, after having considered all systematic uncertainties. The requirement of having two -jets in the event does not have a significant impact on these systematic uncertainties and neither does the presence of a second lepton.

For the estimation of backgrounds with jets misidentified as hadronically decaying leptons, the systematic uncertainty on the scale factors associated with the number of tracks is determined by varying the requirement on the jet multiplicity and the magnitude of the subtraction of candidates matched to a true electron, muon or lepton in the generated events. This uncertainty is 7% for 1-track jets and 11% for 3-track jets. In addition, systematic uncertainties on the jet misidentification probability arise from statistical uncertainties due to the limited control sample size, the differences between misidentification probabilities computed in the region enriched with + 2 jets events and the signal region, as well as the small contamination from true leptons (including those possibly coming from ) in the region enriched with + 2 jets events.

Some of the systematic uncertainties above affect the +lepton and dilepton event yields in the same manner and, as a result, have a limited impact on and . Systematic uncertainties arising from jets and are common to all reconstructed events in the simulation, hence they should cancel in the ratios and . However, due to the use of data-driven background estimates and because of the removal of geometric overlaps between reconstructed objects, some of these systematic uncertainties still have a minor impact. In the EL (MU) category, the systematic uncertainties related to the trigger-matched electron (muon) are the same for the and ( and ) events, thereby not affecting the predicted value of the ratio (). Those coming from the reconstructed muon (electron) only affect event yields in the denominator, and hence the ratio. Similarly, the systematic uncertainties coming from the jets and their misidentification probabilities only affect the numerator of and , hence they do have an impact on the analysis. This is also the case for systematic uncertainties on the backgrounds with misidentified leptons, which have a larger contribution in the dilepton events, i.e. on the denominator of and . Table 4 shows how these ratios (in the SM-only hypothesis) change when shifting a particular parameter by its standard deviation uncertainty.

Systematic uncertainty
Integrated luminosity 0.3% 0.3%
Electron trigger efficiency 0.1% N/A
Electron reco. and ID efficiencies 0.2% 1.9%
Electron energy resolution 0.1% 0.1%
Electron energy scale 0.1% 0.3%
Muon trigger efficiency N/A 0.1%
Muon reco. and ID efficiencies 1.0% 0.1%
Muon momentum resolution 0.1% 0.1%
Muon momentum scale 0.1% 0.1%
ID efficiency 3.9% 3.9%
energy scale 2.9% 3.0%
mis-ID (data-driven): number of associated tracks 2.1% 2.1%
mis-ID (data-driven): true contamination 0.2% 0.2%
mis-ID (data-driven): signal contamination 0.6% 0.6%
mis-ID (data-driven): event environment 1.3% 1.2%
mis-ID (data-driven): statistical uncertainties 3.3% 3.2%
mis-ID (data-driven): electron veto uncertainties 0.6% 0.3%
-tagging 1.9% 2.3%
Jet vertex fraction 0.1% 0.4%
Jet energy resolution 0.4% 0.1%
Jet energy scale 0.7% 0.5%
Jet reconstruction efficiency 0.1% 0.4%
0.3% 0.1%
: cross section 0.7% 0.6%
: generator and parton shower 5.7% 4.4%
: initial- and final-state radiation 3.6% 3.7%
Backgrounds with misidentified leptons 3.5% 4.3%
Total (added in quadrature) 10.3% 10.1%
Table 4: Relative variation of the ratios and in the SM-only hypothesis after shifting a particular parameter by its standard deviation uncertainty.

4.3 Exclusion limits

To test the compatibility of the data with the background-only or the signal+background hypotheses, a profile likelihood ratio Cowan:2010js () is used with and as the discriminating variables. The systematic uncertainties are incorporated via nuisance parameters, and the one-sided profile likelihood ratio, , is used as a test statistic. No significant deviation from the SM prediction is observed in 4.6 fb of data. Exclusion limits are set on the branching fraction by rejecting the signal hypothesis at the 95% confidence level (CL) using the procedure Read:2002hq (). These limits are based on the asymptotic distribution of the test statistic Cowan:2010js (). They are first set for electron-triggered and muon-triggered events separately (see figure 4), and then using a global event yield ratio defined as:

(5)

where is the event yield in the channel after removing the dilepton events that simultaneously fire a single-electron trigger and a single-muon trigger, as those already appear in . The fraction of dilepton events common to the and final states is about 42% in the data. Using this global event yield ratio, upper limits in the range 3.2%–4.4% can be placed on for charged Higgs boson masses in the range 90–140 GeV, as shown in figure 5 and table 5.

