Measurement of Dijet Azimuthal Decorrelations in <em>pp</em> Collisions at √s=7 TeV

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Article

Reference

Measurement of Dijet Azimuthal Decorrelations in pp Collisions at

√s=7 TeV

ATLAS Collaboration

ABDELALIM ALY, Ahmed Aly (Collab.), et al.

Abstract

Azimuthal decorrelations between the two central jets with the largest transverse momenta are sensitive to the dynamics of events with multiple jets. We present a measurement of the normalized differential cross section based on the full data set (∫Ldt=36 pb−1) acquired by the ATLAS detector during the 2010 s√=7 TeV proton-proton run of the LHC. The measured distributions include jets with transverse momenta up to 1.3 TeV, probing perturbative QCD in a high-energy regime.

ATLAS Collaboration, ABDELALIM ALY, Ahmed Aly (Collab.), et al . Measurement of Dijet Azimuthal Decorrelations in pp Collisions at √s=7 TeV. Physical Review Letters , 2011, vol.

106, no. 17, p. 172002

DOI : 10.1103/PhysRevLett.106.172002

Available at:

http://archive-ouverte.unige.ch/unige:41427

Disclaimer: layout of this document may differ from the published version.

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Measurement of Dijet Azimuthal Decorrelations in pp Collisions at ffiffiffi p s

¼ 7 TeV

G. Aadet al.* (ATLAS Collaboration)

(Received 14 February 2011; published 29 April 2011)

Azimuthal decorrelations between the two central jets with the largest transverse momenta are sensitive to the dynamics of events with multiple jets. We present a measurement of the normalized differential cross section based on the full data set (R

Ldt¼36 pb¹) acquired by the ATLAS detector during the 2010 ffiffiffi

ps

¼7 TeVproton-proton run of the LHC. The measured distributions include jets with transverse momenta up to 1.3 TeV, probing perturbative QCD in a high-energy regime.

DOI:10.1103/PhysRevLett.106.172002 PACS numbers: 13.85.Ni, 12.38.Bx, 12.38.Qk, 13.87.Ce

The production of events containing high transverse- momentum (p_T) jets is a key signature of quantum chro- modynamic (QCD) interactions between partons in pp collisions at large center-of-mass energies ( ffiffiffi

ps

). The Large Hadron Collider (LHC) opens a window into the dynamics of interactions with high-ffiffiffi p_T jets in a new energy regime of ps

¼7 TeV. QCD predicts the decorrelation in the azimuthal angle between the two most energetic jets,, as a function of the number of partons produced. Events with only two high-p_T jets have small azimuthal decorrelations, , whileis evidence of events with several high-pT jets. QCD also describes the evolution of the shape of the distribution, which narrows with increasing leading jetp_T. Distributions intherefore test perturbative QCD (pQCD) calculations for multiple jet production without requiring the measurement of additional jets.

Furthermore, a detailed understanding of events with large azimuthal decorrelations is important to searches for new physical phenomena with dijet signatures, such as super- symmetric extensions to the standard model [1].

In this Letter, we present a measurement of dijet azimuthal decorrelations with jetpT up to 1.3 TeV as measured by the ATLAS detector, beyond the reach of previous colliders. The differential cross section ð1=Þðd=dÞ is based upon an integrated luminosity R

Ldt¼ ð364Þpb¹ [2]. Thedistribution is normalized by the inclusive dijet cross section, integrated over the same phase space. This construction minimizes experimental and theoretical uncertainties. Previous measurements of from the D0 [3] and CMS [4] Collaborations are extended here to higher jetp_T values.

Jets are reconstructed using the anti-k_t algorithm [5]

(implemented withFASTJET[6]) with radiusR¼0:6, and the jet four-momenta are constructed from a sum over its constituents, treating each as an ðE; ~pÞ four-vector with

zero mass. The anti-ktalgorithm is well motivated since it is infrared safe to all orders, produces geometrically well- defined conelike jets, and is used for pQCD calculations (from partons), event generators (from stable particles), and the detector (from energy clusters [7]). The azimuthal decorrelation is defined as the absolute value of the difference in azimuthal angle between the jet with the highest pT in each event, p^max_T , and the jet with the second-highest pT in the event. There are nine analysis regions in p^max_T , where the lowest region is bounded by p^max_T >110 GeV and the highest region requires p^max_T >

800 GeV[7]. Only jets withpT>100 GeVandjyj<2:8, where y is the jet rapidity [8], are considered. The two leading jets that defineare required to satisfyjyj<0:8, restricting the measurement to a centralyregion where the momentum fractions (x) of the interacting partons are roughly equal and the experimental acceptance for multijet production is increased. In this region where 0:02&x&

0:14, the parton distribution function (PDF) uncertainties are typically 3% (at fixed factorization scale) [9]. The cross sections, measured over the range =2 and normalized independently for each analysis region, are compared with expectations from a pQCD calculation [10]

that is next-to-leading order (NLO) in three-parton production. The perturbative prediction for the cross section is Oð⁴sÞ, wheresis the strong coupling constant.

