Measurement of the dijet invariant mass cross section in p\overline{p} collisions at \sqrt{s}= 1.96 TeV

Measurement of the dijet invariant mass cross section in collisions at 1.96 TeV

V.M. Abazov    B. Abbott    M. Abolins    B.S. Acharya    M. Adams    T. Adams    E. Aguilo    G.D. Alexeev    G. Alkhazov    A. Alton    G. Alverson    G.A. Alves    L.S. Ancu    M. Aoki    Y. Arnoud    M. Arov    A. Askew    B. Åsman    O. Atramentov    C. Avila    J. BackusMayes    F. Badaud    L. Bagby    B. Baldin    D.V. Bandurin    S. Banerjee    E. Barberis    A.-F. Barfuss    P. Baringer    J. Barreto    J.F. Bartlett    U. Bassler    S. Beale    A. Bean    M. Begalli    M. Begel    C. Belanger-Champagne    L. Bellantoni    J.A. Benitez    S.B. Beri    G. Bernardi    R. Bernhard    I. Bertram    M. Besançon    R. Beuselinck    V.A. Bezzubov    P.C. Bhat    V. Bhatnagar    G. Blazey    S. Blessing    K. Bloom    A. Boehnlein    D. Boline    T.A. Bolton    E.E. Boos    G. Borissov    T. Bose    A. Brandt    R. Brock    G. Brooijmans    A. Bross    D. Brown    X.B. Bu    D. Buchholz    M. Buehler    V. Buescher    V. Bunichev    S. Burdin    T.H. Burnett    C.P. Buszello    P. Calfayan    B. Calpas    S. Calvet    E. Camacho-Pérez    J. Cammin    M.A. Carrasco-Lizarraga    E. Carrera    B.C.K. Casey    H. Castilla-Valdez    S. Chakrabarti    D. Chakraborty    K.M. Chan    A. Chandra    G. Chen    S. Chevalier-Théry    D.K. Cho    S.W. Cho    S. Choi    B. Choudhary    T. Christoudias    S. Cihangir    D. Claes    J. Clutter    M. Cooke    W.E. Cooper    M. Corcoran    F. Couderc    M.-C. Cousinou    D. Cutts    M. Ćwiok    A. Das    G. Davies    K. De    S.J. de Jong    E. De La Cruz-Burelo    K. DeVaughan    F. Déliot    M. Demarteau    R. Demina    D. Denisov    S.P. Denisov    S. Desai    H.T. Diehl    M. Diesburg    A. Dominguez    T. Dorland    A. Dubey    L.V. Dudko    L. Duflot    D. Duggan    A. Duperrin    S. Dutt    A. Dyshkant    M. Eads    D. Edmunds    J. Ellison    V.D. Elvira    Y. Enari    S. Eno    H. Evans    A. Evdokimov    V.N. Evdokimov    G. Facini    A.V. Ferapontov    T. Ferbel    F. Fiedler    F. Filthaut    W. Fisher    H.E. Fisk    M. Fortner    H. Fox    S. Fuess    T. Gadfort    A. Garcia-Bellido    V. Gavrilov    P. Gay    W. Geist    W. Geng    D. Gerbaudo    C.E. Gerber    Y. Gershtein    D. Gillberg    G. Ginther    G. Golovanov    B. Gómez    A. Goussiou    P.D. Grannis    S. Greder    H. Greenlee    Z.D. Greenwood    E.M. Gregores    G. Grenier    Ph. Gris    J.-F. Grivaz    A. Grohsjean    S. Grünendahl    M.W. Grünewald    F. Guo    J. Guo    G. Gutierrez    P. Gutierrez    A. Haas    P. Haefner    S. Hagopian    J. Haley    I. Hall    L. Han    K. Harder    A. Harel    J.M. Hauptman    J. Hays    T. Hebbeker    D. Hedin    A.P. Heinson    U. Heintz    C. Hensel    I. Heredia-De La Cruz    K. Herner    G. Hesketh    M.D. Hildreth    R. Hirosky    T. Hoang    J.D. Hobbs    B. Hoeneisen    M. Hohlfeld    S. Hossain    P. Houben    Y. Hu    Z. Hubacek    N. Huske    V. Hynek    I. Iashvili    R. Illingworth    A.S. Ito    S. Jabeen    M. Jaffré    S. Jain    D. Jamin    R. Jesik    K. Johns    C. Johnson    M. Johnson    D. Johnston    A. Jonckheere    P. Jonsson    A. Juste    E. Kajfasz    D. Karmanov    P.A. Kasper    I. Katsanos    R. Kehoe    S. Kermiche    N. Khalatyan    A. Khanov    A. Kharchilava    Y.N. Kharzheev    D. Khatidze    M.H. Kirby    M. Kirsch    J.M. Kohli    A.V. Kozelov    J. Kraus    A. Kumar    A. Kupco    T. Kurča    V.A. Kuzmin    J. Kvita    S. Lammers    G. Landsberg    P. Lebrun    H.S. Lee    W.M. Lee    J. Lellouch    L. Li    Q.Z. Li    S.M. Lietti    J.K. Lim    D. Lincoln    J. Linnemann    V.V. Lipaev    R. Lipton    Y. Liu    Z. Liu    A. Lobodenko    M. Lokajicek    P. Love    H.J. Lubatti    