In a previously published search for charged Higgs bosons ourpaper (), based on the data collected in 2011 with ATLAS, upper limits on were derived using various distributions of discriminating variables in +jets, +lepton and lepton+jets final states. The most sensitive channel was +jets, except for low values of . A new set of combined upper limits on is derived, using the transverse mass distribution of +jets events from ref. ourpaper () and the global event yield ratio , as shown in figure 6 and table 6. Since a lepton veto is applied for charged Higgs boson searches in +jets final states, there is no correlation between such events and those selected in this study to determine the event yield ratios. With this combination of upper limits, charged Higgs bosons can be excluded for values of the branching fraction larger than 0.8% to 3.4%, for between 90 GeV and 160 GeV. These exclusion limits represent an improvement with respect to those published in ref. ourpaper ().

(a) Using
(b) Using
Figure 4: Upper limits on derived from the event yield ratios (a) and (b) , as a function of the charged Higgs boson mass, obtained for an integrated luminosity of 4.6 fb and with the assumption . The solid line in the figure is used to denote the observed 95% CL upper limits, while the dashed line represents the expected exclusion limits. The green and yellow regions show the 1 and 2 error bands.
Figure 5: Upper limits on derived from the event yield ratio , as a function of the charged Higgs boson mass, obtained for an integrated luminosity of 4.6 fb and with the assumption . The solid line in the figure is used to denote the observed 95% CL upper limits, while the dashed line represents the expected exclusion limits. The green and yellow regions show the 1 and 2 error bands.
(GeV) 90 100 110 120 130 140 150 160
95% CL observed
(expected) limit on 3.3% 3.6% 3.2% 3.4% 3.6% 4.4% 7.3% 18.3%
using (3.1%) (3.3%) (3.0%) (3.1%) (3.3%) (4.0%) (6.7%) (16.8%)
the ratio
Table 5: Observed (expected) 95% CL upper limits on derived from the event yield ratio , as a function of the charged Higgs boson mass, obtained for an integrated luminosity of 4.6 fb and with the assumption that .
Figure 6: Upper limits on derived from the transverse mass distribution of +jets events in ref. ourpaper () and the event yield ratio , as a function of the charged Higgs boson mass, obtained for an integrated luminosity of 4.6 fb and with the assumption . The solid line in the figure is used to denote the observed 95% CL upper limits, while the dashed line represents the expected exclusion limits. The green and yellow regions show the 1 and 2 error bands.
(GeV) 90 100 110 120 130 140 150 160
95% CL observed
(expected) limit on 3.4% 2.9% 1.7% 1.1% 0.9% 0.8% 1.0% 1.1%
using (3.1%) (2.8%) (1.9%) (1.4%) (1.2%) (1.1%) (1.2%) (1.2%)
and +jets
95% CL observed
(expected) limit 4.8% 3.4% 2.1% 1.3% 1.1% 1.0% 1.1% 1.0%
in ref. ourpaper () (4.2%) (3.5%) (2.5%) (1.9%) (1.5%) (1.3%) (1.2%) (1.3%)
Table 6: Observed (expected) 95% CL upper limits on derived using +jets events in ref. ourpaper () and the ratio , as a function of the charged Higgs boson mass, obtained for an integrated luminosity of 4.6 fb and assuming that . The exclusion limits published in ref. ourpaper () are also shown for comparison purposes.

In figure 7, the combined limit on is interpreted in the context of the scenario Carena:2002qg () of the MSSM. The following relative theoretical uncertainties on are considered Heinemeyer:1998yj (); Dittmaier:2012vm (): 5% for one-loop electroweak corrections missing from the calculations, 2% for missing two-loop QCD corrections, and about 1% (depending on ) for -induced uncertainties, where is a correction factor for the running -quark mass Carena:1999py (). These uncertainties are added linearly, as recommended by the LHC Higgs cross-section working group Dittmaier:2012vm ().

Figure 7: Limits for charged Higgs boson production from top quark decays in the - plane, derived using +jets events in ref. ourpaper () and the ratio , in the context of the scenario of the MSSM. The band around the observed limit (dashed lines) shows the theoretical uncertainties. Values below , where the calculations in the MSSM become non-perturbative, are not considered, as the results become unphysical.

Assuming that the boson recently discovered at the LHC higgsATLAS (); higgsCMS () is one of the neutral MSSM Higgs bosons, only a certain region in the - plane is still allowed for a given scenario arXiv:1112.3026 (). If the new boson is the lightest neutral MSSM Higgs boson (), it would imply and . However, the allowed region depends strongly on MSSM parameters which, on the other hand, do not affect the charged Higgs boson production and decay significantly. Thus, by adjusting these MSSM parameters, the region in which the Higgs boson mass can take a value of about 125 GeV can be changed significantly, while the ATLAS exclusion region shown here is relatively stable with respect to these changes. Should the recently discovered boson instead be the heavier CP-even Higgs boson (), the additional constraint from only leads to an upper limit of roughly  GeV, with suppressed couplings for . If the recently discovered particle is an MSSM Higgs boson, excluding a low-mass charged Higgs boson would thus imply that it is the lightest neutral state .