The angular decorrelation is sensitive to multijet con- figurations such as those produced by event generators like

SHERPA[11], which matches higher-order tree-level pQCD diagrams with a dipole parton-shower model [12]. Samples for 2!26jet production are combined using an im- proved parton matching scheme [13]. Event generators such as PYTHIA[14] and HERWIG [15] use2!2 leading order pQCD matrix elements matched with phenomenological parton-cascade models to simulate higher-order QCD effects. Such models have been successful at repro- ducing other QCD processes measured by the ATLAS Collaboration [7,16].

The ATLAS detector [17,18] consists of an inner track- ing system surrounded by a thin superconducting solenoid providing a 2 T magnetic field, electromagnetic and hadronic calorimeters, and a muon spectrometer based on

*Full author list given at the end of the article.

Published by the American Physical Society under the terms of the Creative Commons Attribution 3.0 License. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.

PRL106,172002 (2011) P H Y S I C A L R E V I E W L E T T E R S 29 APRIL 2011

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large superconducting toroids. Jet measurements depend most heavily on the calorimeters. The electromagnetic calorimeter is a lead liquid-argon (LAr) detector with an accordion geometry. Hadron calorimetry is based on two different detector technologies, with scintillator tiles or LAr as the active medium, and with either steel, copper, or tungsten as the absorber material. The pseudorapidity () [8] andsegmentations of the calorimeters are suffi- ciently fine to ensure that angular resolution uncertainties are negligible compared to other sources of systematic uncertainty.

A hardware-based calorimeter jet trigger identified events of interest; the decision was further refined in soft- ware [17,18]. Events with at least one jet that satisfied a minimum transverse energy (ET) requirement were re- corded for further analysis. The events in eachp^max_T range are selected by a single trigger with a givenET threshold, and the lower end of the range is chosen above the jetpTat which that trigger is100%efficient. Three sets of trig- gered events with different integrated luminosity are considered: 2:3 pb¹ for 110< p^max_T 160 GeV, 9:6 pb¹ for 160< p^max_T 260 GeV, and 36 pb¹ for p^max_T >

260 GeV [2]. Events are also required to have a reconstructed primary vertex within 15 cm inzof the center of the detector; each vertex had 5associated tracks. The inputs to the anti-k_tjet algorithm are clusters of calorimeter cells seeded by cells with energy that is significantly above the measured noise [7]. Jets reconstructed in the detector, whether in data or theGEANT4-based simulation [19,20], are corrected for the effects of hadronic shower response and detector-material distributions using a pT- and -dependent calibration [7] based on the detector simulation and validated with extensive test beam [18] and col- lision data [21] studies. Jets likely to have arisen from detector noise or cosmic rays are rejected [22].

The resultingdistribution is shown in Fig.1for jets withpT>100 GeV. There are 146 788 events in the data sample, 85 of which have at least five jets with p_T >

100 GeV. Also shown is the ^PYTHIAsample with MRST 2007LO PDF [23] and ATLAS MC09 underlying event tune [24], processed through the full detector simulation and normalized to the number of events in the data sample.

Two- and three-jet production primarily populates the region 2=3< < while smaller values of re- quire additional activity such as soft radiation or more jets in an event. Figure 1 illustrates that the decorrelation increases when a third high-pT jet is also required.

Events with additional high-pT jets widen the overall distribution.

The measured differentialdistributions in data are corrected in a single step with a bin-by-bin unfolding method [7] to compensate for trigger and detector ineffi- ciencies and the effects of finite experimental resolutions.

These correction factors, evaluated using the PYTHIA

sample, lie within 9%of unity. The leading sources of

systematic uncertainty on the normalized cross section are the jet energy scale calibration (2%–17%) [7], the bin-by- bin unfolding method (1%–19%), and the jet energy and position resolutions (0:5%–5%). The ranges in parentheses represent the magnitude of the uncertainties near and

=2, respectively, and correspond to the analysis region with the smallest statistical uncertainty (160< p^max_T 210 GeV). Multiple pp interactions in the same beam crossing that can increase the measured jet energy are included in the evaluation of the jet energy scale uncertainties (<0:8% on the cross section for all analysis regions).