R. Luna-Garcia    A.L. Lyon    A.K.A. Maciel    D. Mackin    R. Magaña-Villalba    P.K. Mal    S. Malik    V.L. Malyshev    Y. Maravin    J. Martínez-Ortega    R. McCarthy    C.L. McGivern    M.M. Meijer    A. Melnitchouk    L. Mendoza    D. Menezes    P.G. Mercadante    M. Merkin    A. Meyer    J. Meyer    N.K. Mondal    T. Moulik    G.S. Muanza    M. Mulhearn    E. Nagy    M. Naimuddin    M. Narain    R. Nayyar    H.A. Neal    J.P. Negret    P. Neustroev    H. Nilsen    S.F. Novaes    T. Nunnemann    G. Obrant    D. Onoprienko    J. Orduna    N. Osman    J. Osta    G.J. Otero y Garzón    M. Owen    M. Padilla    M. Pangilinan    N. Parashar    V. Parihar    S.-J. Park    S.K. Park    J. Parsons    R. Partridge    N. Parua    A. Patwa    B. Penning    M. Perfilov    K. Peters    Y. Peters    P. Pétroff    R. Piegaia    J. Piper    M.-A. Pleier    P.L.M. Podesta-Lerma    V.M. Podstavkov    M.-E. Pol    P. Polozov    A.V. Popov    M. Prewitt    D. Price    S. Protopopescu    J. Qian    A. Quadt    B. Quinn    M.S. Rangel    K. Ranjan    P.N. Ratoff    I. Razumov    P. Renkel    P. Rich    M. Rijssenbeek    I. Ripp-Baudot    F. Rizatdinova    M. Rominsky    C. Royon    P. Rubinov    R. Ruchti    G. Safronov    G. Sajot    A. Sánchez-Hernández    M.P. Sanders    B. Sanghi    G. Savage    L. Sawyer    T. Scanlon    D. Schaile    R.D. Schamberger    Y. Scheglov    H. Schellman    T. Schliephake    S. Schlobohm    C. Schwanenberger    R. Schwienhorst    J. Sekaric    H. Severini    E. Shabalina    V. Shary    A.A. Shchukin    R.K. Shivpuri    V. Simak    V. Sirotenko    P. Skubic    P. Slattery    D. Smirnov    G.R. Snow    J. Snow    S. Snyder    S. Söldner-Rembold    L. Sonnenschein    A. Sopczak    M. Sosebee    K. Soustruznik    B. Spurlock    J. Stark    V. Stolin    D.A. Stoyanova    M.A. Strang    E. Strauss    M. Strauss    R. Ströhmer    D. Strom    L. Stutte    P. Svoisky    M. Takahashi    A. Tanasijczuk    W. Taylor    B. Tiller    M. Titov    V.V. Tokmenin    D. Tsybychev    B. Tuchming    C. Tully    P.M. Tuts    R. Unalan    L. Uvarov    S. Uvarov    S. Uzunyan    R. Van Kooten    W.M. van Leeuwen    N. Varelas    E.W. Varnes    I.A. Vasilyev    P. Verdier    L.S. Vertogradov    M. Verzocchi    M. Vesterinen    D. Vilanova    P. Vint    P. Vokac    H.D. Wahl    M.H.L.S. Wang    J. Warchol    G. Watts    M. Wayne    G. Weber    M. Weber    M. Wetstein    A. White    D. Wicke    M.R.J. Williams    G.W. Wilson    S.J. Wimpenny    M. Wobisch    D.R. Wood    T.R. Wyatt    Y. Xie    C. Xu    S. Yacoob    R. Yamada    W.-C. Yang    T. Yasuda    Y.A. Yatsunenko    Z. Ye    H. Yin    K. Yip    H.D. Yoo    S.W. Youn    J. Yu    S. Zelitch    T. Zhao    B. Zhou    J. Zhu    M. Zielinski    D. Zieminska    L. Zivkovic (The DØ Collaboration) Universidad de Buenos Aires, Buenos Aires, Argentina LAFEX, Centro Brasileiro de Pesquisas Físicas, Rio de Janeiro, Brazil Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil Universidade Federal do ABC, Santo André, Brazil Instituto de Física Teórica, Universidade Estadual Paulista, São Paulo, Brazil Simon Fraser University, Burnaby, British Columbia, Canada; and York University, Toronto, Ontario, Canada University of Science and Technology of China, Hefei, People’s Republic of China Universidad de los Andes, Bogotá, Colombia Center for Particle Physics, Charles University, Faculty of Mathematics and Physics, Prague, Czech Republic Czech Technical University in Prague, Prague, Czech Republic Center for Particle Physics, Institute of Physics, Academy of Sciences of the Czech Republic, Prague, Czech Republic Universidad San Francisco de Quito, Quito, Ecuador LPC, Université Blaise Pascal, CNRS/IN2P3, Clermont, France LPSC, Université Joseph Fourier Grenoble 1, CNRS/IN2P3, Institut National Polytechnique de Grenoble, Grenoble, France CPPM, Aix-Marseille Université, CNRS/IN2P3, Marseille, France LAL, Université Paris-Sud, IN2P3/CNRS, Orsay, France LPNHE, Universités Paris VI and VII, CNRS/IN2P3, Paris, France CEA, Irfu, SPP, Saclay, France IPHC, Université de Strasbourg, CNRS/IN2P3, Strasbourg, France IPNL, Université Lyon 1, CNRS/IN2P3, Villeurbanne, France and Université de Lyon, Lyon, France III. Physikalisches Institut A, RWTH Aachen University, Aachen, Germany Physikalisches Institut, Universität Freiburg, Freiburg, Germany II. Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen, Germany Institut für Physik, Universität Mainz, Mainz, Germany Ludwig-Maximilians-Universität München, München, Germany Fachbereich Physik, University of Wuppertal, Wuppertal, Germany Panjab University, Chandigarh, India Delhi University, Delhi, India Tata Institute of Fundamental Research, Mumbai, India University College Dublin, Dublin, Ireland Korea Detector Laboratory, Korea University, Seoul, Korea SungKyunKwan University, Suwon, Korea CINVESTAV, Mexico City, Mexico FOM-Institute NIKHEF and University of Amsterdam/NIKHEF, Amsterdam, The Netherlands Radboud University Nijmegen/NIKHEF, Nijmegen, The Netherlands Joint Institute for Nuclear Research, Dubna, Russia Institute for Theoretical and Experimental Physics, Moscow, Russia Moscow State University, Moscow, Russia Institute for High Energy Physics, Protvino, Russia Petersburg Nuclear Physics Institute, St. Petersburg, Russia Stockholm University, Stockholm, Sweden, and Uppsala University, Uppsala, Sweden Lancaster University, Lancaster LA1 4YB, United Kingdom Imperial College London, London SW7 2AZ, United Kingdom The University of Manchester, Manchester M13 9PL, United Kingdom University of Arizona, Tucson, Arizona 85721, USA University of California Riverside, Riverside, California 92521, USA Florida State University, Tallahassee, Florida 32306, USA Fermi National Accelerator Laboratory, Batavia, Illinois 60510, USA University of Illinois at Chicago, Chicago, Illinois 60607, USA Northern Illinois University, DeKalb, Illinois 60115, USA Northwestern University, Evanston, Illinois 60208, USA Indiana University, Bloomington, Indiana 47405, USA Purdue University Calumet, Hammond, Indiana 46323, USA University of Notre Dame, Notre Dame, Indiana 46556, USA Iowa State University, Ames, Iowa 50011, USA University of Kansas, Lawrence, Kansas 66045, USA Kansas State University, Manhattan, Kansas 66506, USA Louisiana Tech University, Ruston, Louisiana 71272, USA University of Maryland, College Park, Maryland 20742, USA Boston University, Boston, Massachusetts 02215, USA Northeastern University, Boston, Massachusetts 02115, USA University of Michigan, Ann Arbor, Michigan 48109, USA Michigan State University, East Lansing, Michigan 48824, USA University of Mississippi, University, Mississippi 38677, USA University of Nebraska, Lincoln, Nebraska 68588, USA Rutgers University, Piscataway, New Jersey 08855, USA Princeton University, Princeton, New Jersey 08544, USA State University of New York, Buffalo, New York 14260, USA Columbia University, New York, New York 10027, USA University of Rochester, Rochester, New York 14627, USA State University of New York, Stony Brook, New York 11794, USA Brookhaven National Laboratory, Upton, New York 11973, USA Langston University, Langston, Oklahoma 73050, USA University of Oklahoma, Norman, Oklahoma 73019, USA Oklahoma State University, Stillwater, Oklahoma 74078, USA Brown University, Providence, Rhode Island 02912, USA University of Texas, Arlington, Texas 76019, USA Southern Methodist University, Dallas, Texas 75275, USA Rice University, Houston, Texas 77005, USA University of Virginia, Charlottesville, Virginia 22901, USA University of Washington, Seattle, Washington 98195, USA
February 24, 2010
Abstract

