EUROPEAN ORGANISATION FOR NUCLEAR RESEARCH (CERN)
CERN-PH-EP-2012-360
Submitted to: PLB
Search for long-lived, multi-charged particles in pp collisions at
√
s
= 7 TeV using the ATLAS detector
The ATLAS Collaboration
Abstract
A search for highly ionising, penetrating particles with electric charges from |q|
= 2e to 6e is
per-formed using the ATLAS detector at the CERN Large Hadron Collider. Proton-proton collision data
taken at
√
s
= 7 TeV during the 2011 running period, corresponding to an integrated luminosity of
4.4 fb
−1, are analysed. No signal candidates are observed, and 95% confidence level cross-section
upper limits are interpreted as mass-exclusion lower limits for a simplified Drell–Yan production model.
In this model, masses are excluded from 50 GeV up to 430, 480, 490, 470 and 420 GeV for charges
2e, 3e, 4e, 5e and 6e, respectively.
Search for long-lived, multi-charged particles in pp collisions at
√
s
= 7 TeV using the
ATLAS detector
The ATLAS Collaboration
Abstract
A search for highly ionising, penetrating particles with electric charges from |q|= 2e to 6e is performed using the ATLAS detector at the CERN Large Hadron Collider. Proton-proton collision data taken at √s= 7 TeV during the 2011 running period, corresponding to an integrated luminosity of 4.4 fb−1, are analysed. No signal candidates are observed, and 95% confidence level cross-section
upper limits are interpreted as mass-exclusion lower limits for a simplified Drell–Yan production model. In this model, masses are excluded from 50 GeV up to 430, 480, 490, 470 and 420 GeV for charges 2e, 3e, 4e, 5e and 6e, respectively.
Keywords: high-energy collider experiment, long-lived particle, highly ionising, new physics, multiple electric charges
1. Introduction
Numerous theories of physics beyond the Standard Model (SM) predict long-lived1 exotic objects producing anomalous
ionisation. These include magnetic monopoles [1], dyons [2], long-lived micro black holes in models of low-scale gravity [3] and Q-balls [4], which are non-topological solitons pre-dicted by minimal supersymmetric generalisations of the SM. No such particles have so far been observed in cosmic-ray and collider searches [1, 5–7], including several recent searches at the Large Hadron Collider (LHC) [8–13]. The high centre-of-mass energy of the LHC makes a new energy regime accessible, and searching for multi-charged particles with electric charges 2e ≤ |q| ≤ 6e complements the searches for slow singly charged particles [10] and for particles with charges beyond 6e [8].
The existence of long-lived particles with an electric charge |q| > e could have implications for the formation of composite dark matter [14]. Two extensions of the SM in which heavy sta-ble multi-charged particles are predicted are the AC model [15] and the walking technicolour model [16–18]. The AC model is based on the approach of almost-commutative geometry [19] which extends the fermion content of the SM by two heavy par-ticles with opposite electric charges, ±q. The minimal walk-ing technicolour model predicts the existence of three particle pairs, with electric charges given in general by q+ e, q, and q − e, which would behave like leptons in the detector. In both of these models, |q| may be larger than e.
This Letter describes a search for multi-charged particles in √
s= 7 TeV pp collisions using data collected in 2011 by the ATLAS detector at the CERN LHC. The data sample corre-sponds to an integrated luminosity of 4.4 fb−1. Multi-charged
particles will be highly ionising, and thus leave an abnormally large specific ionisation signal, dE/dx. In this Letter, a search
1The term long-lived in this paper refers to a particle that does not decay within the ATLAS detector.
for such particles traversing the ATLAS detector leaving a track in the inner tracking detector, and producing a signal in the muon spectrometer, is reported. A SM-like coupling propor-tional to the electric charge is assumed as the production model of the multi-charged particles. Therefore, the main production mode is Drell–Yan (DY) with no weak coupling. Multi-charged particles can also be pair-produced from radiated photons re-sulting in a larger production cross section, and in some cases non-perturbative effects [20] can also enhance the production rate. In the derivation of limits, neither enhancement is included in the calculation resulting in conservative limits in these sce-narios.
2. ATLAS detector
The ATLAS detector [21] covers nearly the entire solid an-gle around the collision point. It consists of an inner track-ing detector (ID) compristrack-ing a silicon pixel detector (pixel), a silicon microstrip detector (SCT) and a Transition Radia-tion Tracker (TRT). Apart from being a straw-based tracking detector, the TRT (covering |η| < 2.0)2 also provides
parti-cle identification via transition radiation and ionisation energy loss measurements [22]. The ID is surrounded by a thin super-conducting solenoid providing a 2 T axial magnetic field, and by high-granularity liquid-argon (LAr) sampling electromag-netic calorimeters. An iron–scintillator tile calorimeter pro-vides hadronic energy measurements in the central rapidity re-gion. The endcap and forward regions are instrumented with LAr calorimeters for both electromagnetic and hadronic en-ergy measurements. The calorimeter system is surrounded by a
2The ATLAS coordinate system is right-handed with the pseudorapidity, η, defined as η= − ln[tan(θ/2)], where the polar angle θ is measured with respect to the LHC beamline. The azimuthal angle, φ, is measured with respect to the x-axis, which points towards the centre of the LHC ring. The z-axis is parallel to the anti-clockwise beam viewed from above. Transverse momentum and energy are defined as pT= p sin θ and ET= E sin θ, respectively.
muon spectrometer (MS) incorporating three superconducting toroid magnet assemblies. The MS is a combination of several sub-detectors used to measure muons that traverse the ATLAS calorimeters. The Resistive Plate Chambers (RPC) in the barrel region (|η| < 1.05) and the Thin Gap Chambers (TGC) in the endcap region (1.05 < |η| < 2.4) provide signals for the trigger for charged particles reaching the MS. Monitored Drift Tube (MDT) chambers measure the momentum and track positions of muons with very high precision.
3. Simulated samples
Benchmark samples of simulated events with multi-charged particles are produced for masses of 50, 100, 200, 300, 400, 500 and 600 GeV, with charges3 2e, 3e, 4e, 5e and 6e. Pairs of long-lived multi-charged particles are simulated using Mad-Graph5 [23] via the DY process to model the kinematic distri-butions. The DY production model also determines the cross section used for limit setting. Typical values for the cross sec-tions of simulated multi-charge pair production range from tens of pb for a mass of 50 GeV down to a few fb at a mass of 600 GeV. Events are generated using the CTEQ6L1 [24] parton distribution functions, and Pythia version 6.425 [25] is used for hadronisation and underlying-event generation. A Geant4 sim-ulation [26, 27] is used to model the response of the ATLAS detector, and the samples are reconstructed and analysed in the same way as the data. The production cross sections are esti-mated using MadGraph5 and are cross-checked with CalcHEP 3.4 [28]. Each simulated event is overlaid with additional col-lision events (“pile-up”) in order to reproduce the observed dis-tribution of the number of proton–proton collisions per bunch crossing. In 2011 data the average number of interactions per bunch crossing was typically between 5 and 20. These sam-ples are used to determine the detection efficiency, the resolu-tion on the quantities used in the event selecresolu-tion and the associ-ated systematic uncertainties for multi-charged particles. While the background estimation is data-driven, muons from Z → µµ simulated samples are used to calibrate the selection variables. These samples are generated in Pythia and passed through the Geant4 simulation of the ATLAS detector.
4. Ionisation estimators
The specific energy loss, dE/dx, is described by the Bethe– Bloch formula [29]. The energy loss depends quadratically on the particle charge, q, so that particles with higher charges have a significantly higher energy loss.
4.1. MDT dE/dx
Each drift tube of the MDT system provides a signal propor-tional to the charge from ionisation, which is used to estimate dE/dx. A truncated mean of dE/dx, where the maximum value is removed, is used as the overall MDT dE/dx estimator. As each track crosses more than 20 drift tubes, the MDT dE/dx provides a good estimate of ionisation losses.
3Wherever a charge is quoted for the exotic particles, the charge conjugate state is also implied.
4.2. TRT dE/dx
Energy deposits in a TRT straw greater than 200 eV (low-threshold hits) are used for tracking, while those that exceed 6 keV (high-threshold hits) occur due to the passage of highly ionising particles or due to transition radiation emitted by highly relativistic electrons when they cross radiator material between the straws. The estimated dE/dx value for each hit is derived from the time the signal remains above the low thresh-old. The TRT dE/dx is the truncated mean of the dE/dx esti-mates, where the highest estimate is removed. On average, a track in the TRT contains 32 hits. Additionally, the ratio of the number of high-threshold (HT) hits to the total number of TRT hits on a given track fHTprovides a second estimator of high ionisation.