The normalized differential cross section is shown for each of the ninep^max_T analysis regions as a function of in Fig. 2. As p^max_T increases, and the probability for the emission of a hard third jet is reduced, the fraction of events near becomes larger. Overlaid on the data are the results from a NLO pQCD ½Oð⁴_sÞ calculation,

NLOJETþþ[10] withFASTNLO[25] and using the MSTW 2008 PDF [9]. The factorization and renormalization scales are set to p^max_T and are varied independently up and down by a factor of 2 to determine the scale uncertainties. The scale uncertainties are larger between=2<

<2=3 where the pQCD calculation is effectively leading order in four-parton production. The PDF uncertainties are treated as the envelope of the 68% C.L. uncertainties from MSTW 2008 [9], NNPDF 2.0 [26], and CTEQ 10 [27], and are combined with the uncertainties resulting from ansvariation of0:004; thescontribu- tions dominate. The calculation is corrected for nonpertur- bative effects due to hadronization and the underlying event [28]; the correction is smaller than 3%. The fixed- order calculation fails near!where soft processes dominate and contributions from logarithmic terms are enhanced. Figure3displays the ratio of the cross section

[rad]

φ

∆

π/2 2π/3 5π/6 π

Number of Events

1 10 102

103

104

105

jets R=0.6 anti-kt pT

y

<2.8 y

>100 GeV |

<0.8 Leading two jets: |

>110 GeV max pT

=36 pb-1 dt

∫L Data

2 jets

≥ 3 jets

≥ 4 jets

≥ 5 jets

≥ PYTHIA

ATLAS s=7 TeV

FIG. 1 (color online). Thedistribution for2,3,4, and5jets withpT>100 GeV. Overlaid on the calibrated but otherwise uncorrected data (points) are results from PYTHIA

processed through the detector simulation (lines). All uncertainties are statistical only.

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with respect to the NLO calculation. In most regions, the theory is consistent with the data. However, the prediction in the range110< p^max_T <160 GeVis relatively low in the central region of where the scale uncertainties are small.

The data are also compared with predictions [29] from

SHERPA, PYTHIA, and HERWIG in Fig. 4. The leading- logarithmic approximations used in these event generators’

parton-shower models effectively regularize the divergence at !; all three provide a good description of the data in this region. In the region=2< <5=6, where multijet contributions are significant, this observ- able distinguishes between the three generators. SHERPA, which explicitly includes higher-order tree-level diagrams, performs well in most and p^max_T regions. Having phenomenological parameters that have been adjusted to previous ATLAS measurements,PYTHIA[28] andHERWIG

[24] also describe the data.

In summary, we present a measurement of dijet azimuthal decorrelations in events produced inffiffiffi ppcollisions at ps

¼7 TeV. The normalized differential cross sections

are based on the full data set (R

Ldt¼36 pb¹) collected by the ATLAS Collaboration during the 2010 run of the LHC. Expectations from NLO pQCD [Oð⁴_sÞ] and those of

160 GeV

≤

max

pT

<

110

ATLAS s=7 TeV

=36 pb-1

dt

∫L

310 GeV

≤

max

pT

<

260

π/2 2π/3 5π/6 π 600 GeV

≤

max

pT

<

500

210 GeV

≤

max

pT

<

160

4) αs O(

NLO pQCD scale unc.

unc.

αs PDF &

400 GeV

≤

max

pT

<

310

π/3

2 5π/6 π

800 GeV

≤

max

pT

<

600

260 GeV

≤

max

pT

<

210

jets R=0.6 anti-kt

<0.8 y

>100 GeV pT

500 GeV

≤

max

pT

<

400

[rad]

φ

∆

π/3

2 5π/6 π

800 GeV

max>

pT

ratio to NLO pQCDφ∆/dσ dσ1/

2.0 1.0 0.5

FIG. 3 (color online). Ratio of the differential cross section ð1=Þðd=dÞmeasured in data with respect to expectations from NLO pQCD (points). The theory uncertainties are indicated by the hatched regions. The region near the divergence at !is excluded from the comparison.

