Measurement of the double-differential inclusive jet cross section in proton–proton collisions at \(\sqrt{s} = 13\,\text {TeV} \)

The European Physical Journal C, Aug 2016

A measurement of the double-differential inclusive jet cross section as a function of jet transverse momentum \(p_{\mathrm {T}} \) and absolute jet rapidity \(|y |\) is presented. The analysis is based on proton–proton collisions collected by the CMS experiment at the LHC at a centre-of-mass energy of 13\(\,\text {TeV}\). The data samples correspond to integrated luminosities of 71 and 44\(\,\text {pb}^\text {-1}\) for \(|y |<3\) and \(3.2<|y |<4.7\), respectively. Jets are reconstructed with the anti-\(k_{\mathrm {t}} \) clustering algorithm for two jet sizes, R, of 0.7 and 0.4, in a phase space region covering jet \(p_{\mathrm {T}} \) up to 2\(\,\text {TeV}\) and jet rapidity up to \(|y |\) = 4.7. Predictions of perturbative quantum chromodynamics at next-to-leading order precision, complemented with electroweak and nonperturbative corrections, are used to compute the absolute scale and the shape of the inclusive jet cross section. The cross section difference in R, when going to a smaller jet size of 0.4, is best described by Monte Carlo event generators with next-to-leading order predictions matched to parton showering, hadronisation, and multiparton interactions. In the phase space accessible with the new data, this measurement provides a first indication that jet physics is as well understood at \(\sqrt{s}=13\,\text {TeV} \) as at smaller centre-of-mass energies.

A PDF file should load here. If you do not see its contents the file may be temporarily unavailable at the journal website or you do not have a PDF plug-in installed and enabled in your browser.

Alternatively, you can download the file locally and open with any standalone PDF reader:

https://link.springer.com/content/pdf/10.1140%2Fepjc%2Fs10052-016-4286-3.pdf

Measurement of the double-differential inclusive jet cross section in proton–proton collisions at \(\sqrt{s} = 13\,\text {TeV} \)

Eur. Phys. J. C Measurement of the double-differential inclusive jet cross section √ in proton-proton collisions at s = 13 TeV CMS Collaboration 0 1 2 3 4 5 6 7 8 9 10 11 12 14 16 17 18 20 21 22 23 24 27 28 29 30 31 32 33 34 35 37 38 39 42 43 44 46 47 48 49 50 52 53 54 55 57 58 60 63 64 65 69 70 71 0 CERN , 1211 Geneva 23 , Switzerland 1 Beihang University , Beijing , China W. Fang 2 University of Sofia , Sofia, Bulgaria A. Dimitrov, I. Glushkov, L. Litov, B. Pavlov, P. Petkov 3 Ghent University , Ghent , Belgium A. Cimmino, T. Cornelis, D. Dobur, A. Fagot, G. Garcia, M. Gul, J. Mccartin, D. Poyraz, S. Salva, R. Schöfbeck, M. Tytgat, W. Van Driessche, E. Yazgan, N. Zaganidis 4 Faculty of Science, University of Split , Split , Croatia Z. Antunovic, M. Kovac 5 State Key Laboratory of Nuclear Physics and Technology, Peking University , Beijing , China C. Asawatangtrakuldee, Y. Ban, Q. Li, S. Liu, Y. Mao, S. J. Qian, D. Wang, Z. Xu 6 Department of Physics, University of Helsinki , Helsinki , Finland P. Eerola, J. Pekkanen, M. Voutilainen 7 Charles University , Prague , Czech Republic M. Finger 8 University of Cyprus , Nicosia, Cyprus A. Attikis, G. Mavromanolakis, J. Mousa, C. Nicolaou, F. Ptochos, P. A. Razis, H. Rykaczewski 9 Tbilisi State University , Tbilisi , Georgia D. Lomidze 10 Georgian Technical University , Tbilisi , Georgia A. Khvedelidze 11 Lappeenranta University of Technology , Lappeenranta , Finland J. Talvitie, T. Tuuva 12 Helsinki Institute of Physics , Helsinki, Finland J. Härkönen, V. Karimäki, R. Kinnunen, T. Lampén, K. Lassila-Perini, S. Lehti, T. Lindén, P. Luukka, T. Peltola, J. Tuominiemi, E. Tuovinen, L. Wendland 13 , J. Molnar, Z. Szillasi 14 University of Hamburg , Hamburg, Germany V. Blobel, M. Centis Vignali, A. R. Draeger, T. Dreyer, E. Garutti, K. Goebel, D. Gonzalez, J. Haller, M. Hoffmann, R. S. Höing, A. Junkes, R. Klanner, R. Kogler, N. Kovalchuk, T. Lapsien, T. Lenz, I. Marchesini, D. Marconi, M. Meyer, M. Niedziela, D. Nowatschin, J. Ott, F. Pantaleo 15 , A. Makovec , P. Raics, Z. L. Trocsanyi, B. Ujvari 16 III. Physikalisches Institut B, RWTH Aachen University , Aachen, Germany V. Cherepanov, Y. Erdogan, G. Flügge, F. Hoehle, B. Kargoll, T. Kress, A. Künsken, J. Lingemann, A. Nehrkorn, A. Nowack, I. M. Nugent, C. Pistone, O. Pooth, A. Stahl 17 III. Physikalisches Institut A, RWTH Aachen University , Aachen, Germany M. Brodski, E. Dietz-Laursonn, D. Duchardt, M. Endres, M. Erdmann, S. Erdweg, T. Esch, R. Fischer, A. Güth, T. Hebbeker, C. Heidemann, K. Hoepfner, S. Knutzen, M. Merschmeyer, A. Meyer, P. Millet, S. Mukherjee, M. Olschewski, K. Padeken, P. Papacz, T. Pook, M. Radziej, H. Reithler, M. Rieger, F. Scheuch, L. Sonnenschein, D. Teyssier, S. Thüer 18 University of Debrecen , Debrecen , Hungary M. Bartók 19 , T. Peiffer , A. Perieanu, J. Poehlsen, C. Sander, C. Scharf, P. Schleper, E. Schlieckau, A. Schmidt, S. Schumann, J. Schwandt, H. Stadie, G. Steinbrück, F. M. Stober, M. Stöver, H. Tholen, D. Troendle, E. Usai, L. Vanelderen, A. Vanhoefer, B. Vormwald 20 Institute of Nuclear Research ATOMKI , Debrecen , Hungary N. Beni, S. Czellar, J. Karancsi 21 University of Ioánnina , Ioannina , Greece I. Evangelou, G. Flouris, C. Foudas, P. Kokkas, N. Loukas, N. Manthos, I. Papadopoulos, E. Paradas 22 Saha Institute of Nuclear Physics , Kolkata , India R. Bhattacharya , S. Bhattacharya, K. Chatterjee, S. Dey, S. Dutt, S. Dutta, S. Ghosh, N. Majumdar, A. Modak, K. Mondal, S. Mukhopadhyay, S. Nandan, A. Purohit, A. Roy, D. Roy, S. Roy Chowdhury, S. Sarkar, M. Sharan, S. Thakur 23 University of Delhi , Delhi , India Ashok Kumar , A. Bhardwaj, B. C. Choudhary, R. B. Garg, S. Keshri, A. Kumar, S. Malhotra, M. Naimuddin, N. Nishu, K. Ranjan, R. Sharma, V. Sharma 24 National Institute of Science Education and Research , Bhubaneswar , India S. Bahinipati, S. Choudhury 25 , P. Mal, K. Mandal, A. Nayak 26 , D. K. Sahoo, N. Sahoo , S. K. Swain 27 Tata Institute of Fundamental Research-B , Mumbai , India S. Banerjee, M. Guchait, Sa. Jain, G. Majumder, K. Mazumdar, N. Wickramage 28 Tata Institute of Fundamental Research-A, Mumbai, India T. Aziz , S. Dugad, G. Kole, B. Mahakud, S. Mitra, G. B. Mohanty, N. Sur, B. Sutar 29 Tata Institute of Fundamental Research , Mumbai , India S. Bhowmik 30 Indian Institute of Technology Madras , Madras , India P. K. Behera 31 Hanyang University , Seoul , Korea J. A. Brochero Cifuentes, T. J. Kim 32 Chonbuk National University , Jeonju , Korea H. Kim, A. Lee 33 Faculty of Physics, Institute of Experimental Physics, University of Warsaw , Warsaw , Poland K. Bunkowski, A. Byszuk 34 Vilnius University , Vilnius , Lithuania V. Dudenas, A. Juodagalvis, J. Vaitkus 35 Sungkyunkwan University , Suwon, Korea Y. Choi, J. Goh, D. Kim, E. Kwon, J. Lee, I. Yu 36 , K. Doroba , A. Kalinowski, M. Konecki, J. Krolikowski, M. Misiura, M. Olszewski, M. Walczak 37 Faculty of Physics and Vinca Institute of Nuclear Sciences, University of Belgrade , Belgrade , Serbia P. Adzic 38 P. N. Lebedev Physical Institute , Moscow , Russia V. Andreev, M. Azarkin 39 Institute for Theoretical and Experimental Physics , Moscow , Russia V. Epshteyn, V. Gavrilov, N. Lychkovskaya, V. Popov, I. Pozdnyakov, G. Safronov, A. Spiridonov, M. Toms, E. Vlasov, A. Zhokin 40 , P. Cirkovic, D. Devetak, J. Milosevic, V. Rekovic 41 , S. V. Rusakov, A. Terkulov 42 Bogazici University , Istanbul , Turkey E. Gülmez, M. Kaya 43 Physics Department, Middle East Technical University , Ankara , Turkey B. Bilin, S. Bilmis, B. Isildak 44 National Central University , Chung-Li , Taiwan V. Candelise, T. H. Doan, Sh. Jain, R. Khurana, M. Konyushikhin, C. M. Kuo, W. Lin, Y. J. Lu, A. Pozdnyakov, S. S. Yu 45 , M. Yalvac , M. Zeyrek 46 The University of Alabama , Tuscaloosa, USA O. Charaf, S. I. Cooper, C. Henderson, P. Rumerio 47 Baylor University , Waco, USA A. Borzou, K. Call, J. Dittmann, K. Hatakeyama, H. Liu, N. Pastika 48 Brunel University , Uxbridge , UK J. E. Cole, P. R. Hobson, A. Khan, P. Kyberd, D. Leslie, I. D. Reid, P. Symonds, L. Teodorescu, M. Turner 49 University of Bristol , Bristol, UK R. Aggleton, F. Ball, L. Beck, J. J. Brooke, D. Burns, E. Clement, D. Cussans, H. Flacher, J. Goldstein, M. Grimes, G. P. Heath, H. F. Heath, J. Jacob, L. Kreczko, C. Lucas, D. M. Newbold 50 Istanbul Technical University , Istanbul , Turkey A. Cakir, K. Cankocak, S. Sen 51 , S. Paramesvaran, A. Poll, T. Sakuma, S. Seif El Nasr-Storey, D. Smith, V. J. Smith 52 University of California , Riverside, Riverside , USA K. Burt , R. Clare, J. Ellison, J. W. Gary, G. Hanson, J. Heilman, P. Jandir, E. Kennedy, F. Lacroix, O. R. Long, M. Malberti, M. Olmedo Negrete, M. I. Paneva, A. Shrinivas, H. Wei, S. Wimpenny, B. R. Yates 53 University of California , Davis, Davis, USA R. Breedon, G. Breto, D. Burns, M. Calderon De La Barca Sanchez, S. Chauhan, M. Chertok, J. Conway, R. Conway, P. T. Cox, R. Erbacher, C. Flores, G. Funk, M. Gardner, W. Ko, R. Lander, C. Mclean, M. Mulhearn, D. Pellett, J. Pilot, F. Ricci-Tam, S. Shalhout, J. Smith, M. Squires, D. Stolp, M. Tripathi, S. Wilbur, R. Yohay 54 Brown University , Providence, USA G. Benelli, E. Berry, D. Cutts, A. Ferapontov, A. Garabedian, J. Hakala, U. Heintz, O. Jesus, E. Laird, G. Landsberg, Z. Mao, M. Narain, S. Piperov, S. Sagir, E. Spencer, R. Syarif 55 California Institute of Technology , Pasadena, USA D. Anderson, A. Apresyan, J. Bendavid, A. Bornheim, J. Bunn, Y. Chen, J. Duarte, A. Mott, H. B. Newman, C. Pena, M. Spiropulu, J. R. Vlimant, S. Xie, R. Y. Zhu 56 , W. Clarida, K. Dilsiz , S. Durgut, R. P. Gandrajula, M. Haytmyradov, V. Khristenko, J.