4.3. Pixel dE/dx
The pixel detector measures the charge from ionisation in each pixel. The dE/dx from the pixel detector is calculated from the truncated mean of measurements from several clus-ters of pixels [30]. Particles with charges higher than 2e deposit energies which easily exceed the dynamic range of the pixel de-tector readout. Therefore, the electronic signal is saturated and pixel information will not be read out leading to an unreliable dE/dx measurement for such particles.
4.4. dE/dx significance
The significance of each dE/dx variable is defined as the dif-ference between the observed dE/dx of the track and that ex-pected for muons, measured in units of the uncertainty of the measurement:
S(dE/dx)=dE/dxtrack− hdE/dxµi
σ(dE/dxµ) . (1)
Here dE/dxtrack represents the estimated dE/dx of the track,
and hdE/dxµi and σ(dE/dxµ), respectively, are the mean and
the width of the dE/dx distribution for muons in data.
To obtain expected dE/dx values and their resolution for the different detector components (MDT, TRT, Pixel), the dE/dx variables are calibrated with muons from Z → µµ events in data and simulation. Muons for this calibration are selected by requiring a track reconstructed in the MS matched to a good quality track in the ID with pT > 20 GeV and |η| < 2.4. Each
muon is further required to belong to an oppositely charged pair with dimuon mass between 81 GeV and 101 GeV. Fig. 1 shows the comparison between these muons in data and simulation for the MDT and TRT dE/dx significance. While the TRT distri-bution shows good agreement except in the tails, a discrepancy between simulation and data is observed for the MDT signifi-cance. This discrepancy has a small effect on the limit setting, and the effect is included in the systematic uncertainties. Fig. 2 shows the distributions of the MDT and TRT dE/dx signifi-cance for simulated muons from Z → µµ production compared to those of multi-charged particles for different charges (2e, 4e and 6e) and for a mass of 200 GeV. For the multi-charge particle
search, the S (MDT dE/dx) and S (TRT dE/dx) variables are re-quired to exceed threshold values. These thresholds are estab-lished from the separation of the dE/dx significance distribu-tions between muons and |q| = 2e signal particles. The dE/dx significance distributions for higher charge values, |q| > 2e, are further separated from muons, as seen for simulated events in Fig. 2. The detailed response for these higher charge particles may not be perfectly modelled by the simulation due to satu-ration effects. However, their dE/dx response will certainly be higher than that of |q| = 2e particles, and thus their detailed response has no significance for the analysis. The separation power of the pixel dE/dx significance is shown in Fig. 3 for a 2e charge at m = 200, 400 and 600 GeV. The behaviour of the dE/dx significance distributions is found to be as expected with respect to pT, η, and φ. For simulated multi-charged
par-ticles the dE/dx significances strongly depend on the particle’s charge and weakly on the particle’s mass.
S(MDT dE/dx) -5 0 5 10 15 20 1 /N d N /d S (M D T d E /d x ) -5 10 -4 10 -3 10 -2 10 -1 10 Monte Carlo -µ + µ → Z data -µ + µ → Z ATLAS -1 L dt = 4.4 fb
∫
= 7 TeV s S(TRT dE/dx) -5 0 5 10 15 20 1 /N d N /d S (T R T d E /d x ) -6 10 -5 10 -4 10 -3 10 -2 10 -1 10 Monte Carlo -µ + µ → Z data -µ + µ → Z ATLAS -1 L dt = 4.4 fb∫
= 7 TeV sFigure 1: Comparison of normalised distributions of the S (MDT dE/dx) (top) and S (TRT dE/dx) (bottom) for muons from Z → µµ events in data and simu-lation.
5. Event and candidate selection
Multi-charged candidates are sought for among those parti-cles traversing the entire ATLAS detector, thus being initially
S(MDT dE/dx) -5 0 5 10 15 20 1 /N d N /d S (M D T d E /d x ) 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2 0.22 -µ + µ → Z
Mass 200 GeV, |q|=2e Mass 200 GeV, |q|=4e Mass 200 GeV, |q|=6e
ATLAS Simulation S(TRT dE/dx) -5 0 5 10 15 20 1 /N d N /d S (T R T d E /d x ) 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 -µ + µ → Z
Mass 200 GeV, |q|=2e Mass 200 GeV, |q|=4e Mass 200 GeV, |q|=6e
ATLAS Simulation
Figure 2: Normalised distributions of S (MDT dE/dx) (top) and S (TRT dE/dx) (bottom) for simulated muons and multi-charged particles. Distributions are shown for the signal samples for |q|= 2e, 4e and 6e, for a mass of 200 GeV.
selected as muons. Candidates are selected by analysing the specific ionisation losses in the different detectors. The search is based on a cut-and-count method, described in Section 6, where the signal region is defined by high dE/dx significances of the track measured by the TRT and MDT detectors.
Track reconstruction assumes particles with charge ±1e, whereas particles with higher charges bend more in the mag-netic field. Therefore, the effective cut on the momentum of the multi-charged particle imposed by the trigger and selection is a factor of |q|/e higher than the cut on the muon candidate. In the following, we will refer to pT as the reconstructed transverse
momentum assuming charge |q|= 1e. 5.1. Trigger and event selection
Events collected with a single-muon trigger [31] with a trans-verse momentum threshold of pT = 18 GeV are considered. In
simulated events the trigger efficiency from the RPC is cor-rected as a function of a particle’s η and β, where β is the ratio of the particle’s velocity to the speed of light. Events are further required4to contain either at least one muon with p
T> 75 GeV
4Information on the MDT dE/dx is not available in the standard ATLAS data stream. Hence, this analysis is based on a special stream which includes
or at least two muons with pT> 15 GeV.
5.2. Candidate selection
Candidate particles are tracks reconstructed in the MS which are required to be matched to the object passing the muon trig-ger, and to originate within tolerances from the primary inter-action point. They must also be within the acceptance region |η| < 2.0, have a pT > 20 GeV, and leave a high-quality track in
the ID. However, because of potential pixel readout saturation, there is no requirement that a candidate particle has pixel infor-mation. The pTmeasured by the muon system is smaller than
the pT measured in the ID due to energy loss in the
calorime-ters, and the pTin the ID is used for candidate selection. In the
track candidate selection, the measurement of the ionisation en-ergy loss in the calorimeter system was not used. However, the calorimeter energy loss was validated for use as an independent cross-check in case of an observation of candidates above the expected background.
An initial preselection of highly ionising candidates is based on the pixel dE/dx significance and the TRT high-threshold fraction fHT. As seen in Fig. 3, the pixel dE/dx significance
is a powerful discriminator for particles with |q|= 2e. The sig-nal region is defined by candidates with a significance greater than 10. For higher values of |q|, the pixel readout saturates and the dE/dx signal is no longer reliable. Therefore, to search for particles with |q| > 2e, the TRT fHT (see Fig. 4) is used as a discriminating variable instead. The signal region is defined by requiring the fHTto be above 0.4. This preselection using the pixel dE/dx or the fHTreduces the background contribution by almost three orders of magnitude for both |q|= 2e and |q| > 2e.
S(Pixel dE/dx) -10 0 10 20 30 40 50 60 1/N dN/dS(Pixel dE/dx) 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2 0.22 -µ + µ → Z
Mass 200 GeV, |q|=2e Mass 400 GeV, |q|=2e Mass 600 GeV, |q|=2e
ATLAS Simulation
Figure 3: Normalised distribution of S (pixel dE/dx) for simulated muons and multi-charged particles. Distributions are shown for the signal sample for |q|= 2e, for masses of 200, 400 and 600 GeV. The structure at a significance of -5 is from pixel read-out saturation.
In the final step of the search, the MDT dE/dx significance, S(MDT dE/dx), and the TRT dE/dx significance, S (TRT
this information. The pTrequirements on muons given here are imposed for the preparation of this stream and are not optimised for the current analysis.
HT f 0 0.2 0.4 0.6 0.8 1 HT 1/N dN/df 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 -µ + µ → Z
Mass 200 GeV, |q|=2e Mass 200 GeV, |q|=4e Mass 200 GeV, |q|=6e
ATLAS Simulation
Figure 4: Normalised distribution of fHT for simulated muons and multi-charged particles. Distributions are shown for the signal samples for |q|= 2e, 4e, and 6e for a mass of 200 GeV.
dE/dx), are used as discriminating variables to separate the sig-nal and background. These variables are shown for real data and simulated signal events in Fig. 5 (6) for candidates preselected as |q| = 2e (|q| > 2e). Only the signal sample for a mass of 200 GeV is shown as there is very little change in the selection variables for different masses. As seen, the detector signatures are different for the two preselected samples, and thus the final signal regions are chosen differently. They are defined in Table 1. The selection was optimised using only simulated samples and data control samples without examining the signal region in the data.