160 GeV

≤ max pT

<

110

ATLAS s=7 TeV

=36 pb-1 dt

∫L

310 GeV

≤ max pT

<

260

π/2 2π/3 5π/6 π 600 GeV

≤ max pT

<

500

210 GeV

≤ max pT

<

160 PYTHIA HERWIG SHERPA stat. unc.

400 GeV

≤ max pT

<

310

π/3

2 5π/6 π

800 GeV max≤ pT

<

600

260 GeV

≤ max pT

<

210

jets R=0.6 anti-kt

<0.8 y

>100 GeV pT

500 GeV

≤ max pT

<

400

π/3

2 5π/6 π

800 GeV max>

pT

ratio to SHERPAφ∆/dσ dσ1/

2.0 1.0 0.5

[rad]

φ

∆

FIG. 4 (color online). Ratio of the differential cross section ð1=Þðd=dÞ measured in data with respect to the result fromSHERPA(points). The shaded region indicates theSHERPA

statistical uncertainty. Predictions fromPYTHIAandHERWIG, also in ratio toSHERPA, are displayed as lines.

[rad]

φ

∆

π/2 2π/3 5π/6 π

]-1 [radφ∆/dσ dσ1/

10-3

10-2

10-1

1 10 102

103

104

105

106

107

108

109

=36 pb-1

dt

∫

L Data

8)

×10 800 GeV (

max>

pT

7)

×10 800 GeV (

≤

max

pT

<

600

6)

×10 600 GeV (

≤

max

pT

<

500

5)

×10 500 GeV (

≤

max

pT

<

400

4)

×10 400 GeV (

≤

max

pT

<

310

3)

×10 310 GeV (

≤

max

pT

<

260

2)

×10 260 GeV (

≤

max

pT

<

210

1)

×10 210 GeV (

≤

max

pT

<

160

0)

×10 160 GeV (

≤

max

pT

<

110

4) αs

O(

NLO pQCD unc.

αs

PDF &

scale unc.

ATLAS s=7 TeV

<0.8 y

>100 GeV pT

jets R=0.6 anti-kt

FIG. 2 (color online). The differential cross section ð1=Þ ðd=dÞbinned in nine p^maxT regions. Overlaid on the data (points) are results from the NLO pQCD calculation. The error bars on the data points indicate the statistical (inner error bar) and systematic uncertainties added in quadrature in this and subsequent figures. The theory uncertainties are indicated by the hatched regions. Different bins inp^maxT are scaled by multi- plicative factors of 10 for display purposes. The region near the divergence at!is excluded from the calculation.

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several event generators successfully describe the general characteristics of our measurements, including the increasing slope of the distribution withp^max_T and the shape near =2 where events with multiple jets make a considerable contribution. Our data, which include jets withpT values that significantly exceed earlier measurements, explore QCD in a new kinematic region.

We wish to thank CERN for the efficient commissioning and operation of the LHC during this initial high-energy data-taking period 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, 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; ARTEMIS, European Union;

IN2P3-CNRS, CEA-DSM/IRFU, France; GNAS, Georgia; BMBF, DFG, HGF, MPG, and AvH Foundation, Germany; GSRT, Greece; ISF, MINERVA, GIF, DIP, and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; FOM and NWO, Netherlands;

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, U.S. The crucial computing support from all WLCG partners is gratefully acknowledged, 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 (U.S.), and in the Tier-2 facilities worldwide.

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W. H. Bell,⁴⁹G. Bella,¹⁵³L. Bellagamba,^19aF. Bellina,²⁹G. Bellomo,^89a,89bM. Bellomo,^119aA. Belloni,⁵⁷ O. Beloborodova,¹⁰⁷K. Belotskiy,⁹⁶O. Beltramello,²⁹S. Ben Ami,¹⁵²O. Benary,¹⁵³D. Benchekroun,^135a C. Benchouk,⁸³M. Bendel,⁸¹B. H. Benedict,¹⁶³N. Benekos,¹⁶⁵Y. Benhammou,¹⁵³D. P. Benjamin,⁴⁴M. Benoit,¹¹⁵