-P. Merlo, H. Mermerkaya 57 The University of Iowa , Iowa City , USA B. Bilki 58 Florida State University , Tallahassee, USA A. Ackert, J. R. Adams, T. Adams, A. Askew, S. Bein, B. Diamond, S. Hagopian, V. Hagopian, K. F. Johnson, A. Khatiwada, H. Prosper, A. Santra, M. Weinberg 59 , A. Penzo , C. Snyder, E. Tiras, J. Wetzel, K. Yi 60 University of Florida , Gainesville, USA D. Acosta, P. Avery, P. Bortignon, D. Bourilkov, A. Brinkerhoff, A. Carnes, M. Carver, D. Curry, S. Das, R. D. Field, I. K. Furic, J. Konigsberg, A. Korytov, P. Ma, K. Matchev, H. Mei, P. Milenovic 61 , A. Mestvirishvili, A. Moeller , J. Nachtman, H. Ogul, Y. Onel, F. Ozok 62 , G. Mitselmakher , D. Rank, L. Shchutska, D. Sperka, L. Thomas, J. Wang, S. Wang, J. Yelton 63 Texas A&M University, College Station , USA O. Bouhali 64 University of Notre Dame , Notre Dame , USA N. Dev, M. Hildreth, K. Hurtado Anampa, C. Jessop, D. J. Karmgard, N. Kellams, K. Lannon, N. Marinelli, F. Meng, C. Mueller, Y. Musienko 65 Northeastern University , Boston, USA G. Alverson, E. Barberis, D. Baumgartel, M. Chasco, A. Hortiangtham, A. Massironi, D. M. Morse, D. Nash, T. Orimoto, R. Teixeira De Lima, D. Trocino, R.-J. Wang, D. Wood 66 , M. Planer , A. Reinsvold, R. Ruchti, G. Smith, S. Taroni, N. Valls, M. Wayne, M. Wolf, A. Woodard 67 , A. Celik , M. Dalchenko, M. De Mattia, A. Delgado, S. Dildick, R. Eusebi, J. Gilmore, T. Huang, E. Juska, T. Kamon 68 , V. Krutelyov, R. Mueller, Y. Pakhotin, R. Patel, A. Perloff, L. Perniè, D. Rathjens, A. Rose, A. Safonov, A. Tatarinov, K. A. Ulmer 69 University of Wisconsin-Madison , Madison, WI , USA D. A. Belknap, S. Dasu, L. Dodd, S. Duric, B. Gomber, M. Grothe, M. Herndon, A. Hervé, P. Klabbers, A. Lanaro, A. Levine, K. Long, R. Loveless, I. Ojalvo, T. Perry, G. A. Pierro, G. Polese, T. Ruggles, A. Savin, A. Sharma, N. Smith, W. H. Smith, D. Taylor, P. Verwilligen, N. Woods 70 University of Virginia , Charlottesville, USA M. W. Arenton, P. Barria, B. Cox, J. Goodell, R. Hirosky, A. Ledovskoy, H. Li, C. Neu, T. Sinthuprasith, X. Sun, Y. Wang, E. Wolfe, F. Xia 71 Vanderbilt University , Nashville, USA A. G. Delannoy, S. Greene, A. Gurrola, R. Janjam, W. Johns, C. Maguire, A. Melo, H. Ni, P. Sheldon, S. Tuo, J. Velkovska, Q. Xu A measurement of the double-differential inclusive jet cross section as a function of jet transverse momentum pT and absolute jet rapidity |y| is presented. The analysis is based on proton-proton collisions collected by the CMS experiment at the LHC at a centre-of-mass energy of 13 TeV. The data samples correspond to integrated luminosities of 71 and 44 pb−1 for |y| < 3 and 3.2 < |y| < 4.7, respectively. Jets are reconstructed with the anti-kt clustering algorithm for two jet sizes, R, of 0.7 and 0.4, in a phase space region covering jet pT up to 2 TeV and jet rapidity up to |y| = 4.7. Predictions of perturbative quantum chromodynamics at next-to-leading order precision, complemented with electroweak and nonperturbative corrections, are used to compute the absolute scale and the shape of the inclusive jet cross section. The cross section difference in R, when going to a smaller jet size of 0.4, is best described by Monte Carlo event generators with next-to-leading order predictions matched to parton showering, hadronisation, and multiparton interactions. In the phase space accessible with the new data, this measurement provides a first indication that jet physics is as well understood at √s = 13 TeV as at smaller centreof-mass energies. Quantum chromodynamics (QCD) is the fundamental theory describing strong interactions among partons, i.e.quarks and gluons. Inclusive jet production (p + p → jet + X) is a key process to test predictions of perturbative QCD (pQCD) over a wide region in phase space. To compare with measurements, the parton-level calculations must be complemented with corrections for nonperturbative (NP) effects that involve the modeling of hadronisation (HAD) and multiparton interactions (MPI). Previous measurements at the CERN LHC have been carried out by the ATLAS and CMS Collaborations at centre-of-mass energies √s = 2.76 TeV [1,2], 7 TeV [3- - 7], and at lower √s by experiments at other hadron colliders [8–12]. The measurements at 2.76 and 7 TeV centre-ofmass energies were found to be in agreement with calculations at next-to-leading order (NLO) in the strong coupling constant αS over a wide range of jet transverse momentum pT and rapidity y. With the latest data from the LHC Run 2, these tests of pQCD are extended to cover the new energy regime of √s = 13 TeV. In this paper, a measurement of the double-differential inclusive jet cross section is presented as a function of the jet pT and absolute jet rapidity |y|. The jets are clustered with the anti-kt jet algorithm [13] as implemented in the FastJet library [14]. Two jet sizes R are used: the larger value R = 0.7 corresponds to the standard jet size chosen in most QCD jet analyses made by the CMS Collaboration because it favourably compares to fixed-order predictions [15]. A second, smaller value of R emphasizes different aspects of perturbative and nonperturbative QCD and permits complementary tests to be performed [16–18]. Moreover, the choice of R = 0.4 as a new CMS default jet size that replaces the previous one of 0.5 in LHC Run 1 analyses will allow direct comparisons between jet measurements made by ATLAS and CMS. The proton–proton collision data were recorded by the CMS experiment at a centre-of-mass energy of 13 TeV in 2015. The data samples correspond to integrated luminosities of 71 and 44 pb−1 for ranges in rapidity of |y| < 3 and 3.2 < |y| < 4.7, respectively. The smaller amount of data for the forward rapidity range is explained by more difficult operating conditions at the very start of data taking, which reduced the event sample certified for physics analyses. The results are compared to fixed-order predictions at NLO precision, complemented with electroweak and nonperturbative corrections, and to predictions of various Monte Carlo (MC) event generators that combine leading-order (LO) or NLO pQCD with the modeling of parton showers (PS), HAD, and MPI. 2 The CMS detector The central feature of the CMS apparatus is a superconducting solenoid of 6 m internal diameter, providing a magnetic field of 3.8 T. Within the solenoid volume are a silicon pixel and strip tracker, a lead tungstate crystal electromagnetic calorimeter (ECAL), and a brass and scintillator hadron calorimeter (HCAL), each composed of a barrel and two endcap sections. Forward calorimeters extend the pseudorapidity (η) coverage provided by the barrel and endcap detectors to the region 3.0 < |y| < 5.2. Muons are measured in gasionisation detectors embedded in the steel flux-return yoke outside the solenoid. In the region |η| < 1.74, the HCAL cells have widths of 0.087 in η and 0.087 radians in azimuth (φ). In the η-φ plane, and for |η| < 1.48, the HCAL cells map onto 5 × 5 ECAL crystals arrays to form calorimeter towers projecting radially outwards from close to the nominal interaction point. At larger values of |η|, the size in rapidity of the towers increases and the matching ECAL arrays contain fewer crystals. Within each tower, the energy deposits in ECAL and HCAL cells are summed to define the calorimeter tower energies, subsequently used to provide the energies and directions of hadronic jets. The particle-flow (PF) event algorithm [19, 20] reconstructs and identifies each individual particle with an optimised combination of information from the various elements of the CMS detector. The energy of photons is directly obtained from the ECAL measurement. The energy of electrons is determined from a combination of the electron momentum at the primary interaction vertex as determined by the tracker, the energy of the corresponding ECAL cluster, and the energy sum of all bremsstrahlung photons spatially compatible with originating from the electron track. The momentum of muons is obtained from the curvature of the corresponding track. The energy of charged hadrons is determined from a combination of their momenta measured in the tracker and the matching ECAL and HCAL energy deposits, corrected for zero-suppression effects and for the response function of the calorimeters to hadronic showers. Finally, the energy of neutral hadrons is obtained from the corresponding ECAL and HCAL energy. When combining information from the entire detector, the jet energy resolution typically amounts to 15 % at 10 GeV, 8 % at 100 GeV, and 4 % at 1 TeV, to be compared to about 40, 12, and 5 % obtained when the ECAL and HCAL alone are used. A more detailed description of the CMS detector, together with a definition of the coordinate system used and the relevant kinematic variables, can be found in Ref. [21]. 3 Event selection and jet reconstruction The measurement is based on data samples collected with single-jet high-level triggers (HLT) [22]. Eight single-jet pT range (GeV) Table 1 Trigger regions defined as ranges of the leading jet pT in each event for all single-jet triggers used in the inclusive jet cross section measurement HLT paths are considered, seeded by Level 1 triggers based on calorimetric information. They require, in the full rapidity coverage of the CMS detector, at least one jet in each event with pT > 60, 80, 140, 200, 260, 300, 400, or 450 GeV. All triggers, except the one with the highest threshold, are prescaled. The relative efficiency of each trigger is estimated using lower- pT-threshold triggers, and found to exceed 99 % in the pT regions shown in Table 1. The absolute trigger efficiency is measured using a tag and probe method [23] based on events selected with a single-jet trigger threshold of 40 GeV, a back-to-back dijet system, and a probe jet matched to a HLT trigger object. This trigger has an efficiency greater than 99 % for selecting an event with a jet of pT > 80 GeV. The main physics objects in this analysis are PF jets, reconstructed by clustering the Lorentz vectors of the PF candidates with the anti-kt (AK) clustering algorithm for the two jet sizes R = 0.7 and 0.4 that will be referred to as AK7 and AK4, respectively. In order to reduce the contribution to the reconstructed jets from additional proton–proton interactions within the same or neighbouring bunch crossings (pileup), the technique of charged hadron subtraction [24] is used. Pileup produces unwanted calorimetric energy depositions and additional tracks. The charged hadron subtraction reduces these effects by removing charged particles that originate from pileup vertices. The average number of pileup interactions observed in these data is ≈19. During data collection the LHC operated with a 50 ns bunch spacing. Reconstructed jets require small energy corrections to