Table 1: The final signal regions for the two preselections.
S(MDT dE/dx) S(TRT dE/dx)
|q|= 2e > 3 > 4
|q|> 2e > 4 > 5
6. Background estimation
The background contribution to the signal region is estimated using an ABCD method. In this method, the regions A,B,C and D are defined by dividing the plane of the uncorrelated TRT and MDT dE/dx significances using the final selection cuts, as seen in Figs. 5 and 6. The region D is defined as the signal region, with regions A, B and C as control regions for the background. The expected number of candidates from background in the re-gion D, ND
data, is estimated from the numbers of observed data
candidates in regions A, B and C (NdataA,B,C):
NdataD = N B data× N C data NA data . (2)
Table 2 gives the number of candidates in A, B and C, as well as the observed number of candidates in the signal region D
S(TRT dE/dx) -10 -5 0 5 10 15 20 25 30 S (M D T d E /d x ) -10 -5 0 5 10 15 20 25 30 ATLAS -1 L dt = 4.4 fb
∫
=7 TeV s DataMass = 200 GeV, |q|=2e
A B
C D
Figure 5: The plane of TRT and MDT dE/dx significances after the |q|= 2e selection. The distributions of the 2011 data and the signal sample (here for a mass of 200 GeV) are shown. The regions labelled A, B and C are control regions used to estimate the background expected in the signal region D.
S(TRT dE/dx) -10 -5 0 5 10 15 20 25 30 S (M D T d E /d x ) -10 -5 0 5 10 15 20 25 30 ATLAS -1 L dt = 4.4 fb
∫
s=7 TeV DataMass = 200 GeV, |q|=4e
A B
C D
Figure 6: The plane of TRT and MDT dE/dx significances after the |q| > 2e selection. The distributions of the 2011 data and the signal sample (here for a mass of 200 GeV and |q|= 4e) are shown. The regions labelled A, B and C are control regions used to estimate the background expected in the signal region D.
after the final selection. These results are compared to the ex-pected number of background candidates of 0.41±0.08 for the |q|= 2e selection and 1.37±0.46 for the |q| > 2e selection. The uncertainties are statistical. The systematic uncertainty on the background estimation is discussed in Section 8.1.
7. Signal selection efficiency The signal cross section is given by
σ = N
rec data
2 × L × , (3)
where L is the integrated luminosity of the analysed data, Nrec data
the number of candidate particles in data above the expected background and the factor of 2 is the number of particles per event in the DY model. The efficiency includes trigger, re-construction and selection efficiencies. The efficiency is the
Table 2: The observed candidate yields in data for an integrated luminosity of 4.4 fb−1. The last column shows the expected background in the signal region D with statistical uncertainty.
A B C D Dexp.
|q|= 2e 8543 92 38 0 0.41±0.08 |q|> 2e 4940 754 9 0 1.37±0.46
number of all multi-charged particles that satisfy the selection criteria divided by the number of all simulated multi-charged particles.
The efficiency to find a multi-charged particle is given in Ta-ble 3 for each signal sample. Several factors contribute to the overall low efficiency and its dependencies on mass and charge. The |η| < 2.0 selection and the requirement to reach the MS with a β which fits the timing window for the trigger are the primary causes of the reduction in efficiency. For the simu-lated signal samples, this timing requirement generally implies a momentum requirement stricter than the explicit pTselection.
The implied selection can be as high as approximately pT/q >
120 GeV. The charge dependence of the efficiency results from higher ionisation and the higher effective single muon pT
selec-tion, which are augmented by the factors q2and q respectively. The mass dependence has two competing factors: at low mass there are more candidates above |η|= 2.0, while at high mass the β spectrum is softer.
Table 3: The efficiencies to select a signal candidate (in %) for the DY produc-tion model. Mass Efficiencies [%] [GeV] |q|= 2e |q| = 3e |q| = 4e |q| = 5e |q| = 6e 50 4.3 2.0 0.3 0.03 0.003 100 8.6 5.5 2.3 0.4 0.07 200 12.6 9.2 4.6 1.8 0.5 300 12.6 9.9 5.8 2.5 0.8 400 10.9 9.0 5.6 2.9 1.0 500 9.9 8.5 5.3 2.9 1.3 600 7.8 6.8 4.6 2.3 1.1 8. Systematic uncertainties
The systematic uncertainties on the background estimate and on the signal efficiency are determined by varying the selection cuts within the uncertainty on each selection variable.
8.1. Background estimation uncertainty
The background estimate in the signal region, D, relies on the fact that the S (TRT dE/dx) and the S (MDT dE/dx) are uncorrelated. To estimate potential influences of signal contamination close to the region boundaries and remaining correlations in the tails of the distributions, the ABCD regions are varied. For this estimate, the signal region D is maintained, but regions A, B and C are redefined by excluding the region
close to the default cut from the background estimation. This ensures a higher background purity. This test is performed for many different definitions of the control regions and leads to an uncertainty of 5% on the estimated background contribution in the signal region.
8.2. Trigger efficiency uncertainty
The uncertainty on the trigger efficiency has two sources: the standard uncertainty on the trigger efficiency of 1% as de-termined by ATLAS muon performance studies [31] and a β-dependent trigger uncertainty. The size of the β-β-dependent part is dominated by the uncertainty on the timing correction of the RPC trigger efficiency (trigger for |η| < 1.05). This correction is varied by ±50% to account for the large dependence of the efficiency on the trigger timing. The relative difference of the trigger efficiencies between the nominal and the varied correc-tion depends on the mass and charge of the benchmark samples, and ranges from less than 1% for |q|= 6e, m = 50 GeV to 24% for |q|= 5e, m = 600 GeV. The timing in the TGC (trigger for |η| ≥ 1.05) for data and simulation is in good agreement, and the systematic uncertainty for the TGC timing correction is negligi-ble. The systematic uncertainty on whether a candidate particle would reach the MS in the timing window for the trigger se-lection also depends on the simulation of energy losses in the calorimeters and the material description of the detector. In a study using muons from Z → µµ events in data and simulation, the energy losses were shown to be in excellent agreement. The energy-loss difference between data and simulation is less than 5%. A cross-check that varies the amount of material by ±10% has a negligible effect on the total systematic uncertainty. 8.3. Uncertainties due to selection
The uncertainties on the selection efficiency arise from the uncertainties on each selection variable used. The following variations of the nominal cuts are studied: pT by ±3%, S (pixel
dE/dx) by ±5%, TRT HT fraction by ±20%, S (TRT dE/dx) by ±5% and S (MDT dE/dx) by −5% and +50%. For the pT
cut this corresponds to the resolution of the track pT
measure-ments. The variation of 20% of the TRT HT fraction arises from the pile-up dependence of this variable. For the pixel and the TRT dE/dx significances, 5% corresponds to the observed agreement of the mean and width of these distributions in the Z → µµ events in data and simulation. This is also applied to the lower variation of S (MDT dE/dx). Here, a relative shift between simulation and data is observed. The magnitude and direction of this shift suggest a variation of S (MDT dE/dx) by 50% in the positive direction. While this would have been im-portant for a potential signal interpretation, it has only a small effect on the limit setting. For all other variables the variations have no observable effect in any of the signal samples. The total systematic uncertainties on the efficiency arising from these cut variations range up to 2.1%.
8.4. Summary of systematic uncertainties
In Table 4 the quadratic sums of all the systematic uncertain-ties considered above are summarised for the different signal
samples. The two main uncertainties are the uncertainty on the trigger efficiency and the uncertainty due to the small number of Monte Carlo events. The latter makes a significant contri-bution for some of the high-charge and low-mass samples. The 50 GeV samples were produced with a selection at the generator level requiring pT/q > 15 GeV in order to decrease the
statisti-cal uncertainty. The systematic uncertainties vary between 6% and 28% in total.
Table 4: Summary of relative systematic uncertainties on the expected num-ber of candidates derived from the uncertainties on the background estimation, trigger efficiency, Monte Carlo statistics and due to selection cuts.