J. R. Bensinger,²²K. Benslama,¹³⁰S. Bentvelsen,¹⁰⁵D. Berge,²⁹E. Bergeaas Kuutmann,⁴¹N. Berger,⁴ F. Berghaus,¹⁶⁹E. Berglund,⁴⁹J. Beringer,¹⁴K. Bernardet,⁸³P. Bernat,⁷⁷R. Bernhard,⁴⁸C. Bernius,²⁴T. Berry,⁷⁶ A. Bertin,^19a,19bF. Bertinelli,²⁹F. Bertolucci,^122a,122bM. I. Besana,^89a,89bN. Besson,¹³⁶S. Bethke,⁹⁹W. Bhimji,⁴⁵ R. M. Bianchi,²⁹M. Bianco,^72a,72bO. Biebel,⁹⁸S. P. Bieniek,⁷⁷J. Biesiada,¹⁴M. Biglietti,^134a,134bH. Bilokon,⁴⁷ M. Bindi,^19a,19bS. Binet,¹¹⁵A. Bingul,^18cC. Bini,^132a,132bC. Biscarat,¹⁷⁷U. Bitenc,⁴⁸K. M. Black,²¹R. E. Blair,⁵

J.-B. Blanchard,¹¹⁵G. Blanchot,²⁹C. Blocker,²²J. Blocki,³⁸A. Blondel,⁴⁹W. Blum,⁸¹U. Blumenschein,⁵⁴ G. J. Bobbink,¹⁰⁵V. B. Bobrovnikov,¹⁰⁷A. Bocci,⁴⁴C. R. Boddy,¹¹⁸M. Boehler,⁴¹J. Boek,¹⁷⁴N. Boelaert,³⁵

S. Bo¨ser,⁷⁷J. A. Bogaerts,²⁹A. Bogdanchikov,¹⁰⁷A. Bogouch,^90,aC. Bohm,^146aV. Boisvert,⁷⁶T. Bold,^163,g V. Boldea,^25aM. Bona,⁷⁵V. G. Bondarenko,⁹⁶M. Boonekamp,¹³⁶G. Boorman,⁷⁶C. N. Booth,¹³⁹P. Booth,¹³⁹

S. Bordoni,⁷⁸C. Borer,¹⁶A. Borisov,¹²⁸G. Borissov,⁷¹I. Borjanovic,^12aS. Borroni,^132a,132bK. Bos,¹⁰⁵ D. Boscherini,^19aM. Bosman,¹¹H. Boterenbrood,¹⁰⁵D. Botterill,¹²⁹J. Bouchami,⁹³J. Boudreau,¹²³ E. V. Bouhova-Thacker,⁷¹C. Boulahouache,¹²³C. Bourdarios,¹¹⁵N. Bousson,⁸³A. Boveia,³⁰J. Boyd,²⁹

I. R. Boyko,⁶⁵N. I. Bozhko,¹²⁸I. Bozovic-Jelisavcic,^12bJ. Bracinik,¹⁷A. Braem,²⁹E. Brambilla,^72a,72b P. Branchini,^134aG. W. Brandenburg,⁵⁷A. Brandt,⁷G. Brandt,¹⁵O. Brandt,⁵⁴U. Bratzler,¹⁵⁶B. Brau,⁸⁴J. E. Brau,¹¹⁴

H. M. Braun,¹⁷⁴B. Brelier,¹⁵⁸J. Bremer,²⁹R. Brenner,¹⁶⁶S. Bressler,¹⁵²D. Breton,¹¹⁵N. D. Brett,¹¹⁸ P. G. Bright-Thomas,¹⁷D. Britton,⁵³F. M. Brochu,²⁷I. Brock,²⁰R. Brock,⁸⁸T. J. Brodbeck,⁷¹E. Brodet,¹⁵³

F. Broggi,^89aC. Bromberg,⁸⁸G. Brooijmans,³⁴W. K. Brooks,^31bG. Brown,⁸²E. Brubaker,³⁰ P. A. Bruckman de Renstrom,³⁸D. Bruncko,^144bR. Bruneliere,⁴⁸S. Brunet,⁶¹A. Bruni,^19aG. Bruni,^19a M. Bruschi,^19aT. Buanes,¹³F. Bucci,⁴⁹J. Buchanan,¹¹⁸N. J. Buchanan,²P. Buchholz,¹⁴¹R. M. Buckingham,¹¹⁸

A. G. Buckley,⁴⁵S. I. Buda,^25aI. A. Budagov,⁶⁵B. Budick,¹⁰⁸V. Bu¨scher,⁸¹L. Bugge,¹¹⁷D. Buira-Clark,¹¹⁸ E. J. Buis,¹⁰⁵O. Bulekov,⁹⁶M. Bunse,⁴²T. Buran,¹¹⁷H. Burckhart,²⁹S. Burdin,⁷³T. Burgess,¹³S. Burke,¹²⁹