account for residual nonuniformities and nonlinearities in the detector response. Jet energy scale (JES) [23] corrections are obtained using simulated events, generated with pythia8.204 [25] with tune CUETM1 [26] and processed through the CMS detector simulation, and in situ measurements with dijet, photon+jet, and Z+jet events. An offset correction is applied to account for the extra energy clustered into jets due to the contribution of neutral particles produced by additional pileup interactions within the same or neighbouring bunch crossings. The JES correction, applied as a multiplicative factor to the jet four-momentum vector, depends on the jet η and pT values. The typical correction is about 10 % for a central jet with a pT of 100 GeV, and decreases with increasing pT. Events are required to have at least one primary vertex (PV). If more than one primary vertex is present, the vertex with the highest sum of the squared pT of the associated tracks is selected. This selected vertex is required to be reconstructed from at least five charged-particle tracks and must satisfy a set of quality requirements, including |zPV| < 24 cm and ρPV < 2 cm, where zPV and ρPV are the longitudinal and transverse distances of the primary vertex from the nominal interaction point in the CMS detector. Jets with pT > 114 GeV are grouped in seven different |y| bins. Additional selection criteria are applied to each event to remove spurious jet-like signatures originating from isolated noise patterns in certain HCAL regions. To suppress noise patterns, tight identification criteria are applied [27]: each jet should contain at least two particles, one of which is a charged hadron, and the jet energy fraction carried by neutral hadrons and photons should be less than 90 %. These criteria have an efficiency greater than 99 % for genuine jets. 4 Measurement of the double-differential inclusive jet cross section The double-differential inclusive jet cross section is defined as L where L is the integrated luminosity, Nj is the number of jets in a bin of a width pT in transverse momentum and y in rapidity, and is the product of the trigger and jet selection efficiencies, which is greater than 99 %. The phase space in rapidity is subdivided into six bins from y = 0 to |y| = 3 with | y| = 0.5, and one bin from |y| = 3.2 to 4.7, the forward rapidity region. The bin width in pT is chosen in such a way that bin-to-bin migrations due to detector resolution are less than 50 %. In each bin, the statistical uncertainty is derived through the formula √(4 − 3 f )/(2 − f ) Njets, where f corresponds to the fraction of events which contribute with exactly one jet in the bin [6]. This procedure corrects for possible multiple entries per event. The fraction f is typically larger than 95 % in the entire phase-space considered, thus the correction is small. The double-differential inclusive jet cross section is corrected for the detector resolution and unfolded to the stable particle level [28]. In this way, a direct comparison of this measurement to results from other experiments and to QCD predictions is possible. Particles are considered stable if their mean path length cτ is greater than 10 mm. The unfolding procedure is based on the iterative d’Agostini method [29], as implemented in the RooUnfold software package [30], using a response matrix that maps the predicted distribution onto the measured one. The response matrix is derived from a simulation, that uses the theoretically predicted spectrum as input and introduces smearing effects by taking into account the jet pT resolution. The predicted spectrum is evaluated from fixed-order calculations based on the NLOJet++ v4.1.13 program [31,32] within the framework of the fastNLO v2.3.1 package [33], using the CT14 [34] parton distribution functions (PDF). More details are presented in Sect. 5.1. The jet pT resolution is evaluated with the CMS detector simulation based on Geant4 [35] using a QCD simulation from pythia8 with tune CUETM1, after correcting for the residual differences between data and simulation [23]. The unfolded distributions differ from the distributions at detector level by 5–20 %. The unfolding procedure can turn statistical fluctuations of the measured spectra into correlated patterns among the neighbouring bins. It has been verified that such effects are always within the statistical uncertainties of the unfolded distributions, which are larger than those of the detector-level distributions. The iterative unfolding procedure is regularized by limiting the number of iterations to four in each rapidity bin. The main systematic uncertainties for the jet cross section measurements arise from the JES calibration and from the uncertainty in the integrated luminosity. The JES uncertainty, evaluated separately for AK7 and AK4 jets, is 1–3 % in the central region (|y| < 2) and increases to 7–8 % in the forward rapidity region (3.2 < |y| < 4.7) [23]. The JES uncertainty also includes the uncertainty carried by the charged hadron subtraction. The resulting uncertainties in the doubledifferential inclusive jet cross section range between 8 % at central rapidities and low pT to 65 % at forward rapidities and the highest pT. The uncertainty in the integrated luminosity (2.7 % [36]) propagates directly to the cross section. The unfolding procedure is affected by uncertainties in the jet energy resolution (JER) parametrisation. Alternative response matrices are used to unfold the measured spectra. They are built by varying the JER parameters within their uncertainties [23]. The JER uncertainty introduces a 1–2 % uncertainty in the measured cross section. The model dependence of the theoretical pT spectrum also affects the response matrix and thus the unfolding, but this uncertainty has negligible effects on the cross section measurement. The model dependence is checked using various PDF sets to calculate the theoretical pT spectrum. Finally, an uncertainty of 1 % is assigned to the cross section to account for residual effects of small inefficiencies from jet identification [15]. The total experimental systematic uncertainty of the measured cross section is obtained by summing in quadrature the individual contributions from JES, luminosity, JER, and jet identification uncertainties. 5 Theoretical predictions 5.1 Predictions from fixed-order calculations in pQCD The theoretical predictions for the jet cross section are calculated at NLO accuracy in pQCD and are evaluated by using NLOJet++ within the framework of fastNLO. The cross sections are calculated at NLO for single inclusive jet production. The renormalisation and the factorisation scales (μr and μ f ) are chosen to be equal to the jet pT. Five quarks are assumed to be massless in the calculation, which is performed using four different PDF sets with NLO accuracy: CT14 [34], HERAPDF1.5 [37], MMHT2014 [38], and NNPDF3.0 [39], with the default values of the strong coupling αS (MZ) = 0.1180, 0.1176, 0.1200, and 0.1180, respectively. The theoretical uncertainties are evaluated as the quadratic sum of the scale, PDF, αS , and NP uncertainties. The scale uncertainty is calculated by varying μr and μ f in the following six combinations: (μr / pT, μ f / pT) = (1/2,1/2), (1/2,1), (1,1/2), (1,2), (2,1) and (2,2). The (asymmetric) scale uncertainty is determined through the maximal upwards and downwards deviations with respect to cross sections obtained with the default setting. The PDF and αS uncertainties are calculated according to the prescription of CT14 at the 90 % confidence level and scaled down to a 68.3 % confidence level. The impact of NP effects, i.e. MPI and HAD effects, is evaluated by using samples obtained from different MC event generators with a simulation of PS and MPI contributions. The following MC event generators are used to estimate the NP corrections: LO pythia8 with tune CUETM1, iton1.25 Simulation NP correction value NP correction uncertainty LO herwig++ 2.7.0 [40] with tunes UE-EE-5C [41] and CUETS1 [26], and NLO powheg [42–44]. The matrix element calculation performed with powheg is interfaced to pythia8 with three different tunes (CUETS1-CTEQ6L1, CUETS1-HERAPDF, and CUETM1) for the simulation of the underlying-event (UE) contributions. The cross section ratios between a nominal event generation interfaced to the simulation of UE contributions, and a sample without HAD and MPI effects are taken as correction separately in each considered rapidity range. In a compact formulation, the NP correction factors can be defined as C NP = where σ PS+HAD+MPI is the cross section obtained with an MC sample simulating the contribution of PS, HAD, and MPI, while σ PS includes only PS effects. Corrections obtained with various NLO and LO event generators are evaluated separately for the AK7 and AK4 jets. The average of the results from the NLO and LO event generators defines the central value of the NP corrections, which are fitted to a power-law function in jet pT. The uncertainty in the NP corrections are evaluated by fitting the upper and lower values of the predictions of the different generators. The combinations of PDF sets, matrix element calculations, and UE tunes used to evaluate the NP corrections are validated on UE, minimum bias and jet variables, and they are able to reproduce a wide set of observables [26]. The NP corrections are shown in Figs. 1 and 2, respectively, for AK7 and AK4 jets in a central (0.5 < |y| < 1.0) and a forward rapidity bin (2.5 < |y| < 3.0). NP correction value NP correction uncertainty Fig. 1 Fits to the nonperturbative corrections obtained for inclusive AK7 jet cross sections as a function of jet pT for two rapidity bins: 0.5 < |y| < 1.0 (left) and 2.5 < |y| < 3.0 (right). The dotted 200 300 400 lines represent the uncertainty bands, which are evaluated by fitting the envelopes of the predictions of the different generators used itco1.02 Simulation NP correction value NP correction uncertainty itco1.02 Simulation 200 300 400 NP correction value NP correction uncertainty Fig. 2 Fits to the nonperturbative corrections obtained for inclusive AK4 jet cross sections as a function of jet pT for two rapidity bins: 0.5 < |y| < 1.0 (left) and 2.5 < |y| < 3.0 (right). The dotted lines represent the uncertainty bands, which are evaluated by fitting the envelopes of the predictions of the different generators used Fig. 3 Electroweak correction factors for the seven rapidity bins for the AK7 (left) and AK4 (right) jets as a function of jet pT The NP corrections for the AK7 jets are ≈15 % (13 %) for pT ∼ 114 GeV in the region 0.5 < |y| < 1.0 (2.5 < |y| < 3.0) and decrease rapidly for increasing pT, flattening at values of ≈1 for pT ∼ 200–300 GeV, depending on the considered rapidity range. Because of the smaller cone size, AK4 jets are less affected by the MPI and HAD effects. In particular, the additional energy produced by MPI shrinks for decreasing radii R, while the out-of-cone losses due to HAD effects increase for smaller radii R. These two effects are responsible for NP corrections that fall below 1 for AK4 jets with pT > 200 GeV at central rapidity. The NP corrections for AK4 jets are very close to unity in the phase space considered. For both cone sizes, the uncertainty assigned to the NP corrections is of the order of 1–2 %. Electroweak effects, which arise from the virtual exchanges of massive gauge W and Z bosons, become sizable at high jet pT and central rapidity. Corrections to electroweak effects are shown in Fig. 3 for both AK7 and AK4 jets [45]. They range between 0.96 and 1.05, depending on the jet pT and rapidity, and are less than 3 % for pT < 1 TeV and very similar between the two cone sizes. For jet measurements performed at a centre-of-mass energy of 7 TeV [46], electroweak corrections of 10–15 % are observed for jet pT > 1 TeV in the |y| < 1.0 range, decreasing below 2 % for lower pT, independent of the jet rapidity. Electroweak corrections are applied to the NLOJet++ predictions in a similar manner to the NP contributions. 5.2 Predictions from fixed-order calculations matched to parton shower simulations The predictions from different MC event generators are compared to data. The herwig++ and the pythia8 event generators are considered. Both of them are based on an LO 2 → 2 matrix element calculation. The pythia8 event generator simulates parton showers ordered in pT and uses the Lund string model [47] for HAD, while herwig++ generates parton showers through angular-ordered emissions and uses a cluster fragmentation model [48] for HAD. The contribution of MPI is simulated in both pythia8 and herwig++. In particular, pythia8 applies a model [49] where MPI are interleaved with parton showering, while herwig++ models the overlap between the colliding protons through a Fourier transform of the electromagnetic form factor, which plays the role of an effective inverse proton radius. Depending on the amount of proton overlap, the contribution of generated MPI varies in the simulation. The MPI parameters of both generators are tuned to measurements in proton–proton collisions at the LHC [26], while the HAD parameters are determined from fits to LEP data. For pythia8, the CUETM1 tune, which is based on NNPDF2.3LO [50, 51], is considered, while herwig++ uses the CUETS1 tune [26], based on the CTEQ6L1 PDF set [52]. Predictions based on NLO pQCD are also considered using the powheg package matched to pythia8 parton showers and including a simulation of MPI. The powheg sample uses the CT10nlo PDF set [53]. Various tunes in pythia8 are used for the UE simulation, which differ in the choice of the Fig. 5 Double-differential inclusive jet cross section as function of jet pT. On the left, data (points) and predictions from NLOJet++ based on the CT14 PDF set corrected for the NP and electroweak effects (line) are shown. On the right, data (points) and predictions from powheg (PH) + pythia8 (P8) with tune CUETM1 (line) are shown. Jets are clustered with the anti-kt algorithm (R = 0.4) < 71 pb-1 (13 TeV) |y| < 0.5 (x106) 0.5 < |y| < 1.0 (x105) 1.0 < |y| < 1.5 (x104) 1.5 < |y| < 2.0 (x103) 2.0 < |y| < 2.5 (x102) 2.5 < |y| < 3.0 (x101) 3.2 < |y| < 4.7 (x100) < 71 pb-1 (13 TeV) |y| < 0.5 (x106) 0.5 < |y| < 1.0 (x105) 1.0 < |y| < 1.5 (x104) 1.5 < |y| < 2.0 (x103) 2.0 < |y| < 2.5 (x102) 2.5 < |y| < 3.0 (x101) 3.2 < |y| < 4.7 (x100) CMS < 71 pb-1 (13 TeV) |y| < 0.5 (x106) 0.5 < |y| < 1.0 (x105) 1.0 < |y| < 1.5 (x104) 1.5 < |y| < 2.0 (x103) 2.0 < |y| < 2.5 (x102) 2.5 < |y| < 3.0 (x101) 3.2 < |y| < 4.7 (x100) Fig. 4 Double-differential inclusive jet cross section as function of jet pT. On the left, data (points) and predictions from NLOJet++ based on the CT14 PDF set corrected for the NP and electroweak effects (line) are shown. On the right, data (points) and predictions from powheg (PH) + pythia8 (P8) with tune CUETM1 (line) are shown. Jets are clustered with the anti-kt algorithm (R = 0.7) 71 pb-1 (13 TeV) 71 pb-1 (13 TeV) 71 pb-1 (13 TeV) 2 Anti-kt R = 0.7 0.5 < |y| < 1.0 2 Anti-kt R = 0.7 1.5 < |y| < 2.0 Anti-kt R = 0.7 2.5 < |y| < 3.0 o it a R0.5 o it a R0.5 +2.5 + t e J 2 O L N1.5 o t ito 1 a R 0.5 2 Anti-kt R = 0.7 2 Anti-kt R = 0.7 1.0 < |y| < 1.5 2.0 < |y| < 2.5 2.5 4 1 T C + + t e J1.5 O L N o it a R0.5 2.5 4 1 T C + + t e J1.5 O L N o it a R0.5 + t e J O1.5 L N t 1 o o it a R0.5 Anti-kt R = 0.7 3.2 < |y| < 4.7 +2.5 + t e J 2 O L N1.5 o t ito 1 a R 0.5 44 pb-1 (13 TeV) Fig. 6 Ratio of measured values to theoretical prediction from NLOJet++ using the CT14 PDF set and corrected for the NP and electroweak effects. Predictions employing three other PDF sets are also shown for comparison. Jets are clustered with the anti-kt algorithm with a distance parameter of 0.7. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic 71 pb-1 (13 TeV) 71 pb-1 (13 TeV) 71 pb-1 (13 TeV) 2.5 4 1 T C + + t e J1.5 O L N o it a R0.5 2.5 4 1 T C + + t e J1.5 O L N o it a R0.5 + t e J O1.5 L N t 1 o o it a R0.5 2 Anti-kt R = 0.4 2 Anti-kt R = 0.4 1.0 < |y| < 1.5 2.0 < |y| < 2.5 71 pb-1 (13 TeV) 71 pb-1 (13 TeV) 71 pb-1 (13 TeV) 2 Anti-kt R = 0.4 0.5 < |y| < 1.0 2 Anti-kt R = 0.4 1.5 < |y| < 2.0 Anti-kt R = 0.4 2.5 < |y| < 3.0 o it a R0.5 o it a R0.5 +2.5 + t e J 2 O L N1.5 o t ito 1 a R 0.5 71 pb-1 (13 TeV) 71 pb-1 (13 TeV) 71 pb-1 (13 TeV) Anti-kt R = 0.4 3.2 < |y| < 4.7 +2.5 + t e J 2 O L N1.5 o t ito 1 a R 0.5 44 pb-1 (13 TeV) Fig. 7 Ratio of measured values to theoretical prediction from NLOJet++ using the CT14 PDF set and corrected for the NP and electroweak effects. Predictions employing three other PDF sets are also shown for comparison. Jets are clustered with the anti-kt algorithm with a distance parameter of 0.4. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic 71 pb-1 (13 TeV) 71 pb-1 (13 TeV) 71 pb-1 (13 TeV) E U2.5 C 8 P 2 + H P1.5 o t E U2.5 C 8 P 2 + H P1.5 o t 44 pb-1 (13 TeV) 71 pb-1 (13 TeV) 71 pb-1 (13 TeV) 71 pb-1 (13 TeV) 120140160180200220 Fig. 8 Ratio of measured values to predictions from powheg (PH) + pythia8 (P8) with tune CUETM1. Predictions employing four other MC generators are also shown for comparison, where PH, P8, and Hpp stands for powheg, pythia8, and herwig++ (HPP), respectively. Jets are clustered with the anti-kt algorithm with a distance parameter of 0.7. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties 71 pb-1 (13 TeV) 71 pb-1 (13 TeV) 71 pb-1 (13 TeV) Anti-kt R = 0.4 3.2 < |y| < 4.7 EU 2 Anti-kt R = 0.4 0.5 < |y| < 1.0 EU 2 Anti-kt R = 0.4 1.5 < |y| < 2.0 C 8 P1.5 + H P o it a R0.5 C 8 P1.5 + H P o it a R0.5 Anti-kt R = 0.4 2.5 < |y| < 3.0 44 pb-1 (13 TeV) EU 2 Anti-kt R = 0.4 EU 2 Anti-kt R = 0.4 1.0 < |y| < 1.5 EU 2 Anti-kt R = 0.4 2.0 < |y| < 2.5 C 8 P1.5 + H P o it a R0.5 C 8 P1.5 + H P o it a R0.5 C 8 P1.5 + H P o it a R0.5 Fig. 9 Ratio of measured values to predictions from powheg (PH) + pythia8 (P8) with tune CUETM1. Predictions employing four other MC generators are also shown for comparison, where PH, P8, and Hpp stands for powheg, pythia8, and herwig++ (HPP), respectively. Jets are clustered with the anti-kt algorithm with a distance parameter of 0.4. The error bars correspond to the statistical uncertainties of the data and the shaded bands to the total experimental systematic uncertainties 71 pb-1 (13 TeV) 71 pb-1 (13 TeV) 71 pb-1 (13 TeV) PDF set and the HAD parameters: the CUETM1, and tunes CUETS1-CTEQL1 and CUETS1-HERAPDF, which use the CTEQ6L1 and the HERAPDF1.5LO [54] PDF sets, respectively. The HAD parameters for the CUETM1 tune are taken from the Monash tune [55], while the 4C tune provides these in both CUETS1 tunes. All these combinations of powheg matrix element and UE-simulation tunes reproduce with very high precision the UE and jet observables at various collision energies [26]. 6 Comparison of theoretical predictions and data Figures 4 and 5 show the double-differential inclusive jet cross section measurements, presented as a function of pT for seven |y| ranges, after unfolding for detector effects, using the anti-kt algorithm with R = 0.7 and 0.4, respectively. The measurements are compared to the NLOJet++ predictions based on the CT14 PDF set, corrected for NP and electroweak effects (left), and to the predictions from powheg + pythia8 with tune CUETM1 (right). The data are consistent with the predictions over a wide range of jet pT from 114 GeV up to 2 TeV. The ratios of data over the NLOJet++ predictions using the CT14 PDF set are shown in Fig. 6 for the AK7 jets. The error bars on the points correspond to the statistical uncertainties, and the shaded bands correspond to the total experimental systematic uncertainties. For comparison, predictions employing three alternative PDF sets are also shown. Figure 7 shows the results for the AK4 jets. Overall, a good agreement within the uncertainties is observed between the data and predictions in the entire kinematic range studied, for both jet cone sizes. However, for R = 0.4, the cross sections are systematically overestimated by about 5–10 %, while a better description is provided for jets reconstructed with R = 0.7. The relatively poor agreement for R = 0.4 is due to PS and soft-gluon resummation contributions, which are missing in fixed-order calculations, and that are more relevant for smaller jet cone sizes because of out-of-cone effects. The ratios of data over predictions from powheg + pythia8 with tune CUETM1 are shown in Figs. 8 and 9 for the AK7(AK4) jets. The error bars on the