Mass quadratic sum of systematic uncertainties [%] [GeV] |q|= 2e |q| = 3e |q| = 4e |q| = 5e |q| = 6e 50 8 6 6 10 19 100 10 9 7 12 28 200 13 12 10 9 12 300 14 15 15 12 11 400 17 17 18 18 13 500 18 18 19 21 18 600 22 22 23 25 24
The uncertainty on the integrated luminosity is estimated to be 3.9% from Van der Meer scans [32, 33] and is not included in Table 4.
9. Results
No signal candidates are found for either the |q|= 2e or the |q|> 2e selected sample. The results are consistent with the ex-pectation of 0.41±0.08±0.02 and 1.37±0.46±0.07 background candidates, respectively. From these numbers the expected and observed limits are computed using pseudo-experiments. For the total cross-section limit, the systematic uncertainties on e ffi-ciency and the luminosity are taken into account in the pseudo-experiments. For every benchmark point, 100,000 pseudo-experiments are used. The measurement excludes DY model pair-production over wide ranges of tested masses. Fig. 7 shows the observed 95% confidence level cross-section limits as a function of mass for the five different charges. Due to the low number of expected events, the dominant uncertainty arises from Poisson statistics as reflected in the asymmetric un-certainty bands. The limits range from around 10−2pb for the lower charges to 10−1 pb for |q| = 6e. In addition to the ex-pected and observed limits the predicted cross section is shown for the simplified Drell–Yan model. For the given model the cross-section limits can be transformed into mass exclusion lower limits from 50 GeV to 430, 480, 490, 470 and 420 GeV for charges |q| = 2e, 3e, 4e, 5e and 6e, respectively. Fig. 8 summarises the observed limits.
10. Summary
A search for long-lived, multi-charged particles has been per-formed using an integrated luminosity of 4.4 fb−1of pp
colli-m [GeV] 0 100 200 300 400 500 600 [pb] σ -3 10 -2 10 -1 10 1 10 2 10 |q|=2e ATLAS =7 TeV s -1 L=4.4 fb
∫
m [GeV] 0 100 200 300 400 500 600 [pb] σ -3 10 -2 10 -1 10 1 10 2 10 |q|=3e ATLAS =7 TeV s -1 L=4.4 fb∫
Expected 95 % C.L. σ 1 ± σ 2 ± Observed 95 % C.L. Drell-Yan Model m [GeV] 0 100 200 300 400 500 600 [pb] σ -3 10 -2 10 -1 10 1 10 2 10 |q|=4e ATLAS =7 TeV s -1 L=4.4 fb∫
m [GeV] 0 100 200 300 400 500 600 [pb] σ -3 10 -2 10 -1 10 1 10 2 10 |q|=5e ATLAS =7 TeV s -1 L=4.4 fb∫
m [GeV] 0 100 200 300 400 500 600 [pb] σ -3 10 -2 10 -1 10 1 10 2 10 |q|=6e ATLAS =7 TeV s -1 L=4.4 fb∫
Figure 7: Upper limits on the production cross section of multi-charged highly ionising particles from pair-production as a function of particle mass. The dotted line shows the expected limit with the ±1σ and ±2σ uncertainty bands. The observed limit is compared with the predicted rapidly falling cross section from the DY model. The plots are shown separately for charges from |q|= 2e to |q| = 6e. In the |q| = 2e case, the observed limit lies on top of the expected limit.
m [GeV] 0 100 200 300 400 500 600 [pb] σ -3 10 -2 10 -1 10 1 10 2 10 3 10 ATLAS =7 TeV s -1 L=4.4 fb
∫
Prediction Theory DY |q|=6e DY |q|=5e DY |q|=4e DY |q|=3e DY |q|=2e 95 % CL limit Observed |q|=6e |q|=5e |q|=4e |q|=3e |q|=2eFigure 8: Observed 95% CL cross-section upper limits and theoretical cross sections as functions of the multi-charged particle mass.
sions recorded by the ATLAS detector at the LHC. No candi-dates are found in the 2011 data set, consistent with the back-ground expectation. The results presented here are the first mass limits from ATLAS for charges of 2e to 6e, filling the missing range of charges between the searches for slow singly charged long-lived particles [10] and searches for particles with charges from 6e to 17e [8].
11. 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; Yer-PhI, 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, Colom-bia; MSMT CR, MPO CR and VSC CR, Czech Repub-lic; 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), Ro-mania; 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 King-dom; 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 (Den-mark, 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.
References
[1] M. Fairbairn et al., Stable massive particles at colliders, Phys. Rept. 438 (2007) 1, arXiv:hep-ph/0611040.
[2] J. Schwinger, Magnetic charge and quantum field theory, Phys. Rev. 144 (1966) 1087.
[3] S. Dimopoulos and G. L. Landsberg, Black Holes at the Large Hadron Collider, Phys. Rev. Lett. 87 (2001) 161602, arXiv:hep-ph/0106295. [4] A. Kusenko and M. E. Shaposhnikov, Supersymmetric Q-balls as dark
matter, Phys. Lett. B 418 (1998) 46, arXiv:hep-ph/9709492. [5] SLIM Collaboration, S. Cecchini et al., Results of the Search for Strange
Quark Matter and Q-balls with the SLIM Experiment, Eur. Phys. J. C 57 (2008) 525, arXiv:0805.1797 [hep-ex].
[6] D0 Collaboration, V. M. Abazov et al., Search for Long-Lived Charged Massive Particles with the D0 Detector, Phys. Rev. Lett. 102 (2009) 161802, arXiv:0809.4472 [hep-ex].
[7] CDF Collaboration, T. Aaltonen et al., Search for Long-Lived Massive Charged Particles in 1.96 TeV p¯p Collisions, Phys. Rev. Lett. 103 (2009) 021802, arXiv:0902.1266 [hep-ex].
[8] ATLAS Collaboration, Search for Massive Long-lived Highly Ionising Particles with the ATLAS Detector at the LHC, Phys. Lett. B 698 (2011) 353, arXiv:1102.0459 [hep-ex].
[9] ATLAS Collaboration, Search for stable hadronising squarks and gluinos with the ATLAS experiment at the LHC, Phys. Lett. B 701 (2011) 1, arXiv:1103.1984 [hep-ex].
[10] ATLAS Collaboration, Searches for Heavy Long-Lived Sleptons and R-hadrons with the ATLAS detector in pp collisions at√s= 7 TeV, CERN-PH-EP-2012-236. arXiv:1211.1597 [hep-ex]. [11] CMS Collaboration, Search for Heavy Stable Charged Particles in pp
collisions at√s=7 TeV, JHEP 1103 (2011) 024, arXiv:1101.1645 [hep-ex].
[12] CMS Collaboration, Search for heavy long-lived charged particles in pp collisions at√s=7 TeV, Phys. Lett. B 713 (2012) 408,
arXiv:1205.0272 [hep-ex].
[13] ATLAS Collaboration, Search for magnetic monopoles in√s= 7 TeV pp collisions with the ATLAS detector, Phys. Rev. Lett. 109 (2012) 261803, arXiv:1207.6411 [hep-ex].
[14] M. Y. Khlopov, Physics of Dark Matter in the Light of Dark Atoms, Mod. Phys. Lett. A 26 (2011) 2823, arXiv:1111.2838 [astro-ph.CO]. [15] C. A. Stephan, Almost-Commutative Geometries Beyond the Standard
Model, J. Phys. A 39 (2006) 9657, arXiv:hep-th/0509213. [16] F. Sannino and K. Tuominen, Orientifold theory dynamics and symmetry
breaking, Phys. Rev. D71 (2005) 051901, arXiv:hep-ph/0405209. [17] S. B. Gudnason, C. Kouvaris, and F. Sannino, Towards working
technicolor: Effective theories and dark matter, Phys. Rev. D 73 (2006) 115003, arXiv:hep-ph/0603014.
[18] R. Foadi, M. T. Frandsen, T. A. Ryttov, and F. Sannino, Minimal Walking Technicolor: Set Up for Collider Physics, Phys. Rev. D 76 (2007) 055005, arXiv:hep-ph/0706.1696.
[19] A. Connes, Noncommutative Geometry. Academic Press, London and San Diego, 1994.
[20] A. Sakharov, Interaction of the electron and the positron in pair production, Sov. Phys. Usp 34 (1991) 375. [Zh. Eksp. Teor. Fiz. 18 (1948) 631].
[21] ATLAS Collaboration, The ATLAS Experiment at the CERN Large Hadron Collider, JINST 3 (2008) S08003.
[22] ATLAS Collaboration, Particle Identification Performance of the ATLAS Transition Radiation Tracker, ATLAS-CONF-2011-128.
http://cdsweb.cern.ch/record/1383793.