E. Busato,³³P. Bussey,⁵³C. P. Buszello,¹⁶⁶F. Butin,²⁹B. Butler,¹⁴³J. M. Butler,²¹C. M. Buttar,⁵³

J. M. Butterworth,⁷⁷W. Buttinger,²⁷T. Byatt,⁷⁷S. Cabrera Urba´n,¹⁶⁷M. Caccia,^89a,89bD. Caforio,^19a,19bO. Cakir,^3a P. Calafiura,¹⁴G. Calderini,⁷⁸P. Calfayan,⁹⁸R. Calkins,¹⁰⁶L. P. Caloba,^23aR. Caloi,^132a,132bD. Calvet,³³S. Calvet,³³

R. Camacho Toro,³³A. Camard,⁷⁸P. Camarri,^133a,133bM. Cambiaghi,^119a,119bD. Cameron,¹¹⁷J. Cammin,²⁰ S. Campana,²⁹M. Campanelli,⁷⁷V. Canale,^102a,102bF. Canelli,³⁰A. Canepa,^159aJ. Cantero,⁸⁰L. Capasso,^102a,102b

M. D. M. Capeans Garrido,²⁹I. Caprini,^25aM. Caprini,^25aD. Capriotti,⁹⁹M. Capua,^36a,36bR. Caputo,¹⁴⁸ PRL106,172002 (2011) P H Y S I C A L R E V I E W L E T T E R S 29 APRIL 2011

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C. Caramarcu,^25aR. Cardarelli,^133aT. Carli,²⁹G. Carlino,^102aL. Carminati,^89a,89bB. Caron,^159aS. Caron,⁴⁸ C. Carpentieri,⁴⁸G. D. Carrillo Montoya,¹⁷²A. A. Carter,⁷⁵J. R. Carter,²⁷J. Carvalho,^124a,hD. Casadei,¹⁰⁸ M. P. Casado,¹¹M. Cascella,^122a,122bC. Caso,^50a,50b,aA. M. Castaneda Hernandez,¹⁷²E. Castaneda-Miranda,¹⁷² V. Castillo Gimenez,¹⁶⁷N. F. Castro,^124aG. Cataldi,^72aF. Cataneo,²⁹A. Catinaccio,²⁹J. R. Catmore,⁷¹A. Cattai,²⁹

G. Cattani,^133a,133bS. Caughron,⁸⁸D. Cauz,^164a,164cA. Cavallari,^132a,132bP. Cavalleri,⁷⁸D. Cavalli,^89a M. Cavalli-Sforza,¹¹V. Cavasinni,^122a,122bA. Cazzato,^72a,72bF. Ceradini,^134a,134bA. S. Cerqueira,^23aA. Cerri,²⁹

L. Cerrito,⁷⁵F. Cerutti,⁴⁷S. A. Cetin,^18bF. Cevenini,^102a,102bA. Chafaq,^135aD. Chakraborty,¹⁰⁶K. Chan,² B. Chapleau,⁸⁵J. D. Chapman,²⁷J. W. Chapman,⁸⁷E. Chareyre,⁷⁸D. G. Charlton,¹⁷V. Chavda,⁸²S. Cheatham,⁷¹

S. Chekanov,⁵S. V. Chekulaev,^159aG. A. Chelkov,⁶⁵H. Chen,²⁴L. Chen,²S. Chen,^32cT. Chen,^32cX. Chen,¹⁷² S. Cheng,^32aA. Cheplakov,⁶⁵V. F. Chepurnov,⁶⁵R. Cherkaoui El Moursli,^135eV. Chernyatin,²⁴E. Cheu,⁶

S. L. Cheung,¹⁵⁸L. Chevalier,¹³⁶F. Chevallier,¹³⁶G. Chiefari,^102a,102bL. Chikovani,⁵¹J. T. Childers,^58a A. Chilingarov,⁷¹G. Chiodini,^72aM. V. Chizhov,⁶⁵G. Choudalakis,³⁰S. Chouridou,¹³⁷I. A. Christidi,⁷⁷ A. Christov,⁴⁸D. Chromek-Burckhart,²⁹M. L. Chu,¹⁵¹J. Chudoba,¹²⁵G. Ciapetti,^132a,132bK. Ciba,³⁷A. K. Ciftci,^3a R. Ciftci,^3aD. Cinca,³³V. Cindro,⁷⁴M. D. Ciobotaru,¹⁶³C. Ciocca,^19a,19bA. Ciocio,¹⁴M. Cirilli,⁸⁷M. Ciubancan,^25a