points correspond to the statistical uncertainties and the shaded bands to the total experimental systematic uncertainties. For comparison, four other MC predictions are also shown. There is an overall good level of agreement within the uncertainties between data and predictions from powheg + pythia8 with various tunes for both cone sizes, in the entire kinematic range studied. The agreement of data with pythia8 and herwig++ is poor in absolute scale. The herwig++ event generator shows good agreement with the data in shape for all rapidity bins, 7 Summary A measurement of the double-differential cross section as a function of jet pT and absolute rapidity |y| is presented for tcwololijseitosniszeast √R = 0.4 and 0.7 using data from proton–proton s = 13 TeV collected with the CMS detector. Data samples corresponding to integrated luminosities of 71 and 44 pb−1 are used for absolute rapidities |y| < 3 and for the forward region 3.2 < |y| < 4.7, respectively. As expected for LO predictions, the MC event generators pythia8 and herwig++ exhibit significant discrepancies in absolute scale with respect to data, which are somewhat more pronounced for the case of herwig++ . In contrast, the shape of the inclusive jet pT distribution is well described by herwig++ in all rapidity bins. Predictions from pythia8 start deviating from the observed shape as |y| increases. In the comparison between data and predictions at NLO in perturbative QCD including corrections for nonperturbative and electroweak effects, it is observed that jet cross sections for the larger jet size of R = 0.7 are accurately described, while for R = 0.4 theory overestimates the cross section by 5–10 % almost globally. In contrast, NLO predictions matched to parton showers as performed with powheg + pythia8 for two different tunes, perform equally well for both jet sizes. This result is consistent with the previous measurement performed at √s = 7 TeV [15], where it was observed that powheg + pythia8 correctly describes the R dependence of the inclusive jet cross section, while fixedorder predictions at NLO were insufficient in that respect. This measurement is a first indication that jet physics is as well understood at √s = 13 TeV as at smaller centreof-mass energies in the phase space accessible with the new data. Acknowledgments We would like to thank A. Huss for providing us with the electroweak correction factors. We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at CERN and at other CMS institutes for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centres and personnel of the Worldwide LHC Computing Grid for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies: BMWFW and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES and CSF (Croatia); RPF (Cyprus); MoER, ERC IUT and ERDF (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NIH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MBIE (New Zealand); PAEC (Pakistan); MSHE and NSC (Poland); FCT (Portugal); JINR (Dubna); MON, RosAtom, RAS and RFBR (Russia); MESTD (Serbia); SEIDI and CPAN (Spain); Swiss Funding Agencies (Switzerland); MST (Taipei); ThEPCenter, IPST, STAR and NSTDA (Thailand); TUBITAK and TAEK (Turkey); NASU and SFFR (Ukraine); STFC (United Kingdom); DOE and NSF (USA). Individuals have received support from the Marie-Curie programme and the European Research Council and EPLANET (European Union); the Leventis Foundation; the A. P. Sloan Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science Policy Office; the Fonds pour la Formation à la Recherche dans l’Industrie et dans l’Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWTBelgium); the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Council of Science and Industrial Research, India; the HOMING PLUS programme of the Foundation for Polish Science, cofinanced from European Union, Regional Development Fund; the Mobility Plus programme of the Ministry of Science and Higher Education (Poland); the OPUS programme of the National Science Center (Poland); the Thalis and Aristeia programmes cofinanced by EU-ESF and the Greek NSRF; the National Priorities Research Program by Qatar National Research Fund; the Programa Clarín-COFUND del Principado de Asturias; the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University (Thailand); the Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand); and the Welch Foundation, contract C-1845. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecomm ons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Funded by SCOAP3. CMS Collaboration Yerevan Physics Institute, Yerevan, Armenia V. Khachatryan, A. M. Sirunyan, A. Tumasyan National Centre for Particle and High Energy Physics, Minsk, Belarus V. Mossolov, N. Shumeiko, J. Suarez Gonzalez Universiteit Antwerpen, Antwerp, Belgium S. Alderweireldt, E. A. De Wolf, X. Janssen, A. Knutsson, J. Lauwers, M. Van De Klundert, H. Van Haevermaet, P. Van Mechelen, N. Van Remortel, A. Van Spilbeeck Université Catholique de Louvain, Louvain-la-Neuve, Belgium C. Beluffi3, O. Bondu, S. Brochet, G. Bruno, A. Caudron, L. Ceard, S. De Visscher, C. Delaere, M. Delcourt, L. Forthomme, B. Francois, A. Giammanco, A. Jafari, P. Jez, M. Komm, V. Lemaitre, A. Magitteri, A. Mertens, M. Musich, C. Nuttens, K. Piotrzkowski, L. Quertenmont, M. Selvaggi, M. Vidal Marono, S. Wertz Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, Brazil W. L. Aldá Júnior, F. L. Alves, G. A. Alves, L. Brito, M. Hamer, C. Hensel, A. Moraes, M. E. Pol, P. Rebello Teles Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil E. Belchior Batista Das Chagas, W. Carvalho, J. Chinellato4, A. Custódio, E. M. Da Costa, G. G. Da Silveira, D. De Jesus Damiao, C. De Oliveira Martins, S. Fonseca De Souza, L. M. Huertas Guativa, H. Malbouisson, D. Matos Figueiredo, C. Mora Herrera, L. Mundim, H. Nogima, W. L. Prado Da Silva, A. Santoro, A. Sznajder, E. J. Tonelli Manganote4, A. Vilela Pereira Universidade Estadual Paulistaa , Universidade Federal do ABCb, São Paulo, Brazil S. Ahujaa , C. A. Bernardesb, S. Dograa , T. R. Fernandez Perez Tomeia , E. M. Gregoresb, P. G. Mercadanteb, C. S. Moona,5, S. F. Novaesa , Sandra S. Padulaa , D. Romero Abadb, J. C. Ruiz Vargas Institute for Nuclear Research and Nuclear Energy, Sofia, Bulgaria A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, M. Rodozov, S. Stoykova, G. Sultanov, M. Vutova Institute Rudjer Boskovic, Zagreb, Croatia V. Brigljevic, D. Ferencek, K. Kadija, S. Micanovic, L. Sudic Universidad San Francisco de Quito, Quito, Ecuador E. Carrera Jarrin Academy of Scientific Research and Technology of the Arab Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, Egypt S. Elgammal9, A. Mohamed10, Y. Mohammed11, E. Salama9,12 National Institute of Chemical Physics and Biophysics, Tallinn, Estonia B. Calpas, M. Kadastik, M. Murumaa, L. Perrini, M. Raidal, A. Tiko, C. Veelken Laboratoire Leprince-Ringuet, Ecole Polytechnique, IN2P3-CNRS, Palaiseau, France A. Abdulsalam, I. Antropov, S. Baffioni, F. Beaudette, P. Busson, L. Cadamuro, E. Chapon, C. Charlot, O. Davignon, R. Granier de Cassagnac, M. Jo, S. Lisniak, P. Miné, I. N. Naranjo, M. Nguyen, C. Ochando, G. Ortona, P. Paganini, P. Pigard, S. Regnard, R. Salerno, Y. Sirois, T. Strebler, Y. Yilmaz, A. Zabi Institut Pluridisciplinaire Hubert Curien, Université de Strasbourg, Université de Haute Alsace Mulhouse, CNRS/IN2P3, Strasbourg, France J.-L. Agram13, J. Andrea, A. Aubin, D. Bloch, J.-M. Brom, M. Buttignol, E. C. Chabert, N. Chanon, C. Collard, E. Conte13, X. Coubez, J.-C. Fontaine13, D. Gelé, U. Goerlach, A.-C. Le Bihan, J. A. Merlin14, K. Skovpen, P. Van Hove Centre de Calcul de l’Institut National de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3, Villeurbanne, France S. Gadrat Institut de Physique Nucléaire de Lyon, Université de Lyon, Université Claude Bernard Lyon 1, CNRS-IN2P3, Villeurbanne, France S. Beauceron, C. Bernet, G. Boudoul, E. Bouvier, C. A. Carrillo Montoya, R. Chierici, D. Contardo, B. Courbon, P. Depasse, H. El Mamouni, J. Fan, J. Fay, S. Gascon, M. Gouzevitch, G. Grenier, B. Ille, F. Lagarde, I. B. Laktineh, M. Lethuillier, L. Mirabito, A. L. Pequegnot, S. Perries, A. Popov15, D. Sabes, V. Sordini, M. Vander Donckt, P. Verdier, S. Viret I. Physikalisches Institut, RWTH Aachen University, Aachen, Germany C. Autermann, S. Beranek, L. Feld, A. Heister, M. K. Kiesel, K. Klein, M. Lipinski, A. Ostapchuk, M. Preuten, F. Raupach, S. Schael, C. Schomakers, J. F. Schulte, J. Schulz, T. Verlage, H. Weber, V. Zhukov15 Deutsches Elektronen-Synchrotron, Hamburg, Germany M. Aldaya Martin, I. Asin, K. Beernaert, O. Behnke, U. Behrens, A. A. Bin Anuar, K. Borras16, A. Campbell, P. Connor, C. Contreras-Campana, F. Costanza, C. Diez Pardos, G. Dolinska, G. Eckerlin, D. Eckstein, E. Gallo17, J. Garay Garcia, A. Geiser, A. Gizhko, J. M. Grados Luyando, P. Gunnellini, A. Harb, J. Hauk, M. Hempel18, H. Jung, A. Kalogeropoulos, O. Karacheban18, M. Kasemann, J. Keaveney, J. Kieseler, C. Kleinwort, I. Korol, W. Lange, A. Lelek, J. Leonard, K. Lipka, A. Lobanov, W. Lohmann18, R. Mankel, I.