[23] J. Alwall, M. Herquet, F. Maltoni, O. Mattelaer, and T. Stelzer, MadGraph 5 : Going Beyond, JHEP 1106 (2011) 128, arXiv:hep-ph/1106.0522.
[24] J. Pumplin, D. Stump, J. Huston, H. Lai, P. M. Nadolsky, and W. Tung, New generation of parton distributions with uncertainties from global QCD analysis, JHEP 0207 (2002) 012, arXiv:hep-ph/0201195. [25] T. Sjostrand, S. Mrenna, and P. Skands, PYTHIA 6.4 Physics and
Manual, JHEP 0605 (2006) 026, arXiv:hep-ph/0603175. [26] GEANT4 Collaboration, S. Agostinelli et al., GEANT4: A simulation
toolkit, Nucl. Instrum. Meth. A 506 (2003) 250.
[27] ATLAS Collaboration, The ATLAS Simulation Infrastructure, Eur. Phys. J. C 70 (2010) 823, arXiv:1005.4568 [physics.ins-det]. [28] A. Belyaev, N. D. Christensen, and A. Pukhov, CalcHEP 3.4 for collider
physics within and beyond the Standard Model, arXiv:hep-ph/1207.6082.
[29] H. Bethe, Zur Theorie des Durchgangs schneller Korpuskularstrahlen durch Materie, Ann. Phys. 5 (1930) 325.
[30] ATLAS Collaboration, dE/dx measurement in the ATLAS Pixel Detector and its use for particle identification, ATLAS-CONF-2011-16. http://cdsweb.cern.ch/record/1336519.
[31] ATLAS Collaboration, Performance of the ATLAS muon trigger in 2011, ATLAS-CONF-2012-099.
http://cdsweb.cern.ch/record/1462601.
[32] ATLAS Collaboration, Luminosity Determination in pp Collisions at sqrt(s)=7 TeV Using the ATLAS Detector at the LHC, Eur. Phys. J. C 71 (2011) 1630, arXiv:1101.2185 [hep-ex].
[33] ATLAS Collaboration, Luminosity Determination in pp Collisions at sqrt(s)= 7 TeV using the ATLAS Detector in 2011,
ATLAS-CONF-2011-116.
The ATLAS Collaboration
G. Aad48, T. Abajyan21, B. Abbott111, J. Abdallah12, S. Abdel Khalek115, A.A. Abdelalim49, O. Abdinov11, R. Aben105, B. Abi112,
M. Abolins88, O.S. AbouZeid158, H. Abramowicz153, H. Abreu136, B.S. Acharya164a,164b,a, L. Adamczyk38, D.L. Adams25,
T.N. Addy56, J. Adelman176, S. Adomeit98, P. Adragna75, T. Adye129, S. Aefsky23, J.A. Aguilar-Saavedra124b,b, M. Agustoni17,
M. Aharrouche81, S.P. Ahlen22, F. Ahles48, A. Ahmad148, M. Ahsan41, G. Aielli133a,133b, T.P.A. Åkesson79, G. Akimoto155,
A.V. Akimov94, M.A. Alam76, J. Albert169, S. Albrand55, M. Aleksa30, I.N. Aleksandrov64, F. Alessandria89a, C. Alexa26a,
G. Alexander153, G. Alexandre49, T. Alexopoulos10, M. Alhroob164a,164c, M. Aliev16, G. Alimonti89a, J. Alison120,
B.M.M. Allbrooke18, P.P. Allport73, S.E. Allwood-Spiers53, J. Almond82, A. Aloisio102a,102b, R. Alon172, A. Alonso36, F. Alonso70,
A. Altheimer35, B. Alvarez Gonzalez88, M.G. Alviggi102a,102b, K. Amako65, C. Amelung23, V.V. Ammosov128,∗,
S.P. Amor Dos Santos124a, A. Amorim124a,c, N. Amram153, C. Anastopoulos30, L.S. Ancu17, N. Andari115, T. Andeen35, C.F. Anders58b, G. Anders58a, K.J. Anderson31, A. Andreazza89a,89b, V. Andrei58a, M-L. Andrieux55, X.S. Anduaga70, S. Angelidakis9, P. Anger44, A. Angerami35, F. Anghinolfi30, A. Anisenkov107, N. Anjos124a, A. Annovi47, A. Antonaki9,
M. Antonelli47, A. Antonov96, J. Antos144b, F. Anulli132a, M. Aoki101, S. Aoun83, L. Aperio Bella5, R. Apolle118,d, G. Arabidze88, I. Aracena143, Y. Arai65, A.T.H. Arce45, S. Arfaoui148, J-F. Arguin93, S. Argyropoulos42, E. Arik19a,∗, M. Arik19a,
A.J. Armbruster87, O. Arnaez81, V. Arnal80, A. Artamonov95, G. Artoni132a,132b, D. Arutinov21, S. Asai155, S. Ask28, B. Åsman146a,146b, D. Asner29, L. Asquith6, K. Assamagan25,e, A. Astbury169, M. Atkinson165, B. Aubert5, E. Auge115,
K. Augsten126, M. Aurousseau145a, G. Avolio30, D. Axen168, G. Azuelos93, f, Y. Azuma155, M.A. Baak30, G. Baccaglioni89a,
C. Bacci134a,134b, A.M. Bach15, H. Bachacou136, K. Bachas154, M. Backes49, M. Backhaus21, J. Backus Mayes143, E. Badescu26a,
P. Bagnaia132a,132b, S. Bahinipati3, Y. Bai33a, D.C. Bailey158, T. Bain35, J.T. Baines129, O.K. Baker176, M.D. Baker25, S. Baker77,
P. Balek127, E. Banas39, P. Banerjee93, Sw. Banerjee173, D. Banfi30, A. Bangert150, V. Bansal169, H.S. Bansil18, L. Barak172,
S.P. Baranov94, A. Barbaro Galtieri15, T. Barber48, E.L. Barberio86, D. Barberis50a,50b, M. Barbero21, D.Y. Bardin64, T. Barillari99,
M. Barisonzi175, T. Barklow143, N. Barlow28, B.M. Barnett129, R.M. Barnett15, A. Baroncelli134a, G. Barone49, A.J. Barr118,
F. Barreiro80, J. Barreiro Guimar˜aes da Costa57, R. Bartoldus143, A.E. Barton71, V. Bartsch149, A. Basye165, R.L. Bates53,
L. Batkova144a, J.R. Batley28, A. Battaglia17, M. Battistin30, F. Bauer136, H.S. Bawa143,g, S. Beale98, T. Beau78,
P.H. Beauchemin161, R. Beccherle50a, P. Bechtle21, H.P. Beck17, K. Becker175, S. Becker98, M. Beckingham138, K.H. Becks175, A.J. Beddall19c, A. Beddall19c, S. Bedikian176, V.A. Bednyakov64, C.P. Bee83, L.J. Beemster105, M. Begel25, S. Behar Harpaz152, P.K. Behera62, M. Beimforde99, C. Belanger-Champagne85, P.J. Bell49, W.H. Bell49, G. Bella153, L. Bellagamba20a, M. Bellomo30, A. Belloni57, O. Beloborodova107,h, K. Belotskiy96, O. Beltramello30, O. Benary153, D. Benchekroun135a, K. Bendtz146a,146b, N. Benekos165, Y. Benhammou153, E. Benhar Noccioli49, J.A. Benitez Garcia159b, D.P. Benjamin45, M. Benoit115, J.R. Bensinger23, K. Benslama130, S. Bentvelsen105, D. Berge30, E. Bergeaas Kuutmann42, N. Berger5, F. Berghaus169, E. Berglund105, J. Beringer15, P. Bernat77, R. Bernhard48, C. Bernius25, T. Berry76, C. Bertella83, A. Bertin20a,20b, F. Bertolucci122a,122b, M.I. Besana89a,89b,
G.J. Besjes104, N. Besson136, S. Bethke99, W. Bhimji46, R.M. Bianchi30, L. Bianchini23, M. Bianco72a,72b, O. Biebel98,
S.P. Bieniek77, K. Bierwagen54, J. Biesiada15, M. Biglietti134a, H. Bilokon47, M. Bindi20a,20b, S. Binet115, A. Bingul19c,