The inclusive dijet production double differential cross section as a function of the dijet invariant mass and of the largest absolute rapidity of the two jets with the largest transverse momentum in an event is measured in collisions at TeV using 0.7 fb of integrated luminosity collected with the D0 detector at the Fermilab Tevatron Collider. The measurement is performed in six rapidity regions up to a maximum rapidity of 2.4. Next-to-leading order perturbative QCD predictions are found to be in agreement with the data.

pacs:
13.87.Ce, 12.38.Qk

Fermilab-Pub-10/038-E

The dominant process contributing to the total inelastic cross section in collisions at TeV is the production of hadronic jets. A measurement of the dijet production cross section as a function of the dijet invariant mass () can be used to test the predictions of perturbative quantum chromodynamics (QCD), to constrain parton distribution functions (PDFs) of the proton, and to look for signatures of physics not predicted by the standard model. This type of measurement is sensitive to quark compositeness, to extra spatial dimensions, and to undiscovered heavy particles that decay into two quarks composite (); composite2 (); composite3 (); composite4 (); composite5 (); composite6 (); composite7 (); composite8 (). The distribution presented in this paper is particularly sensitive to the PDF of gluons at high proton momentum fraction, a region in which the gluon distribution is weakly constrained. Previous measurements of the dijet invariant mass dependent cross section in this energy regime restricted the rapidity of the jets to runIpaper (); dmr1 (); cdfrun2 () where , is the energy of the jet, and is the component of momentum along the direction of the proton beam.

In this Letter, we present a measurement of the double differential dijet production cross section as a function of the dijet invariant mass and the variable , for . The dijet invariant mass is computed from the four momenta of the two jets with largest transverse momentum () with respect to the beam direction. Both jets are required to have GeV. The variable is defined as where and are the rapidities of the two jets with the largest . The cross section results are corrected for instrumental effects and presented at the particle level, which includes energy from stable particles, the underlying event, muons, and neutrinos, as defined in Ref. Buttar:2008jx ().