A. Clark,⁴⁹P. J. Clark,⁴⁵W. Cleland,¹²³J. C. Clemens,⁸³B. Clement,⁵⁵C. Clement,^146a,146bR. W. Clifft,¹²⁹ Y. Coadou,⁸³M. Cobal,^164a,164cA. Coccaro,^50a,50bJ. Cochran,⁶⁴P. Coe,¹¹⁸J. G. Cogan,¹⁴³J. Coggeshall,¹⁶⁵ E. Cogneras,¹⁷⁷C. D. Cojocaru,²⁸J. Colas,⁴A. P. Colijn,¹⁰⁵C. Collard,¹¹⁵N. J. Collins,¹⁷C. Collins-Tooth,⁵³ J. Collot,⁵⁵G. Colon,⁸⁴R. Coluccia,^72a,72bG. Comune,⁸⁸P. Conde Muin˜o,^124aE. Coniavitis,¹¹⁸M. C. Conidi,¹¹ M. Consonni,¹⁰⁴S. Constantinescu,^25aC. Conta,^119a,119bF. Conventi,^102a,iJ. Cook,²⁹M. Cooke,¹⁴B. D. Cooper,⁷⁷

A. M. Cooper-Sarkar,¹¹⁸N. J. Cooper-Smith,⁷⁶K. Copic,³⁴T. Cornelissen,^50a,50bM. Corradi,^19aF. Corriveau,^85,j A. Cortes-Gonzalez,¹⁶⁵G. Cortiana,⁹⁹G. Costa,^89aM. J. Costa,¹⁶⁷D. Costanzo,¹³⁹T. Costin,³⁰D. Coˆte´,²⁹ R. Coura Torres,^23aL. Courneyea,¹⁶⁹G. Cowan,⁷⁶C. Cowden,²⁷B. E. Cox,⁸²K. Cranmer,¹⁰⁸M. Cristinziani,²⁰

G. Crosetti,^36a,36bR. Crupi,^72a,72bS. Cre´pe´-Renaudin,⁵⁵C. Cuenca Almenar,¹⁷⁵T. Cuhadar Donszelmann,¹³⁹ S. Cuneo,^50a,50bM. Curatolo,⁴⁷C. J. Curtis,¹⁷P. Cwetanski,⁶¹H. Czirr,¹⁴¹Z. Czyczula,¹¹⁷S. D’Auria,⁵³ M. D’Onofrio,⁷³A. D’Orazio,^132a,132bA. Da Rocha Gesualdi Mello,^23aP. V. M. Da Silva,^23aC. Da Via,⁸² W. Dabrowski,³⁷A. Dahlhoff,⁴⁸T. Dai,⁸⁷C. Dallapiccola,⁸⁴S. J. Dallison,^129,aM. Dam,³⁵M. Dameri,^50a,50b D. S. Damiani,¹³⁷H. O. Danielsson,²⁹R. Dankers,¹⁰⁵D. Dannheim,⁹⁹V. Dao,⁴⁹G. Darbo,^50aG. L. Darlea,^25b

C. Daum,¹⁰⁵J. P. Dauvergne,²⁹W. Davey,⁸⁶T. Davidek,¹²⁶N. Davidson,⁸⁶R. Davidson,⁷¹M. Davies,⁹³ A. R. Davison,⁷⁷E. Dawe,¹⁴²I. Dawson,¹³⁹J. W. Dawson,^5,aR. K. Daya,³⁹K. De,⁷R. de Asmundis,^102a S. De Castro,^19a,19bP. E. De Castro Faria Salgado,²⁴S. De Cecco,⁷⁸J. de Graat,⁹⁸N. De Groot,¹⁰⁴P. de Jong,¹⁰⁵ C. De La Taille,¹¹⁵B. De Lotto,^164a,164cL. De Mora,⁷¹L. De Nooij,¹⁰⁵M. De Oliveira Branco,²⁹D. De Pedis,^132a P. de Saintignon,⁵⁵A. De Salvo,^132aU. De Sanctis,^164a,164cA. De Santo,¹⁴⁹J. B. De Vivie De Regie,¹¹⁵S. Dean,⁷⁷