C. Bini132a,132b, C. Biscarat178, B. Bittner99, C.W. Black150, K.M. Black22, R.E. Blair6, J.-B. Blanchard136, T. Blazek144a,
I. Bloch42, C. Blocker23, J. Blocki39, A. Blondel49, W. Blum81, U. Blumenschein54, G.J. Bobbink105, V.S. Bobrovnikov107,
S.S. Bocchetta79, A. Bocci45, C.R. Boddy118, M. Boehler48, J. Boek175, T.T. Boek175, N. Boelaert36, J.A. Bogaerts30,
A. Bogdanchikov107, A. Bogouch90,∗, C. Bohm146a, J. Bohm125, V. Boisvert76, T. Bold38, V. Boldea26a, N.M. Bolnet136,
M. Bomben78, M. Bona75, M. Boonekamp136, S. Bordoni78, C. Borer17, A. Borisov128, G. Borissov71, I. Borjanovic13a, M. Borri82,
S. Borroni87, J. Bortfeldt98, V. Bortolotto134a,134b, K. Bos105, D. Boscherini20a, M. Bosman12, H. Boterenbrood105, J. Bouchami93,
J. Boudreau123, E.V. Bouhova-Thacker71, D. Boumediene34, C. Bourdarios115, N. Bousson83, A. Boveia31, J. Boyd30, I.R. Boyko64, I. Bozovic-Jelisavcic13b, J. Bracinik18, P. Branchini134a, A. Brandt8, G. Brandt118, O. Brandt54, U. Bratzler156, B. Brau84, J.E. Brau114, H.M. Braun175,∗, S.F. Brazzale164a,164c, B. Brelier158, J. Bremer30, K. Brendlinger120, R. Brenner166, S. Bressler172, D. Britton53, F.M. Brochu28, I. Brock21, R. Brock88, F. Broggi89a, C. Bromberg88, J. Bronner99, G. Brooijmans35, T. Brooks76, W.K. Brooks32b, G. Brown82, P.A. Bruckman de Renstrom39, D. Bruncko144b, R. Bruneliere48, S. Brunet60, A. Bruni20a, G. Bruni20a, M. Bruschi20a, L. Bryngemark79, T. Buanes14, Q. Buat55, F. Bucci49, J. Buchanan118, P. Buchholz141, R.M. Buckingham118, A.G. Buckley46, S.I. Buda26a, I.A. Budagov64, B. Budick108, L. Bugge117, O. Bulekov96, A.C. Bundock73,
M. Bunse43, T. Buran117, H. Burckhart30, S. Burdin73, T. Burgess14, S. Burke129, E. Busato34, V. B¨uscher81, P. Bussey53,
C.P. Buszello166, B. Butler143, J.M. Butler22, C.M. Buttar53, J.M. Butterworth77, W. Buttinger28, M. Byszewski30, S. Cabrera
Urb´an167, D. Caforio20a,20b, O. Cakir4a, P. Calafiura15, G. Calderini78, P. Calfayan98, R. Calkins106, L.P. Caloba24a, R. Caloi132a,132b,
D. Calvet34, S. Calvet34, R. Camacho Toro34, P. Camarri133a,133b, D. Cameron117, L.M. Caminada15, R. Caminal Armadans12,
S. Campana30, M. Campanelli77, V. Canale102a,102b, F. Canelli31, A. Canepa159a, J. Cantero80, R. Cantrill76, L. Capasso102a,102b,
M.D.M. Capeans Garrido30, I. Caprini26a, M. Caprini26a, D. Capriotti99, M. Capua37a,37b, R. Caputo81, R. Cardarelli133a, T. Carli30,
G. Carlino102a, L. Carminati89a,89b, B. Caron85, S. Caron104, E. Carquin32b, G.D. Carrillo-Montoya145b, A.A. Carter75,
J.R. Carter28, J. Carvalho124a,i, D. Casadei108, M.P. Casado12, M. Cascella122a,122b, C. Caso50a,50b,∗,
A.M. Castaneda Hernandez173, j, E. Castaneda-Miranda173, V. Castillo Gimenez167, N.F. Castro124a, G. Cataldi72a, P. Catastini57, A. Catinaccio30, J.R. Catmore30, A. Cattai30, G. Cattani133a,133b, S. Caughron88, V. Cavaliere165, P. Cavalleri78, D. Cavalli89a,
M. Cavalli-Sforza12, V. Cavasinni122a,122b, F. Ceradini134a,134b, A.S. Cerqueira24b, A. Cerri15, L. Cerrito75, F. Cerutti15, S.A. Cetin19b, A. Chafaq135a, D. Chakraborty106, I. Chalupkova127, K. Chan3, P. Chang165, B. Chapleau85, J.D. Chapman28,
J.W. Chapman87, D.G. Charlton18, V. Chavda82, C.A. Chavez Barajas30, S. Cheatham85, S. Chekanov6, S.V. Chekulaev159a,
G.A. Chelkov64, M.A. Chelstowska104, C. Chen63, H. Chen25, S. Chen33c, X. Chen173, Y. Chen35, Y. Cheng31, A. Cheplakov64,
R. Cherkaoui El Moursli135e, V. Chernyatin25, E. Cheu7, S.L. Cheung158, L. Chevalier136, G. Chiefari102a,102b, L. Chikovani51a,∗,
J.T. Childers30, A. Chilingarov71, G. Chiodini72a, A.S. Chisholm18, R.T. Chislett77, A. Chitan26a, M.V. Chizhov64,
G. Choudalakis31, S. Chouridou137, I.A. Christidi77, A. Christov48, D. Chromek-Burckhart30, M.L. Chu151, J. Chudoba125,
G. Ciapetti132a,132b, A.K. Ciftci4a, R. Ciftci4a, D. Cinca34, V. Cindro74, A. Ciocio15, M. Cirilli87, P. Cirkovic13b, Z.H. Citron172,
M. Citterio89a, M. Ciubancan26a, A. Clark49, P.J. Clark46, R.N. Clarke15, W. Cleland123, J.C. Clemens83, B. Clement55,
C. Clement146a,146b, Y. Coadou83, M. Cobal164a,164c, A. Coccaro138, J. Cochran63, L. Coffey23, J.G. Cogan143, J. Coggeshall165,
J. Colas5, S. Cole106, A.P. Colijn105, N.J. Collins18, C. Collins-Tooth53, J. Collot55, T. Colombo119a,119b, G. Colon84,
G. Compostella99, P. Conde Mui˜no124a, E. Coniavitis166, M.C. Conidi12, S.M. Consonni89a,89b, V. Consorti48, S. Constantinescu26a, C. Conta119a,119b, G. Conti57, F. Conventi102a,k, M. Cooke15, B.D. Cooper77, A.M. Cooper-Sarkar118, K. Copic15, T. Cornelissen175, M. Corradi20a, F. Corriveau85,l, A. Cortes-Gonzalez165, G. Cortiana99, G. Costa89a, M.J. Costa167, D. Costanzo139, D. Cˆot´e30, L. Courneyea169, G. Cowan76, B.E. Cox82, K. Cranmer108, S. Cr´ep´e-Renaudin55, F. Crescioli78, M. Cristinziani21,
G. Crosetti37a,37b, C.-M. Cuciuc26a, C. Cuenca Almenar176, T. Cuhadar Donszelmann139, J. Cummings176, M. Curatolo47, C.J. Curtis18, C. Cuthbert150, P. Cwetanski60, H. Czirr141, P. Czodrowski44, Z. Czyczula176, S. D’Auria53, M. D’Onofrio73,
A. D’Orazio132a,132b, M.J. Da Cunha Sargedas De Sousa124a, C. Da Via82, W. Dabrowski38, A. Dafinca118, T. Dai87, F. Dallaire93,
C. Dallapiccola84, M. Dam36, M. Dameri50a,50b, D.S. Damiani137, H.O. Danielsson30, V. Dao49, G. Darbo50a, G.L. Darlea26b,
J.A. Dassoulas42, W. Davey21, T. Davidek127, N. Davidson86, R. Davidson71, E. Davies118,d, M. Davies93, O. Davignon78,
A.R. Davison77, Y. Davygora58a, E. Dawe142, I. Dawson139, R.K. Daya-Ishmukhametova23, K. De8, R. de Asmundis102a,
S. De Castro20a,20b, S. De Cecco78, J. de Graat98, N. De Groot104, P. de Jong105, C. De La Taille115, H. De la Torre80,
F. De Lorenzi63, L. de Mora71, L. De Nooij105, D. De Pedis132a, A. De Salvo132a, U. De Sanctis164a,164c, A. De Santo149,