-A. Melzer-Pellmann, A. B. Meyer, G. Mittag, J. Mnich, A. Mussgiller, E. Ntomari, D. Pitzl, R. Placakyte, A. Raspereza, B. Roland, M. Ö. Sahin, P. Saxena, T. Schoerner-Sadenius, C. Seitz, S. Spannagel, N. Stefaniuk, K. D. Trippkewitz, G. P. Van Onsem, R. Walsh, C. Wissing Institute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, Greece G. Anagnostou, G. Daskalakis, T. Geralis, V. A. Giakoumopoulou, A. Kyriakis, D. Loukas, I. Topsis-Giotis National and Kapodistrian University of Athens, Athens, Greece A. Agapitos, S. Kesisoglou, A. Panagiotou, N. Saoulidou, E. Tziaferi MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös Loránd University, Budapest, Hungary N. Filipovic Panjab University, Chandigarh, India S. Bansal, S. B. Beri, V. Bhatnagar, R. Chawla, R. Gupta, U. Bhawandeep, A. K. Kalsi, A. Kaur, M. Kaur, R. Kumar, A. Mehta, M. Mittal, J. B. Singh, G. Walia Indian Institute of Science Education and Research (IISER), Pune, India S. Chauhan, S. Dube, A. Kapoor, K. Kothekar, A. Rane, S. Sharma Institute for Research in Fundamental Sciences (IPM), Tehran, Iran H. Bakhshiansohi, H. Behnamian, S. Chenarani26, E. Eskandari Tadavani, S. M. Etesami26, A. Fahim27, M. Khakzad, M. Mohammadi Najafabadi, M. Naseri, S. Paktinat Mehdiabadi, F. Rezaei Hosseinabadi, B. Safarzadeh28, M. Zeinali University College Dublin, Dublin, Ireland M. Felcini, M. Grunewald INFN Sezione di Baria , Università di Barib, Politecnico di Baric, Bari, Italy M. Abbresciaa,b, C. Calabriaa,b, C. Caputoa,b, A. Colaleoa , D. Creanzaa,c, L. Cristellaa,b, N. De Filippisa,c, M. De Palmaa,b, L. Fiorea , G. Iasellia,c, G. Maggia,c, M. Maggia , G. Minielloa,b, S. Mya,b, S. Nuzzoa,b, A. Pompilia,b, G. Pugliesea,c, R. Radognaa,b, A. Ranieria , G. Selvaggia,b, L. Silvestrisa,14, R. Vendittia,b INFN Laboratori Nazionali di Frascati, Frascati, Italy L. Benussi, S. Bianco, F. Fabbri, D. Piccolo, F. Primavera14 INFN Sezione di Genovaa , Università di Genovab, Genova, Italy V. Calvellia,b, F. Ferroa , M. Lo Veterea,b, M. R. Mongea,b, E. Robuttia , S. Tosia,b INFN Sezione di Milano-Bicoccaa , Università di Milano-Bicoccab, Milan, Italy L. Brianza, M. E. Dinardoa,b, S. Fiorendia,b, S. Gennaia , A. Ghezzia,b, P. Govonia,b, S. Malvezzia , R. A. Manzonia,b,14, B. Marzocchia,b, D. Menascea , L. Moronia , M. Paganonia,b, D. Pedrinia , S. Pigazzini, S. Ragazzia,b, T. Tabarelli de Fatisa,b INFN Sezione di Napolia , Università di Napoli ‘Federico II’b, Napoli, Italy, Università della Basilicatac, Potenza, Italy, Università G. Marconid , Rome, Italy S. Buontempoa , N. Cavalloa,c, G. De Nardo, S. Di Guidaa,d,14, M. Espositoa,b, F. Fabozzia,c, A. O. M. Iorioa,b, G. Lanzaa , L. Listaa , S. Meolaa,d,14, M. Merolaa , P. Paoluccia,14, C. Sciaccaa,b, F. Thyssen INFN Sezione di Padovaa , Università di Padovab, Padua, Italy, Università di Trentoc, Trento, Italy P. Azzia,14, N. Bacchettaa , M. Bellatoa , L. Benatoa,b, D. Biselloa,b, A. Bolettia,b, R. Carlina,b, A. Carvalho Antunes De Oliveiraa,b, P. Checchiaa , M. Dall’Ossoa,b, P. De Castro Manzanoa , T. Dorigoa , U. Gasparinia,b, S. Lacapraraa , M. Margonia,b, A. T. Meneguzzoa,b, F. Montecassianoa , M. Passaseoa , J. Pazzinia,b,14, N. Pozzobona,b, P. Ronchesea,b, F. Simonettoa,b, E. Torassa a , S. Venturaa , M. Zanetti, P. Zottoa,b, A. Zucchettaa,b INFN Sezione di Paviaa , Università di Paviab, Pavia, Italy A. Braghieria , A. Magnania,b, P. Montagnaa,b, S. P. Rattia,b, V. Rea , C. Riccardia,b, P. Salvinia , I. Vaia,b, P. Vituloa,b INFN Sezione di Perugiaa , Università di Perugiab, Perugia, Italy L. Alunni Solestizia,b, G. M. Bileia , D. Ciangottinia,b, L. Fanòa,b, P. Laricciaa,b, R. Leonardia,b, G. Mantovania,b, M. Menichellia , A. Sahaa , A. Santocchiaa,b INFN Sezione di Pisaa , Università di Pisab, Scuola Normale Superiore di Pisac, Pisa, Italy K. Androsova,29, P. Azzurria,14, G. Bagliesia , J. Bernardinia , T. Boccalia , R. Castaldia , M. A. Cioccia,29, R. Dell’Orsoa , S. Donatoa,c, G. Fedi, A. Giassia , M. T. Grippoa,29, F. Ligabuea,c, T. Lomtadzea , L. Martinia,b, A. Messineoa,b, F. Pallaa , A. Rizzia,b, A. Savoy-Navarroa,30, P. Spagnoloa , R. Tenchinia , G. Tonellia,b, A. Venturia , P. G. Verdinia INFN Sezione di Romaa , Università di Romab, Rome, Italy L. Baronea,b, F. Cavallaria , M. Cipriania,b, G. D’imperioa,b,14, D. Del Rea,b,14, M. Diemoza , S. Gellia,b, C. Jordaa , E. Longoa,b, F. Margarolia,b, P. Meridiania , G. Organtinia,b, R. Paramattia , F. Preiatoa,b, S. Rahatloua,b, C. Rovellia , F. Santanastasioa,b INFN Sezione di Torinoa , Università di Torinob, Turin, Italy, Università del Piemonte Orientalec, Novara, Italy N. Amapanea,b, R. Arcidiaconoa,c,14, S. Argiroa,b, M. Arneodoa,c, N. Bartosika , R. Bellana,b, C. Biinoa , N. Cartigliaa , M. Costaa,b, R. Covarellia,b, A. Deganoa,b, N. Demariaa , L. Fincoa,b, B. Kiania,b, C. Mariottia , S. Masellia , E. Migliorea,b, V. Monacoa,b, E. Monteila,b, M. M. Obertinoa,b, L. Pachera,b, N. Pastronea , M. Pelliccionia , G. L. Pinna Angionia,b, F. Raveraa,b, A. Romeroa,b, M. Ruspaa,c, R. Sacchia,b, K. Shchelinaa,b, V. Solaa , A. Solanoa,b, A. Staianoa , P. Traczyka,b INFN Sezione di Triestea , Università di Triesteb, Trieste, Italy S. Belfortea , M. Casarsaa , F. Cossuttia , G. Della Riccaa,b, C. La Licataa,b, A. Schizzia,b, A. Zanettia Centro de Investigacion y de Estudios Avanzados del IPN, Mexico City, Mexico H. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-De La Cruz33, A. Hernandez-Almada, R. Lopez-Fernandez, J. Mejia Guisao, A. Sanchez-Hernandez Universidad Iberoamericana, Mexico City, Mexico S. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia Benemerita Universidad Autonoma de Puebla, Puebla, Mexico S. Carpinteyro, I. Pedraza, H. A. Salazar Ibarguen, C. Uribe Estrada Universidad Autónoma de San Luis Potosí, San Luis Potosí, Mexico A. Morelos Pineda University of Auckland, Auckland, New Zealand D. Krofcheck University of Canterbury, Christchurch, New Zealand P. H. Butler National Centre for Nuclear Research, Swierk, Poland H. Bialkowska, M. Bluj, B. Boimska, T. Frueboes, M. Górski, M. Kazana, K. Nawrocki, K. Romanowska-Rybinska, M. Szleper, P. Zalewski Laboratório de Instrumentação e Física Experimental de Partículas, Lisbon, Portugal P. Bargassa, C. Beirão Da Cruz E Silva, A. Di Francesco, P. Faccioli, P. G. Ferreira Parracho, M. Gallinaro, J. Hollar, N. Leonardo, L. Lloret Iglesias, M. V. Nemallapudi, J. Rodrigues Antunes, J. Seixas, O. Toldaiev, D. Vadruccio, J. Varela, P. Vischia Petersburg Nuclear Physics Institute, Gatchina (St. Petersburg), Russia L. Chtchipounov, V. Golovtsov, Y. Ivanov, V. Kim37, E. Kuznetsova38, V. Murzin, V. Oreshkin, V. Sulimov, A. Vorobyev Institute for Nuclear Research, Moscow, Russia Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, M. Kirsanov, N. Krasnikov, A. Pashenkov, D. Tlisov, A. Toropin National Research Nuclear University ‘Moscow Engineering Physics Institute’ (MEPhI), Moscow, Russia M. Chadeeva39, M. Danilov39, O. Markin State Research Center of Russian Federation, Institute for High Energy Physics, Protvino, Russia I. Azhgirey, I. Bayshev, S. Bitioukov, D. Elumakhov, V. Kachanov, A. Kalinin, D. Konstantinov, V. Krychkine, V. Petrov, R. Ryutin, A. Sobol, S. Troshin, N. Tyurin, A. Uzunian, A. Volkov Centro de Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain J. Alcaraz Maestre, E. Calvo, M. Cerrada, M. Chamizo Llatas, N. Colino, B. De La Cruz, A. Delgado Peris, A. Escalante Del Valle, C. Fernandez Bedoya, J. P. Fernández Ramos, J. Flix, M. C. Fouz, P. Garcia-Abia, O. Gonzalez Lopez, S. Goy Lopez, J. M. Hernandez, M. I. Josa, E. Navarro De Martino, A. Pérez-Calero Yzquierdo, J. Puerta Pelayo, A. Quintario Olmeda, I. Redondo, L. Romero, M. S. Soares Universidad Autónoma de Madrid, Madrid, Spain J. F. de Trocóniz, M. Missiroli, D. Moran Universidad de Oviedo, Oviedo, Spain J. Cuevas, J. Fernandez Menendez, I. Gonzalez Caballero, J. R. González Fernández, E. Palencia Cortezon, S. Sanchez Cruz, J. M. Vizan Garcia Instituto de Física de Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, Spain I. J. Cabrillo, A. Calderon, J. R. Castiñeiras De Saa, E. Curras, M. Fernandez, J. Garcia-Ferrero, G. Gomez, A. Lopez Virto, J. Marco, C. Martinez Rivero, F. Matorras, J. Piedra Gomez, T. Rodrigo, A. Ruiz-Jimeno, L. Scodellaro, N. Trevisani, I. Vila, R. Vilar Cortabitarte Universität Zürich, Zurich, Switzerland T. K. Aarrestad, C. Amsler48, L. Caminada, M. F. Canelli, V. Chiochia, A. De Cosa, C. Galloni, A. Hinzmann, T. Hreus, B. Kilminster, C. Lange, J. Ngadiuba, D. Pinna, G. Rauco, P. Robmann, D. Salerno, Y. Yang National Taiwan University (NTU), Taipei, Taiwan Arun Kumar, P. Chang, Y. H. Chang, Y. W. Chang, Y. Chao, K. F. Chen, P. H. Chen, C. Dietz, F. Fiori, W.-S. Hou, Y. Hsiung, Y. F. Liu, R.-S. Lu, M. Miñano Moya, E. Paganis, A. Psallidas, J. F. Tsai, Y. M. Tzeng Institute for Scintillation Materials of National Academy of Science of Ukraine, Kharkiv, Ukraine B. Grynyov National Scientific Center, Kharkov Institute of Physics and Technology, Kharkov, Ukraine L. Levchuk, P. Sorokin Imperial College, London, UK M. Baber, R. Bainbridge, O. Buchmuller, A. Bundock, D. Burton, S. Casasso, M. Citron, D. Colling, L. Corpe, P. Dauncey, G. Davies, A. De Wit, M. Della Negra, P. Dunne, A. Elwood, D. Futyan, Y. Haddad, G. Hall, G. Iles, R. Lane, C. Laner, R. Lucas61, L. Lyons, A.-M. Magnan, S. Malik, L. Mastrolorenzo, J. Nash, A. Nikitenko47, J. Pela, B. Penning, M. Pesaresi, D. M. Raymond, A. Richards, A. Rose, C. Seez, A. Tapper, K. Uchida, M. Vazquez Acosta63, T. Virdee14, S. C. Zenz University of California, Los Angeles, USA R. Cousins, P. Everaerts, A. Florent, J. Hauser, M. Ignatenko, D. Saltzberg, E. Takasugi, V. Valuev, M. Weber University of California, San Diego, La Jolla, USA J. G. Branson, G. B. Cerati, S. Cittolin, M. Derdzinski, R. Gerosa, A. Holzner, D. Klein, J. Letts, I. Macneill, D. Olivito, S. Padhi, M. Pieri, M. Sani, V. Sharma, S. Simon, M. Tadel, A. Vartak, S. Wasserbaech64, C. Welke, J. Wood, F. Würthwein, A. Yagil, G. Zevi Della Porta University of California, Santa Barbara, Santa Barbara, USA R. Bhandari, J. Bradmiller-Feld, C. Campagnari, A. Dishaw, V. Dutta, K. Flowers, M. Franco Sevilla, P. Geffert, C. George, F. Golf, L. Gouskos, J. Gran, R. Heller, J. Incandela, N. Mccoll, S. D. Mullin, A. Ovcharova, J. Richman, D. Stuart, I. Suarez, C. West, J. Yoo Carnegie Mellon University, Pittsburgh, USA M. B. Andrews, V. Azzolini, A. Calamba, B. Carlson, T. Ferguson, M. Paulini, J. Russ, M. Sun, H. Vogel, I. Vorobiev University of Colorado Boulder, Boulder, USA J. P. Cumalat, W. T. Ford, F. Jensen, A. Johnson, M. Krohn, T. Mulholland, K. Stenson, S. R. Wagner Cornell University, Ithaca, USA J. Alexander, J. Chaves, J. Chu, S. Dittmer, N. Mirman, G. Nicolas Kaufman, J. R. Patterson, A. Rinkevicius, A. Ryd, L. Skinnari, W. Sun, S. M. Tan, Z. Tao, J. Thom, J. Tucker, P. Wittich Florida International University, Miami, USA S. Linn, P. Markowitz, G. Martinez, J. L. Rodriguez Florida Institute of Technology, Melbourne, USA M. M. Baarmand, V. Bhopatkar, S. Colafranceschi66, M. Hohlmann, D. Noonan, T. Roy, F. Yumiceva University of Illinois at Chicago (UIC), Chicago, USA M. R. Adams, L. Apanasevich, D. Berry, R. R. Betts, I. Bucinskaite, R. Cavanaugh, O. Evdokimov, L. Gauthier, C. E. Gerber, D. J. Hofman, P. Kurt, C. O’Brien, I. D. Sandoval Gonzalez, P. Turner, N. Varelas, Z. Wu, M. Zakaria, J. Zhang