D. V. Dedovich,⁶⁵J. Degenhardt,¹²⁰M. Dehchar,¹¹⁸M. Deile,⁹⁸C. Del Papa,^164a,164cJ. Del Peso,⁸⁰ T. Del Prete,^122a,122bA. Dell’Acqua,²⁹L. Dell’Asta,^89a,89bM. Della Pietra,^102a,kD. della Volpe,^102a,102b M. Delmastro,²⁹P. Delpierre,⁸³N. Delruelle,²⁹P. A. Delsart,⁵⁵C. Deluca,¹⁴⁸S. Demers,¹⁷⁵M. Demichev,⁶⁵ B. Demirkoz,¹¹J. Deng,¹⁶³S. P. Denisov,¹²⁸D. Derendarz,³⁸J. E. Derkaoui,^135dF. Derue,⁷⁸P. Dervan,⁷³K. Desch,²⁰

E. Devetak,¹⁴⁸P. O. Deviveiros,¹⁵⁸A. Dewhurst,¹²⁹B. DeWilde,¹⁴⁸S. Dhaliwal,¹⁵⁸R. Dhullipudi,^24,l A. Di Ciaccio,^133a,133bL. Di Ciaccio,⁴A. Di Girolamo,²⁹B. Di Girolamo,²⁹S. Di Luise,^134a,134bA. Di Mattia,⁸⁸ B. Di Micco,^134a,134bR. Di Nardo,^133a,133bA. Di Simone,^133a,133bR. Di Sipio,^19a,19bM. A. Diaz,^31aF. Diblen,^18c

E. B. Diehl,⁸⁷H. Dietl,⁹⁹J. Dietrich,⁴⁸T. A. Dietzsch,^58aS. Diglio,¹¹⁵K. Dindar Yagci,³⁹J. Dingfelder,²⁰ C. Dionisi,^132a,132bP. Dita,^25aS. Dita,^25aF. Dittus,²⁹F. Djama,⁸³R. Djilkibaev,¹⁰⁸T. Djobava,⁵¹M. A. B. do Vale,^23a

A. Do Valle Wemans,^124aT. K. O. Doan,⁴M. Dobbs,⁸⁵R. Dobinson,^29,aD. Dobos,⁴²E. Dobson,²⁹M. Dobson,¹⁶³ J. Dodd,³⁴O. B. Dogan,^18a,aC. Doglioni,¹¹⁸T. Doherty,⁵³Y. Doi,^66,aJ. Dolejsi,¹²⁶I. Dolenc,⁷⁴Z. Dolezal,¹²⁶

B. A. Dolgoshein,^96,aT. Dohmae,¹⁵⁵M. Donadelli,^23bM. Donega,¹²⁰J. Donini,⁵⁵J. Dopke,¹⁷⁴A. Doria,^102a A. Dos Anjos,¹⁷²M. Dosil,¹¹A. Dotti,^122a,122bM. T. Dova,⁷⁰J. D. Dowell,¹⁷A. D. Doxiadis,¹⁰⁵A. T. Doyle,⁵³ Z. Drasal,¹²⁶J. Drees,¹⁷⁴N. Dressnandt,¹²⁰H. Drevermann,²⁹C. Driouichi,³⁵M. Dris,⁹J. G. Drohan,⁷⁷J. Dubbert,⁹⁹ T. Dubbs,¹³⁷S. Dube,¹⁴E. Duchovni,¹⁷¹G. Duckeck,⁹⁸A. Dudarev,²⁹F. Dudziak,⁶⁴M. Du¨hrssen,²⁹I. P. Duerdoth,⁸²

L. Duflot,¹¹⁵M-A. Dufour,⁸⁵M. Dunford,²⁹H. Duran Yildiz,^3bR. Duxfield,¹³⁹M. Dwuznik,³⁷F. Dydak,²⁹ D. Dzahini,⁵⁵M. Du¨ren,⁵²W. L. Ebenstein,⁴⁴J. Ebke,⁹⁸S. Eckert,⁴⁸S. Eckweiler,⁸¹K. Edmonds,⁸¹C. A. Edwards,⁷⁶

I. Efthymiopoulos,⁴⁹W. Ehrenfeld,⁴¹T. Ehrich,⁹⁹T. Eifert,²⁹G. Eigen,¹³K. Einsweiler,¹⁴E. Eisenhandler,⁷⁵ T. Ekelof,¹⁶⁶M. El Kacimi,⁴M. Ellert,¹⁶⁶S. Elles,⁴F. Ellinghaus,⁸¹K. Ellis,⁷⁵N. Ellis,²⁹J. Elmsheuser,⁹⁸ PRL106,172002 (2011) P H Y S I C A L R E V I E W L E T T E R S 29 APRIL 2011