J.B. De Vivie De Regie115, G. De Zorzi132a,132b, W.J. Dearnaley71, R. Debbe25, C. Debenedetti46, B. Dechenaux55,
D.V. Dedovich64, J. Degenhardt120, J. Del Peso80, T. Del Prete122a,122b, T. Delemontex55, M. Deliyergiyev74, A. Dell’Acqua30,
L. Dell’Asta22, M. Della Pietra102a,k, D. della Volpe102a,102b, M. Delmastro5, P.A. Delsart55, C. Deluca105, S. Demers176, M. Demichev64, B. Demirkoz12,m, S.P. Denisov128, D. Derendarz39, J.E. Derkaoui135d, F. Derue78, P. Dervan73, K. Desch21, E. Devetak148, P.O. Deviveiros105, A. Dewhurst129, B. DeWilde148, S. Dhaliwal105, R. Dhullipudi25,n, A. Di Ciaccio133a,133b, L. Di Ciaccio5, C. Di Donato102a,102b, A. Di Girolamo30, B. Di Girolamo30, S. Di Luise134a,134b, A. Di Mattia152, B. Di Micco30, R. Di Nardo47, A. Di Simone133a,133b, R. Di Sipio20a,20b, M.A. Diaz32a, E.B. Diehl87, J. Dietrich42, T.A. Dietzsch58a, S. Diglio86, K. Dindar Yagci40, J. Dingfelder21, F. Dinut26a, C. Dionisi132a,132b, P. Dita26a, S. Dita26a, F. Dittus30, F. Djama83, T. Djobava51b, M.A.B. do Vale24c, A. Do Valle Wemans124a,o, T.K.O. Doan5, M. Dobbs85, D. Dobos30, E. Dobson30,p, J. Dodd35, C. Doglioni49,
T. Doherty53, T. Dohmae155, Y. Doi65,∗, J. Dolejsi127, Z. Dolezal127, B.A. Dolgoshein96,∗, M. Donadelli24d, J. Donini34, J. Dopke30,
A. Doria102a, A. Dos Anjos173, A. Dotti122a,122b, M.T. Dova70, A.D. Doxiadis105, A.T. Doyle53, N. Dressnandt120, M. Dris10,
J. Dubbert99, S. Dube15, E. Duchovni172, G. Duckeck98, D. Duda175, A. Dudarev30, F. Dudziak63, I.P. Duerdoth82, L. Duflot115,
M-A. Dufour85, L. Duguid76, M. D¨uhrssen30, M. Dunford58a, H. Duran Yildiz4a, M. D¨uren52, R. Duxfield139, M. Dwuznik38,
W.L. Ebenstein45, J. Ebke98, S. Eckweiler81, K. Edmonds81, W. Edson2, C.A. Edwards76, N.C. Edwards53, W. Ehrenfeld42,
T. Eifert143, G. Eigen14, K. Einsweiler15, E. Eisenhandler75, T. Ekelof166, M. El Kacimi135c, M. Ellert166, S. Elles5, F. Ellinghaus81,
K. Ellis75, N. Ellis30, J. Elmsheuser98, M. Elsing30, D. Emeliyanov129, R. Engelmann148, A. Engl98, B. Epp61, J. Erdmann176,
A. Ereditato17, D. Eriksson146a, J. Ernst2, M. Ernst25, J. Ernwein136, D. Errede165, S. Errede165, E. Ertel81, M. Escalier115,
H. Esch43, C. Escobar123, X. Espinal Curull12, B. Esposito47, F. Etienne83, A.I. Etienvre136, E. Etzion153, D. Evangelakou54, H. Evans60, L. Fabbri20a,20b, C. Fabre30, R.M. Fakhrutdinov128, S. Falciano132a, Y. Fang33a, M. Fanti89a,89b, A. Farbin8, A. Farilla134a, J. Farley148, T. Farooque158, S. Farrell163, S.M. Farrington170, P. Farthouat30, F. Fassi167, P. Fassnacht30, D. Fassouliotis9, B. Fatholahzadeh158, A. Favareto89a,89b, L. Fayard115, P. Federic144a, O.L. Fedin121, W. Fedorko88, M. Fehling-Kaschek48, L. Feligioni83, C. Feng33d, E.J. Feng6, A.B. Fenyuk128, J. Ferencei144b, W. Fernando6, S. Ferrag53, J. Ferrando53, V. Ferrara42, A. Ferrari166, P. Ferrari105, R. Ferrari119a, D.E. Ferreira de Lima53, A. Ferrer167, D. Ferrere49, C. Ferretti87, A. Ferretto Parodi50a,50b, M. Fiascaris31, F. Fiedler81, A. Filipˇciˇc74, F. Filthaut104, M. Fincke-Keeler169,
M.C.N. Fiolhais124a,i, L. Fiorini167, A. Firan40, G. Fischer42, M.J. Fisher109, M. Flechl48, I. Fleck141, J. Fleckner81,
P. Fleischmann174, S. Fleischmann175, T. Flick175, A. Floderus79, L.R. Flores Castillo173, A.C. Florez Bustos159b,
M.J. Flowerdew99, T. Fonseca Martin17, A. Formica136, A. Forti82, D. Fortin159a, D. Fournier115, A.J. Fowler45, H. Fox71,
P. Francavilla12, M. Franchini20a,20b, S. Franchino119a,119b, D. Francis30, T. Frank172, M. Franklin57, S. Franz30,
M. Fraternali119a,119b, S. Fratina120, S.T. French28, C. Friedrich42, F. Friedrich44, D. Froidevaux30, J.A. Frost28, C. Fukunaga156,
E. Fullana Torregrosa127, B.G. Fulsom143, J. Fuster167, C. Gabaldon30, O. Gabizon172, T. Gadfort25, S. Gadomski49,
G. Gagliardi50a,50b, P. Gagnon60, C. Galea98, B. Galhardo124a, E.J. Gallas118, V. Gallo17, B.J. Gallop129, P. Gallus125, K.K. Gan109,
Y.S. Gao143,g, A. Gaponenko15, F. Garberson176, C. Garc´ıa167, J.E. Garc´ıa Navarro167, M. Garcia-Sciveres15, R.W. Gardner31,
N. Garelli30, V. Garonne30, C. Gatti47, G. Gaudio119a, B. Gaur141, L. Gauthier136, P. Gauzzi132a,132b, I.L. Gavrilenko94, C. Gay168, G. Gaycken21, E.N. Gazis10, P. Ge33d,q, Z. Gecse168, C.N.P. Gee129, D.A.A. Geerts105, Ch. Geich-Gimbel21, K. Gellerstedt146a,146b,
C. Gemme50a, A. Gemmell53, M.H. Genest55, S. Gentile132a,132b, M. George54, S. George76, D. Gerbaudo12, P. Gerlach175, A. Gershon153, C. Geweniger58a, H. Ghazlane135b, N. Ghodbane34, B. Giacobbe20a, S. Giagu132a,132b, V. Giangiobbe12,
F. Gianotti30, B. Gibbard25, A. Gibson158, S.M. Gibson30, M. Gilchriese15, D. Gillberg29, A.R. Gillman129, D.M. Gingrich3, f,
J. Ginzburg153, N. Giokaris9, M.P. Giordani164c, R. Giordano102a,102b, F.M. Giorgi16, P. Giovannini99, P.F. Giraud136, D. Giugni89a,
M. Giunta93, B.K. Gjelsten117, L.K. Gladilin97, C. Glasman80, J. Glatzer21, A. Glazov42, K.W. Glitza175, G.L. Glonti64,
J.R. Goddard75, J. Godfrey142, J. Godlewski30, M. Goebel42, C. Goeringer81, S. Goldfarb87, T. Golling176, D. Golubkov128,
A. Gomes124a,c, L.S. Gomez Fajardo42, R. Gonc¸alo76, J. Goncalves Pinto Firmino Da Costa42, L. Gonella21, S. Gonz´alez de la
Hoz167, G. Gonzalez Parra12, M.L. Gonzalez Silva27, S. Gonzalez-Sevilla49, J.J. Goodson148, L. Goossens30, T. G¨opfert44,
P.A. Gorbounov95, H.A. Gordon25, I. Gorelov103, G. Gorfine175, B. Gorini30, E. Gorini72a,72b, A. Goriˇsek74, E. Gornicki39,
A.T. Goshaw6, M. Gosselink105, C. G¨ossling43, M.I. Gostkin64, I. Gough Eschrich163, M. Gouighri135a, D. Goujdami135c,