Johns Hopkins University, Baltimore, USA I. Anderson, B. Blumenfeld, A. Cocoros, N. Eminizer, D. Fehling, L. Feng, A. V. Gritsan, P. Maksimovic, M. Osherson, J. Roskes, U. Sarica, M. Swartz, M. Xiao, Y. Xin, C. You The University of Kansas, Lawrence, USA A. Al-bataineh, P. Baringer, A. Bean, J. Bowen, C. Bruner, J. Castle, R. P. KennyIII, A. Kropivnitskaya, D. Majumder, W. Mcbrayer, M. Murray, S. Sanders, R. Stringer, J. D. Tapia Takaki, Q. Wang Kansas State University, Manhattan, USA A. Ivanov, K. Kaadze, S. Khalil, M. Makouski, Y. Maravin, A. Mohammadi, L. K. Saini, N. Skhirtladze, S. Toda Lawrence Livermore National Laboratory, Livermore, USA D. Lange, F. Rebassoo, D. Wright University of Maryland, College Park, USA C. Anelli, A. Baden, O. Baron, A. Belloni, B. Calvert, S. C. Eno, C. Ferraioli, J. A. Gomez, N. J. Hadley, S. Jabeen, R. G. Kellogg, T. Kolberg, J. Kunkle, Y. Lu, A. C. Mignerey, Y. H. Shin, A. Skuja, M. B. Tonjes, S. C. Tonwar University of Mississippi, Oxford, USA J. G. Acosta, S. Oliveros University of Nebraska-Lincoln, Lincoln, USA E. Avdeeva, R. Bartek, K. Bloom, S. Bose, D. R. Claes, A. Dominguez, C. Fangmeier, R. Gonzalez Suarez, R. Kamalieddin, D. Knowlton, I. Kravchenko, A. Malta Rodrigues, F. Meier, J. Monroy, J. E. Siado, G. R. Snow, B. Stieger State University of New York at Buffalo, Buffalo, USA M. Alyari, J. Dolen, J. George, A. Godshalk, C. Harrington, I. Iashvili, J. Kaisen, A. Kharchilava, A. Kumar, A. Parker, S. Rappoccio, B. Roozbahani Northwestern University, Evanston, USA S. Bhattacharya, K. A. Hahn, A. Kubik, J. F. Low, N. Mucia, N. Odell, B. Pollack, M. H. Schmitt, K. Sung, M. Trovato, M. Velasco The Ohio State University, Columbus, USA J. Alimena, L. Antonelli, J. Brinson, B. Bylsma, L. S. Durkin, S. Flowers, B. Francis, A. Hart, C. Hill, R. Hughes, W. Ji, B. Liu, W. Luo, D. Puigh, B. L. Winer, H. W. Wulsin Princeton University, Princeton, USA S. Cooperstein, O. Driga, P. Elmer, J. Hardenbrook, P. Hebda, J. Luo, D. Marlow, T. Medvedeva, M. Mooney, J. Olsen, C. Palmer, P. Piroué, D. Stickland, C. Tully, A. Zuranski Purdue University, West Lafayette, USA A. Barker, V. E. Barnes, D. Benedetti, S. Folgueras, L. Gutay, M. K. Jha, M. Jones, A. W. Jung, K. Jung, D. H. Miller, N. Neumeister, B. C. Radburn-Smith, X. Shi, J. Sun, A. Svyatkovskiy, F. Wang, W. Xie, L. Xu Purdue University Calumet, Hammond, USA N. Parashar, J. Stupak University of Rochester, Rochester, USA B. Betchart, A. Bodek, P. de Barbaro, R. Demina, Y. t. Duh, T. Ferbel, M. Galanti, A. Garcia-Bellido, J. Han, O. Hindrichs, A. Khukhunaishvili, K. H. Lo, P. Tan, M. Verzetti Rutgers, The State University of New Jersey, Piscataway, USA J. P. Chou, E. Contreras-Campana, Y. Gershtein, T. A. Gómez Espinosa, E. Halkiadakis, M. Heindl, D. Hidas, E. Hughes, S. Kaplan, R. Kunnawalkam Elayavalli, S. Kyriacou, A. Lath, K. Nash, H. Saka, S. Salur, S. Schnetzer, D. Sheffield, S. Somalwar, R. Stone, S. Thomas, P. Thomassen, M. Walker University of Tennessee, Knoxville, USA M. Foerster, J. Heideman, G. Riley, K. Rose, S. Spanier, K. Thapa Wayne State University, Detroit, USA C. Clarke, R. Harr, P. E. Karchin, P. Lamichhane, J. Sturdy † Deceased 37: Also at St. Petersburg State Polytechnical University, St. Petersburg, Russia 38: Also at University of Florida, Gainesville, USA 39: Also at P.N. Lebedev Physical Institute, Moscow, Russia 40: Also at California Institute of Technology, Pasadena, USA 41: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia 42: Also at INFN Sezione di Roma Università di Roma, Rome, Italy 43: Also at National Technical University of Athens, Athens, Greece 44: Also at Scuola Normale e Sezione dell’INFN, Pisa, Italy 45: Also at National and Kapodistrian University of Athens, Athens, Greece 46: Also at Riga Technical University, Riga, Latvia 47: Also at Institute for Theoretical and Experimental Physics, Moscow, Russia 48: Also at Albert Einstein Center for Fundamental Physics, Bern, Switzerland 49: Also at Adiyaman University, Adiyaman, Turkey 50: Also at Mersin University, Mersin, Turkey 51: Also at Cag University, Mersin, Turkey 52: Also at Piri Reis University, Istanbul, Turkey 53: Also at Gaziosmanpasa University, Tokat, Turkey 54: Also at Ozyegin University, Istanbul, Turkey 55: Also at Izmir Institute of Technology, Izmir, Turkey 56: Also at Marmara University, Istanbul, Turkey 57: Also at Kafkas University, Kars, Turkey 58: Also at Istanbul Bilgi University, Istanbul, Turkey 59: Also at Yildiz Technical University, Istanbul, Turkey 60: Also at Hacettepe University, Ankara, Turkey 61: Also at Rutherford Appleton Laboratory, Didcot, UK 62: Also at School of Physics and Astronomy, University of Southampton, Southampton, UK 63: Also at Instituto de Astrofísica de Canarias, La Laguna, Spain 64: Also at Utah Valley University, Orem, USA 65: Also at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia 66: Also at Facoltà Ingegneria, Università di Roma, Rome, Italy 67: Also at Argonne National Laboratory, Argonne, USA 68: Also at Erzincan University, Erzincan, Turkey 69: Also at Mimar Sinan University, Istanbul, Istanbul, Turkey 70: Also at Texas A&M University at Qatar, Doha, Qatar 71: Also at Kyungpook National University, Taegu, Korea 1. ATLAS Collaboration, Measurement of the inclusive jet crosssection in pp collisions at √s = 2.76 TeV and comparison to the inclusive jet cross-section at √s = 7 TeV using the ATLAS detector . Eur. Phys. J. C 73 , 2509 ( 2013 ). doi:10.1140/epjc/ s10052- 013 - 2509 -4. arXiv: 1304 .4739 2. CMS Collaboration, Measurement of the inclusive jet cross section in pp collisions at √s = 2. 76 TeV ( 2015 ). arXiv: 1512 .06212. Accepted by Eur . Phys. J. C 3. ATLAS Collaboration, Measurement of inclusive jet and dijet cross sections in proton-proton collisions at 7 TeV centre-of-mass energy with the ATLAS detector . Eur. Phys. J. C 71 , 1512 ( 2011 ). doi:10. 1140/epjc/s10052- 010 - 1512 -2. arXiv: 1009 .5908 4. CMS Collaboration, Measurement of the inclusive jet cross section in pp collisions at √s = 7 TeV. Phys. Rev. Lett . 107 , 132001 ( 2011 ). doi:10.1103/PhysRevLett.107.132001. arXiv:1106.0208 5. ATLAS Collaboration, Measurement of inclusive jet and dijet production in pp collisions at √s = 7 TeV using the ATLAS detector . Phys. Rev. D 86 , 014022 ( 2012 ). doi:10.1103/PhysRevD.86. 014022. arXiv:1112.6297 6. CMS Collaboration, Measurements of differential jet cross sections in proton-proton collisions at √s = 7 TeV with the CMS detector . Phys. Rev. D 87 , 112002 ( 2013 ). doi:10.1103/PhysRevD. 87.112002. arXiv:1212.6660 7. ATLAS Collaboration, Measurement of the inclusive jet crosssection in proton-proton collisions at √s = 7 TeV using 4.5fb−1 of data with the ATLAS detector . JHEP 02 , 153 ( 2015 ). doi:10.1007/ JHEP02(2015)153 . arXiv: 1410 .8857. [Erratum: doi:10.1007/JHEP09(2015)141] 8. UA2 Collaboration, Observation of very large transverse momentum jets at the CERN p p¯ collider . Phys. Lett. B 118 , 203 ( 1982 ). doi:10.1016/ 0370 -269 3 9. UA1 Collaboration, Hadronic jet production at the CERN protonantiproton collider . Phys. Lett. B 132 , 214 ( 1983 ). doi:10.1016/ 0370 -2693(83) 90254 - X 10. CDF Collaboration, Measurement of the inclusive jet cross section using the kT algorithm in p p¯ collisions at √s = 1.96 Tev with the CDF II detector . Phys. Rev. D 75 , 092006 ( 2007 ). doi:10.1103/ PhysRevD.75.092006. arXiv:hep-ex/ 0701051 [Erratum: doi:10. 1103/PhysRevD.75.119901] 11. D0 Collaboration, Measurement of the inclusive jet cross section in p p¯ collisions at √ s = 1.96 TeV. Phys. Rev. Lett . 101 , 062001 ( 2008 ). doi:10.1103/PhysRevLett.101.062001. arXiv:0802.2400 12. CDF Collaboration, Measurement of the inclusive jet cross section at the Fermilab Tevatron p p¯ collider using a cone-based jet algorithm . Phys. Rev. D 78 , 052006 ( 2008 ). doi:10.1103/PhysRevD. 78.052006. arXiv: 0807 .2204. [Erratum: doi:10.1103/PhysRevD. 79.119902] 13. M. Cacciari , G.P. Salam , G. Soyez , The anti-kt jet clustering algorithm . JHEP 04 , 063 ( 2008 ). doi:10.1088/ 1126 - 6708 /2008/04/063. arXiv: 0802 .1189 14. M. Cacciari , G.P. Salam , G. Soyez , FastJet user manual . Eur. Phys. J. C 72 , 1896 ( 2012 ). doi:10.1140/epjc/s10052- 012 - 1896 -2. arXiv: 1111 .6097 15. CMS Collaboration, Measurement of the ratio of inclusive jet cross sections using the anti-kT algorithm with radius parameters R = 0.5 and 0.7 in pp collisions at √s = 7 TeV. Phys. Rev. D 90 , 072006 ( 2014 ). doi:10.1103/PhysRevD.90.072006. arXiv:1406.0324 16. M. Dasgupta , L. Magnea , G.P. Salam , Non-perturbative QCD effects in jets at hadron colliders . JHEP 02 , 055 ( 2008 ). doi:10. 1088/ 1126 - 6708 /2008/02/055. arXiv: 0712 .3014 17. M. Dasgupta , F. Dreyer , G.P. Salam , G. Soyez , Small-radius jets to all orders in QCD . JHEP 04 , 039 ( 2015 ). doi:10.1007/ JHEP04(2015)039 . arXiv:1411.5182 18. M. Dasgupta , F.A. Dreyer , G.P. Salam , G. Soyez , Inclusive jet spectrum for small-radius jets (2016) . arXiv:1602.01110 19. CMS Collaboration, Particle-flow event reconstruction in CMS and performance for jets , taus, and E miss. CMS Physics Analysis SumT mary CMS-PAS-PFT-09-001 (2009) 20. CMS Collaboration, Commissioning of the particle-flow reconstruction in minimum-bias and jet events from pp collisions at 7 TeV . CMS Physics Analysis Summary CMS-PAS-PFT-10-002 (2010) 21. CMS Collaboration, The CMS experiment at the CERN LHC . JINST 3, S08004 ( 2008 ). doi:10.1088/ 1748 - 0221 /3/08/S08004 22. CMS Collaboration, The CMS high level trigger . Eur. Phys. J. C 46 , 605 ( 2006 ). doi:10.1140/epjc/s2006- 02495 -8. arXiv:hep-ex/0512077 23. CMS Collaboration, Determination of jet energy calibration and transverse momentum resolution in CMS . JINST 6, P11002 ( 2011 ). doi:10.1088/ 1748 - 0221 /6/11/P11002. arXiv: 1107 .4277 24. CMS Collaboration, Jet energy corrections and uncertainties. Detector performance plots for 2012 . CMS Detector Performance Report CMS-DP-2012-012 (2012) 25. T. Sjöstrand et al., An introduction to PYTHIA 8.2. Comput. Phys. Commun . 