5 Conclusions

Charged Higgs bosons have been searched for in  events, in the decay mode followed by . A total of 4.6 fb of collision data at , recorded in 2011 with the ATLAS experiment at the LHC, is used. Event yield ratios are measured in the data and compared to the predictions from simulations, between electron-triggered and events, and between muon-triggered and events, in order to search for a violation of lepton universality in events. This method reduces the impact of several systematic uncertainties in the analysis. Data-driven methods and simulation are employed to estimate the number of background events. The observed data are found to be in agreement with the SM predictions. Assuming , upper limits at the 95% confidence level in the range 3.2%–4.4% have been placed on the branching fraction for charged Higgs boson masses in the range 90–140 GeV. For charged Higgs boson masses below 110 GeV, this analysis improves the previously published limits on , based on direct searches for charged Higgs bosons in decays using the lepton+jets, +jets and +lepton final states. When the results of the present analysis are combined with the results from the search for charged Higgs bosons in decays using the +jets final state ourpaper (), upper limits on are set in the range 0.8%–3.4%, for between 90 GeV and 160 GeV.

6 Acknowledgements

We thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently.

We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWF and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF, DNSRC and Lundbeck Foundation, Denmark; EPLANET, ERC and NSRF, European Union; IN2P3-CNRS, CEA-DSM/IRFU, France; GNSF, Georgia; BMBF, DFG, HGF, MPG and AvH Foundation, Germany; GSRT and NSRF, Greece; ISF, MINERVA, GIF, DIP and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; FOM and NWO, Netherlands; BRF and RCN, Norway; MNiSW, Poland; GRICES and FCT, Portugal; MERYS (MECTS), Romania; MES of Russia and ROSATOM, Russian Federation; JINR; MSTD, Serbia; MSSR, Slovakia; ARRS and MVZT, Slovenia; DST/NRF, South Africa; MICINN, Spain; SRC and Wallenberg Foundation, Sweden; SER, SNSF and Cantons of Bern and Geneva, Switzerland; NSC, Taiwan; TAEK, Turkey; STFC, the Royal Society and Leverhulme Trust, United Kingdom; DOE and NSF, United States of America.

The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN and the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (UK) and BNL (USA) and in the Tier-2 facilities worldwide.