M.P. Goulette49, A.G. Goussiou138, C. Goy5, S. Gozpinar23, I. Grabowska-Bold38, P. Grafstr¨om20a,20b, K-J. Grahn42, E. Gramstad117, F. Grancagnolo72a, S. Grancagnolo16, V. Grassi148, V. Gratchev121, N. Grau35, H.M. Gray30, J.A. Gray148, E. Graziani134a, O.G. Grebenyuk121, T. Greenshaw73, Z.D. Greenwood25,n, K. Gregersen36, I.M. Gregor42, P. Grenier143, J. Griffiths8, N. Grigalashvili64, A.A. Grillo137, S. Grinstein12, Ph. Gris34, Y.V. Grishkevich97, J.-F. Grivaz115, A. Grohsjean42, E. Gross172, J. Grosse-Knetter54, J. Groth-Jensen172, K. Grybel141, D. Guest176, C. Guicheney34, E. Guido50a,50b, S. Guindon54, U. Gul53, J. Gunther125, B. Guo158, J. Guo35, P. Gutierrez111, N. Guttman153, O. Gutzwiller173, C. Guyot136, C. Gwenlan118, C.B. Gwilliam73, A. Haas108, S. Haas30, C. Haber15, H.K. Hadavand8, D.R. Hadley18, P. Haefner21, F. Hahn30, Z. Hajduk39,
H. Hakobyan177, D. Hall118, K. Hamacher175, P. Hamal113, K. Hamano86, M. Hamer54, A. Hamilton145b,r, S. Hamilton161,
L. Han33b, K. Hanagaki116, K. Hanawa160, M. Hance15, C. Handel81, P. Hanke58a, J.R. Hansen36, J.B. Hansen36, J.D. Hansen36,
P.H. Hansen36, P. Hansson143, K. Hara160, T. Harenberg175, S. Harkusha90, D. Harper87, R.D. Harrington46, O.M. Harris138,
J. Hartert48, F. Hartjes105, T. Haruyama65, A. Harvey56, S. Hasegawa101, Y. Hasegawa140, S. Hassani136, S. Haug17,
M. Hauschild30, R. Hauser88, M. Havranek21, C.M. Hawkes18, R.J. Hawkings30, A.D. Hawkins79, T. Hayakawa66, T. Hayashi160,
D. Hayden76, C.P. Hays118, H.S. Hayward73, S.J. Haywood129, S.J. Head18, V. Hedberg79, L. Heelan8, S. Heim120,
B. Heinemann15, S. Heisterkamp36, L. Helary22, C. Heller98, M. Heller30, S. Hellman146a,146b, D. Hellmich21, C. Helsens12,
R.C.W. Henderson71, M. Henke58a, A. Henrichs176, A.M. Henriques Correia30, S. Henrot-Versille115, C. Hensel54,
C.M. Hernandez8, Y. Hern´andez Jim´enez167, R. Herrberg16, G. Herten48, R. Hertenberger98, L. Hervas30, G.G. Hesketh77, N.P. Hessey105, E. Hig´on-Rodriguez167, J.C. Hill28, K.H. Hiller42, S. Hillert21, S.J. Hillier18, I. Hinchliffe15, E. Hines120, M. Hirose116, F. Hirsch43, D. Hirschbuehl175, J. Hobbs148, N. Hod153, M.C. Hodgkinson139, P. Hodgson139, A. Hoecker30, M.R. Hoeferkamp103, J. Hoffman40, D. Hoffmann83, M. Hohlfeld81, M. Holder141, S.O. Holmgren146a, T. Holy126,
J.L. Holzbauer88, T.M. Hong120, L. Hooft van Huysduynen108, S. Horner48, J-Y. Hostachy55, S. Hou151, A. Hoummada135a, J. Howard118, J. Howarth82, I. Hristova16, J. Hrivnac115, T. Hryn’ova5, P.J. Hsu81, S.-C. Hsu138, D. Hu35, Z. Hubacek30, F. Hubaut83, F. Huegging21, A. Huettmann42, T.B. Huffman118, E.W. Hughes35, G. Hughes71, M. Huhtinen30, M. Hurwitz15,
N. Huseynov64,s, J. Huston88, J. Huth57, G. Iacobucci49, G. Iakovidis10, M. Ibbotson82, I. Ibragimov141, L. Iconomidou-Fayard115,
J. Idarraga115, P. Iengo102a, O. Igonkina105, Y. Ikegami65, M. Ikeno65, D. Iliadis154, N. Ilic158, T. Ince99, P. Ioannou9, M. Iodice134a,
K. Iordanidou9, V. Ippolito132a,132b, A. Irles Quiles167, C. Isaksson166, M. Ishino67, M. Ishitsuka157, R. Ishmukhametov109,
C. Issever118, S. Istin19a, A.V. Ivashin128, W. Iwanski39, H. Iwasaki65, J.M. Izen41, V. Izzo102a, B. Jackson120, J.N. Jackson73,
P. Jackson1, M.R. Jaekel30, V. Jain2, K. Jakobs48, S. Jakobsen36, T. Jakoubek125, J. Jakubek126, D.O. Jamin151, D.K. Jana111,
E. Jansen77, H. Jansen30, J. Janssen21, A. Jantsch99, M. Janus48, R.C. Jared173, G. Jarlskog79, L. Jeanty57, G.-Y. Jeng150,
I. Jen-La Plante31, D. Jennens86, P. Jenni30, P. Jeˇz36, S. J´ez´equel5, M.K. Jha20a, H. Ji173, W. Ji81, J. Jia148, Y. Jiang33b,
M. Jimenez Belenguer42, S. Jin33a, O. Jinnouchi157, M.D. Joergensen36, D. Joffe40, M. Johansen146a,146b, K.E. Johansson146a,
P. Johansson139, S. Johnert42, K.A. Johns7, K. Jon-And146a,146b, G. Jones170, R.W.L. Jones71, T.J. Jones73, C. Joram30, P.M. Jorge124a, K.D. Joshi82, J. Jovicevic147, T. Jovin13b, X. Ju173, C.A. Jung43, R.M. Jungst30, V. Juranek125, P. Jussel61, A. Juste Rozas12, S. Kabana17, M. Kaci167, A. Kaczmarska39, P. Kadlecik36, M. Kado115, H. Kagan109, M. Kagan57, E. Kajomovitz152, S. Kalinin175, L.V. Kalinovskaya64, S. Kama40, N. Kanaya155, M. Kaneda30, S. Kaneti28, T. Kanno157, V.A. Kantserov96, J. Kanzaki65, B. Kaplan108, A. Kapliy31, D. Kar53, M. Karagounis21, K. Karakostas10, M. Karnevskiy58b, V. Kartvelishvili71, A.N. Karyukhin128, L. Kashif173, G. Kasieczka58b, R.D. Kass109, A. Kastanas14, Y. Kataoka155, J. Katzy42, V. Kaushik7, K. Kawagoe69, T. Kawamoto155, G. Kawamura81, M.S. Kayl105, S. Kazama155, V.F. Kazanin107, M.Y. Kazarinov64,
R. Keeler169, P.T. Keener120, R. Kehoe40, M. Keil54, G.D. Kekelidze64, J.S. Keller138, M. Kenyon53, O. Kepka125, N. Kerschen30,
B.P. Kerˇsevan74, S. Kersten175, K. Kessoku155, J. Keung158, F. Khalil-zada11, H. Khandanyan146a,146b, A. Khanov112,
D. Kharchenko64, A. Khodinov96, A. Khomich58a, T.J. Khoo28, G. Khoriauli21, A. Khoroshilov175, V. Khovanskiy95,
E. Khramov64, J. Khubua51b, H. Kim146a,146b, S.H. Kim160, N. Kimura171, O. Kind16, B.T. King73, M. King66, R.S.B. King118,
J. Kirk129, A.E. Kiryunin99, T. Kishimoto66, D. Kisielewska38, T. Kitamura66, T. Kittelmann123, K. Kiuchi160, E. Kladiva144b,
M. Klein73, U. Klein73, K. Kleinknecht81, M. Klemetti85, A. Klier172, P. Klimek146a,146b, A. Klimentov25, R. Klingenberg43,
J.A. Klinger82, E.B. Klinkby36, T. Klioutchnikova30, P.F. Klok104, S. Klous105, E.-E. Kluge58a, T. Kluge73, P. Kluit105, S. Kluth99,
E. Kneringer61, E.B.F.G. Knoops83, A. Knue54, B.R. Ko45, T. Kobayashi155, M. Kobel44, M. Kocian143, P. Kodys127, S. Koenig81,
F. Koetsveld104, P. Koevesarki21, T. Koffas29, E. Koffeman105, L.A. Kogan118, S. Kohlmann175, F. Kohn54, Z. Kohout126, T. Kohriki65, T. Koi143, G.M. Kolachev107,∗, H. Kolanoski16, V. Kolesnikov64, I. Koletsou89a, J. Koll88, A.A. Komar94,