191 , 159 ( 2015 ). doi:10.1016/j.cpc. 2015 .01.024. arXiv:1410.3012 26. CMS Collaboration, Event generator tunes obtained from underlying event and multiparton scattering measurements . Eur. Phys. J. C 76 , 155 ( 2016 ). doi:10.1140/epjc/s10052- 016 - 3988 -x. arXiv:1512.00815 27. CMS Collaboration, Jet performance in pp collisions at √s = 7 TeV . CMS Physics Analysis Summary CMS-PAS-JME-10-003 (2010) 28. C. Buttar et al., Standard model handles and candles working group: tools and jets summary report ( 2008 ). arXiv:0803.0678 29. G. D'Agostini, A multidimensional unfolding method based on Bayes' theorem. Nucl. Instrum. Methods A 362 , 487 ( 1995 ). doi:10.1016/ 0168 -9002(95) 00274 - X 30. T. Adye , Unfolding algorithms and tests using RooUnfold, in PHYSTAT 2011 Workshop on Statistical Issues Related to Discovery Claims in Search Experiments and Unfolding, ed. by H. Prosper , L. Lyons , p. 313 . Geneva , Switzerland ( 2011 ). doi:10.5170/ CERN-2011-006.313. arXiv:1105.1160 31. Z. Nagy , Three-jet cross sections in hadron-hadron collisions at next-to-leading order . Phys. Rev. Lett . 88 , 122003 ( 2002 ). doi:10. 1103/PhysRevLett.88.122003. arXiv:hep-ph/0110315 32. Z. Nagy , Next-to-leading order calculation of three-jet observables in hadron-hadron collisions . Phys. Rev. D 68 , 094002 ( 2003 ). doi:10.1103/PhysRevD.68.094002. arXiv:hep-ph/0307268 33. D. Britzger , K. Rabbertz , F. Stober , M. Wobisch , New features in version 2 of the fastNLO project ( 2012 ). arXiv:1208.3641 34. S. Dulat et al., New parton distribution functions from a global analysis of quantum chromodynamics ( 2016 ). arXiv:1506.07443 35. GEANT4 Collaboration, GEANT4-a simulation toolkit . Nucl. Instrum. Methods A 506 , 250 ( 2003 ). doi:10.1016/ S0168-9002(03)01368- 8 36. CMS Collaboration, CMS luminosity measurement for the 2015 data taking period . CMS Physics Analysis Summary CMS-PASLUM-15-001 (2015) 37. ZEUS and H1 Collaborations, Combined measurement and QCD analysis of the inclusive e±p scattering cross sections at HERA . JHEP 01 , 109 ( 2010 ). doi:10.1007/ JHEP01(2010)109 . arXiv:0911.0884 38. L.A. Harland-Lang , A.D. Martin , P. Motylinski , R.S. Thorne , Parton distributions in the LHC era: MMHT 2014 PDFs. Eur . Phys. J. C 75 , 204 ( 2015 ). doi:10.1140/epjc/s10052- 015 - 3397 -6. arXiv: 1412 .3989 39. NNPDF Collaboration, Parton distributions for the LHC run II . JHEP 04 , 040 ( 2015 ). doi:10.1007/ JHEP04(2015)040 . arXiv:1410.8849 40. J. Bellm et al., Herwig++ 2.7 release note (2013). arXiv:1310.6877 41. M.H. Seymour , A. Siódmok , Constraining MPI models using σeff and recent Tevatron and LHC underlying event data . JHEP 10 , 113 ( 2013 ). doi:10.1007/ JHEP10(2013)113 . arXiv:1307.5015 42. P. Nason , A new method for combining NLO QCD with shower Monte Carlo algorithms . JHEP 11 , 040 ( 2004 ). doi:10.1088/ 1126 - 6708 /2004/11/040. arXiv:hep-ph/ 0409146 43. S. Frixione , P. Nason , C. Oleari , Matching NLO QCD computations with parton shower simulations: the POWHEG method . JHEP 11 , 070 ( 2007 ). doi:10.1088/ 1126 - 6708 /2007/11/070. arXiv: 0709 . 2092 44. S. Alioli et al., Jet pair production in POWHEG. JHEP 04 , 081 ( 2011 ). doi:10.1007/ JHEP04(2011)081 . arXiv:1012.3380 45. S. Dittmaier , A. Huss , C. Speckner , Weak radiative corrections to dijet production at hadron colliders . JHEP 11 , 095 ( 2012 ). doi:10. 1007/ JHEP11(2012)095 . arXiv:1210.0438 46. CMS Collaboration, Constraints on parton distribution functions and extraction of the strong coupling constant from the inclusive jet cross section in pp collisions at √s = 7 TeV . Eur. Phys. J. C 75 , 288 ( 2015 ). doi:10.1140/epjc/s10052- 015 - 3499 -1. arXiv: 1410 .6765 47. B. Andersson , The Lund model. Camb. Monogr. Part. Phys. Nucl. Phys. Cosmol . 7 , 1 ( 1997 ). doi:10.1016/ 0375 -9474(87)9 0 48. B.R. Webber , A QCD model for jet fragmentation including soft gluon interference . Nucl. Phys. B 238 , 492 ( 1984 ). doi:10.1016/ 0550 -3213(84) 90333 - X 49. R. Corke , T. Sjöstrand , Interleaved parton showers and tuning prospects . JHEP 03 , 032 ( 2011 ). doi:10.1007/ JHEP03(2011)032 . arXiv:1011.1759 50. NNPDF Collaboration, Parton distributions with QED corrections . Nucl. Phys. B 877 , 290 ( 2013 ). doi:10.1016/j.nuclphysb. 2013 .10. 010. arXiv:1308.0598 51. NNPDF Collaboration, Unbiased global determination of parton distributions and their uncertainties at NNLO and at LO . Nucl. Phys . B 855 , 153 ( 2012 ). doi:10.1016/j.nuclphysb. 2011 .09.024. arXiv:1107.2652 52. J. Pumplin et al., New generation of parton distributions with uncertainties from global QCD analysis . JHEP 07 , 012 ( 2002 ). doi:10. 1088/ 1126 - 6708 /2002/07/012. arXiv:hep-ph/ 0201195 53. H.-L. Lai et al., New parton distributions for collider physics. Phys. Rev. D 82 , 074024 ( 2010 ). doi:10.1103/PhysRevD.82.074024. arXiv:1007.2241 54. A.M. Cooper-Sarkar , HERAPDF1 .5LO PDF set with experimental uncertainties , in Proceedings, 22nd International Workshop on Deep-Inelastic Scattering and Related Subjects (DIS 2014) , vol. DIS2014 , p. 032 ( 2014 ) 55. P.Z. Skands , S. Carrazza , J. Rojo , Tuning PYTHIA 8.1: the Monash 2013 Tune. Eur. Phys. J. C 74 , 3024 ( 2014 ). doi:10.1140/epjc/ s10052- 014 - 3024 -y. arXiv:1404.5630 Institut für Hochenergiephysik der OeAW , Vienna, Austria W. Adam , E. Asilar , T. Bergauer , J. Brandstetter , E. Brondolin , M. Dragicevic , J. Erö , M. Flechl , M. Friedl , R. Frühwirth1 , V. M. Ghete , C. Hartl , N. Hörmann , J. Hrubec , M. Jeitler1 , A. König , I. Krätschmer , D. Liko , T. Matsushita , I. Mikulec , D. Rabady , N. Rad , B. Rahbaran , H. Rohringer , J. Schieck1 , J. Strauss , W. Treberer-Treberspurg , W. Waltenberger , C.-E. Wulz1 INFN Sezione di Bolognaa , Università di Bolognab, Bologna, Italy G. Abbiendia , C. Battilana, D. Bonacorsia,b, S. Braibant-Giacomellia,b, L. Brigliadoria,b, R. Campaninia,b, P. Capiluppia,b, A. Castroa,b, F. R. Cavalloa , S. S. Chhibraa,b, G. Codispotia,b, M. Cuffiania,b, G. M. Dallavallea , F. Fabbria , A. Fanfania,b, D. Fasanellaa,b, P. Giacomellia , C. Grandia , L. Guiduccia,b, S. Marcellinia , G. Masettia , A. Montanaria , F. L. Navarriaa,b, A. Perrottaa , A. M. Rossia,b, T. Rovellia,b, G. P. Sirolia,b, N. Tosia,b,14 INFN Sezione di Cataniaa , Università di Cataniab, Catania, Italy S. Albergoa,b, M. Chiorbolia,b, S. Costaa,b, A. Di Mattiaa , F. Giordanoa,b, R. Potenzaa,b, A. Tricomia,b, C. Tuvea,b INFN Sezione di Firenzea , Università di Firenzeb, Florence, Italy G. Barbaglia , V. Ciullia,b, C. Civininia , R. D'Alessandroa,b, E. Focardia,b, V. Goria,b, P. Lenzia,b, M. Meschinia , S. Paolettia , G. Sguazzonia , L. Viliania,b,14 CERN, European Organization for Nuclear Research, Geneva, Switzerland D. Abbaneo, E. Auffray, G. Auzinger, M. Bachtis, P. Baillon, A. H. Ball, D. Barney, P. Bloch, A. Bocci, A. Bonato, C. Botta, T. Camporesi, R. Castello, M. Cepeda, G. Cerminara, M. D'Alfonso, D. d'Enterria, A. Dabrowski, V. Daponte, A. David, M. De Gruttola, F. De Guio, A. De Roeck, E. Di Marco42, M. Dobson, M. Dordevic, B. Dorney, T. du Pree, D. Duggan, M. Dünser, N. Dupont, A. Elliott-Peisert, S. Fartoukh, G. Franzoni, J. Fulcher, W. Funk, D. Gigi, K. Gill, M. Girone, F. Glege, D. Gulhan, S. Gundacker, M. Guthoff, J. Hammer, P. Harris, J. Hegeman, V. Innocente, P. Janot, H. Kirschenmann, V. Knünz, M. J. Kortelainen, K. Kousouris, M. Krammer1, P. Lecoq, C. Lourenço, M. T. Lucchini, L. Malgeri, M. Mannelli, A. Martelli, F. Meijers, S. Mersi, E. Meschi, F. Moortgat, S. Morovic, M. Mulders, H. Neugebauer, S. Orfanelli43, L. Orsini, L. Pape, E. Perez, M. Peruzzi, A. Petrilli, G. Petrucciani, A. Pfeiffer, M. Pierini, A. Racz, T. Reis, G. Rolandi44, M. Rovere, M. Ruan, H. Sakulin, J. B. Sauvan, C. Schäfer, C. Schwick, M. Seidel, A. Sharma, P. Silva, M. Simon, P. Sphicas45, J. Steggemann, M. Stoye, Y. Takahashi, M. Tosi, D. Treille, A. Triossi, A. Tsirou, V. Veckalns46, G. I. Veres20, N. Wardle, A. Zagozdzinska34, W. D. Zeuner Paul Scherrer Institut, Villigen, Switzerland W. Bertl, K. Deiters, W. Erdmann, R. Horisberger, Q. Ingram, H. C. Kaestli, D. Kotlinski, U. Langenegger, T. Rohe Institute for Particle Physics, ETH Zurich, Zurich, Switzerland F. Bachmair, L. Bäni, L. Bianchini, B. Casal, G. Dissertori, M. Dittmar, M. Donegà, P. Eller, C. Grab, C. Heidegger, D. Hits, J. Hoss, G. Kasieczka, P. Lecomte†, W. Lustermann, B. Mangano, M. Marionneau, P. Martinez Ruiz del Arbol, M. Masciovecchio, M. T. Meinhard, D. Meister, F. Micheli, P. Musella, F. Nessi-Tedaldi, F. Pandolfi, J. Pata, F. Pauss, Fermi National Accelerator Laboratory, Batavia, USA S. Abdullin, M. Albrow, G. Apollinari, S. Banerjee, L. A. T. Bauerdick, A. Beretvas, J. Berryhill, P. C. Bhat, G. Bolla, K. Burkett, J. N. Butler, H. W. K. Cheung, F. Chlebana, S. Cihangir, M. Cremonesi, V. D. Elvira, I. Fisk, J. Freeman, E. Gottschalk, L. Gray, D. Green, S. Grünendahl, O. Gutsche, D. Hare, R. M. Harris, S. Hasegawa, J. Hirschauer, Z. Hu, B. Jayatilaka, S. Jindariani, M. Johnson, U. Joshi, B. Klima, B. Kreis, S. Lammel, J. Linacre, D. Lincoln, R. Lipton, T. Liu, R. Lopes De Sá, J. Lykken, K. Maeshima,N. Magini, J. M. Marraffino, S. Maruyama, D. Mason, P. McBride, P. Merkel, S. Mrenna, S. Nahn, C. Newman-Holmes†, V. O'Dell, K. Pedro, O. Prokofyev, G. Rakness, L. Ristori, E. Sexton-Kennedy, A. Soha, W. J. Spalding, L. Spiegel, S. Stoynev, N. Strobbe, L. Taylor, S. Tkaczyk, N. V. Tran, L. Uplegger, E. W. Vaandering, C. Vernieri, M. Verzocchi, R. Vidal, M. Wang, H. A. Weber, A. Whitbeck Massachusetts Institute of Technology, Cambridge, USA A. Apyan, R. Barbieri, A. Baty, R. Bi, K. Bierwagen, S. Brandt, W. Busza, I. A. Cali, Z. Demiragli, L. Di Matteo, G. Gomez Ceballos, M. Goncharov, D. Hsu, Y. Iiyama, G. M. Innocenti, M. Klute, D. Kovalskyi, K. Krajczar, Y. S. Lai, Y.-J. Lee, A. Levin, P. D. Luckey, A. C. Marini, C. Mcginn, C. Mironov, S. Narayanan, X. Niu, C. Paus, C. Roland, G. Roland, J. Salfeld-Nebgen, G. S. F. Stephans, K. Sumorok, K. Tatar, M. Varma, D. Velicanu, J. Veverka, J. Wang, T. W. Wang, B. Wyslouch, M. Yang, V. Zhukova


This is a preview of a remote PDF: https://link.springer.com/content/pdf/10.1140%2Fepjc%2Fs10052-016-4286-3.pdf

V. Khachatryan, A. M. Sirunyan, A. Tumasyan, W. Adam. Measurement of the double-differential inclusive jet cross section in proton–proton collisions at \(\sqrt{s} = 13\,\text {TeV} \), The European Physical Journal C, 2016, 451, DOI: 10.1140/epjc/s10052-016-4286-3