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The ATLAS Collaboration

G. Aad, T. Abajyan, B. Abbott, J. Abdallah, S. Abdel Khalek, A.A. Abdelalim, O. Abdinov, R. Aben, B. Abi, M. Abolins, O.S. AbouZeid, H. Abramowicz, H. Abreu, B.S. Acharya, L. Adamczyk, D.L. Adams, T.N. Addy, J. Adelman, S. Adomeit, P. Adragna, T. Adye, S. Aefsky, J.A. Aguilar-Saavedra, M. Agustoni, M. Aharrouche, S.P. Ahlen, F. Ahles, A. Ahmad, M. Ahsan, G. Aielli, T.P.A. Åkesson, G. Akimoto, A.V. Akimov, M.A. Alam, J. Albert, S. Albrand, M. Aleksa, I.N. Aleksandrov, F. Alessandria, C. Alexa, G. Alexander, G. Alexandre, T. Alexopoulos, M. Alhroob, M. Aliev, G. Alimonti, J. Alison, B.M.M. Allbrooke, P.P. Allport, S.E. Allwood-Spiers, J. Almond, A. Aloisio, R. Alon, A. Alonso, F. Alonso, A. Altheimer, B. Alvarez Gonzalez, M.G. Alviggi, K. Amako, C. Amelung, V.V. Ammosov, S.P. Amor Dos Santos, A. Amorim, N. Amram, C. Anastopoulos, L.S. Ancu, N. Andari, T. Andeen, C.F. Anders, G. Anders, K.J. Anderson, A. Andreazza, V. Andrei, M-L. Andrieux, X.S. Anduaga, S. Angelidakis, P. Anger, A. Angerami, F. Anghinolfi, A. Anisenkov, N. Anjos, A. Annovi, A. Antonaki, M. Antonelli, A. Antonov, J. Antos, F. Anulli, M. Aoki, S. Aoun, L. Aperio Bella, R. Apolle, G. Arabidze, I. Aracena, Y. Arai, A.T.H. Arce, S. Arfaoui, J-F. Arguin, S. Argyropoulos, E. Arik, M. Arik, A.J. Armbruster, O. Arnaez, V. Arnal, A. Artamonov, G. Artoni, D. Arutinov, S. Asai, S. Ask, B. Åsman, D. Asner, L. Asquith, K. Assamagan, A. Astbury, M. Atkinson, B. Aubert, E. Auge, K. Augsten, M. Aurousseau, G. Avolio, D. Axen, G. Azuelos, Y. Azuma, M.A. Baak, G. Baccaglioni, C. Bacci, A.M. Bach, H. Bachacou, K. Bachas, M. Backes, M. Backhaus, J. Backus Mayes, E. Badescu, P. Bagnaia, S. Bahinipati, Y. Bai, D.C. Bailey, T. Bain, J.T. Baines, O.K. Baker, M.D. Baker, S. Baker, P. Balek, E. Banas, P. Banerjee, Sw. Banerjee, D. Banfi, A. Bangert, V. Bansal, H.S. Bansil, L. Barak, S.P. Baranov, A. Barbaro Galtieri, T. Barber, E.L. Barberio, D. Barberis, M. Barbero, D.Y. Bardin, T. Barillari, M. Barisonzi, T. Barklow, N. Barlow, B.M. Barnett, R.M. Barnett, A. Baroncelli, G. Barone, A.J. Barr, F. Barreiro, J. Barreiro Guimarães da Costa, R. Bartoldus, A.E. Barton, V. Bartsch, A. Basye, R.L. Bates, L. Batkova, J.R. Batley, A. Battaglia, M. Battistin, F. Bauer, H.S. Bawa, S. Beale, T. Beau, P.H. Beauchemin, R. Beccherle, P. Bechtle, H.P. Beck, K. Becker, S. Becker, M. Beckingham, K.H. Becks, A.J. Beddall, A. Beddall, S. Bedikian, V.A. Bednyakov, C.P. Bee, L.J. Beemster, M. Begel, S. Behar Harpaz, P.K. Behera, M. Beimforde, C. Belanger-Champagne, P.J. Bell, W.H. Bell, G. Bella, L. Bellagamba, M. Bellomo, A. Belloni, O. Beloborodova, K. Belotskiy, O. Beltramello, O. Benary, D. Benchekroun, K. Bendtz, N. Benekos, Y. Benhammou, E. Benhar Noccioli, J.A. Benitez Garcia, D.P. Benjamin, M. Benoit, J.R. Bensinger, K. Benslama, S. Bentvelsen, D. Berge, E. Bergeaas Kuutmann, N. Berger, F. Berghaus, E. Berglund, J. Beringer, P. Bernat, R. Bernhard, C. Bernius, T. Berry, C. Bertella, A. Bertin, F. Bertolucci, M.I. Besana, G.J. Besjes, N. Besson, S. Bethke, W. Bhimji, R.M. Bianchi, L. Bianchini, M. Bianco, O. Biebel, S.P. Bieniek, K. Bierwagen, J. Biesiada, M. Biglietti, H. Bilokon, M. Bindi, S. Binet, A. Bingul, C. Bini, C. Biscarat, B. Bittner, C.W. Black, K.M. Black, R.E. Blair, J.-B. Blanchard, T. Blazek, I. Bloch, C. Blocker, J. Blocki, A. Blondel, W. Blum, U. Blumenschein, G.J. Bobbink, V.S. Bobrovnikov, S.S. Bocchetta, A. Bocci, C.R. Boddy, M. Boehler, J. Boek, T.T. Boek, N. Boelaert, J.A. Bogaerts, A. Bogdanchikov, A. Bogouch, C. Bohm, J. Bohm, V. Boisvert, T. Bold, V. Boldea, N.M. Bolnet, M. Bomben, M. Bona, M. Boonekamp, S. Bordoni, C. Borer, A. Borisov, G. Borissov, I. Borjanovic, M. Borri, S. Borroni, J. Bortfeldt, V. Bortolotto, K. Bos, D. Boscherini, M. Bosman, H. Boterenbrood, J. Bouchami, J. Boudreau, E.V. Bouhova-Thacker, D. Boumediene, C. Bourdarios, N. Bousson, A. Boveia, J. Boyd, I.R. Boyko, I. Bozovic-Jelisavcic, J. Bracinik, P. Branchini, A. Brandt, G. Brandt, O. Brandt, U. Bratzler, B. Brau, J.E. Brau, H.M. Braun, S.F. Brazzale, B. Brelier, J. Bremer, K. Brendlinger, R. Brenner, S. Bressler, T.M. Bristow, D. Britton, F.M. Brochu, I. Brock, R. Brock, F. Broggi, C. Bromberg, J. Bronner, G. Brooijmans, T. Brooks, W.K. Brooks, G. Brown, P.A. Bruckman de Renstrom, D. Bruncko, R. Bruneliere, S. Brunet