This measurement uses approximately 0.7 fb of integrated luminosity collected with the D0 detector d0det () at the Fermilab Tevatron Collider in collisions at TeV during 2004–2005. Outgoing partons created in the scattering process hadronize to produce jets of particles that are detected in the finely segmented liquid-argon and uranium calorimeters which cover most of the solid angle. The central calorimeter (CC) covers the pseudorapidity region up to 1.1 ( where is the angle with respect to the proton beam direction) and the two end calorimeters (EC) extend the coverage up to . The intercryostat region (ICR) between the CC and EC contains scintillator-based detectors to improve the energy sampling in this region. Jets are reconstructed by clustering energy deposited in the calorimeter towers using an iterative seed-based cone jet algorithm including midpoints d0jets () with cone radius , where is the azimuthal angle. The of each jet is calculated using only calorimeter information and the location of the collision. The measurement is performed in six rapidity regions: , , , , , and .

Events are required to satisfy jet or dijet invariant mass dependent trigger requirements with minimum dijet invariant mass thresholds. Trigger efficiencies are studied by comparing observables in data sets collected with higher trigger thresholds to those collected using lower trigger thresholds in regions where the lower threshold trigger is 100% efficient. The trigger with the lowest threshold is determined to be 100% efficient in the region of interest by comparing it with sample of independently triggered muon events. For , single jet triggers are used, while dijet invariant mass triggers are used for . The measurement is only done in the kinematic regions where the trigger efficiency is .

Events must satisfy data and jet quality requirements. The position of the interaction is reconstructed using a tracking system consisting of silicon microstrip detectors and scintillating fibers located inside a solenoidal magnetic field of approximately 2 T. The position of this primary vertex along the beam line is required to be within 50 cm of the detector center. This requirement is efficient. Requirements based on calorimeter shower shapes are used to remove the remaining background due to electrons, photons, and detector noise that mimic jets. The sample selection efficiency is 99% ( 97.5% for ). In order to suppress cosmic ray events, the requirements for GeV of the highest jet and otherwise are applied, where is the transverse component of the vector sum of the momenta in all calorimeter cells and is the transverse momentum of the jet with the maximum . After all these requirements, the background is reduced to less than 0.1% in our sample.

The measured energy of each jet formed from calorimeter energy depositions is not the same as the actual energy of the particles which enter the calorimeter and shower. The jet four-momentum is corrected, on average, to account for the energy response of the calorimeters, the energy showering in and out of the cone, additional energy from previous beam crossings, and multiple proton-antiproton interactions in the same event. The absolute jet energy calibration correction is determined from the missing transverse energy measured in + jet events for the region , while the rapidity dependence is derived from dijet events using a similar data driven method. Additionally, since this dijet sample has a large fraction of gluon initiated jets, corrections of the order of (2–4)% are made due to the difference in response between quark and gluon initiated jets as estimated using simulated jets produced with the pythia event generator pythia () that have been passed through a geant-based detector simulation geant (). The total jet energy correction varies between 50% and 20% for a jet of 50 to 400 GeV and adjusts the measured jet energy to the energy of all stable particles that entered the calorimeter except for muons and neutrinos, which are accounted for in the final differential cross section.

Bin sizes in are chosen to be about twice the mass resolution and to correspond to an efficiency and purity of about 50% as determined using a parameterized detector model. The efficiency is defined as the ratio of Monte Carlo (MC) events generated and reconstructed to those generated in a bin, and purity is defined as the ratio of MC events generated and reconstructed in a bin to all events reconstructed in that bin. The detector model used is a fast simulation of the D0 detector based on parameterizations including energy and position resolutions obtained either from the data or from a detailed simulation of the D0 detector using geant. This detector model uses events generated by pythia (using the settings of Tune QW Albrow:2006rt () and MSTW2008LO PDFs  MSTW2008 ()) that have been reweighted to match measured dijet invariant mass and rapidity distributions in data. This reweighting assumes a smooth underlying distribution, which does not include resonances. After this tuning, other spectra fundamental to this measurement, such as the jet distributions, show good agreement between the data and simulation. Because the underlying dijet cross sections are steeply falling, the measured dijet invariant mass distributions are systematically shifted to higher invariant mass values due to jet resolution. The jet resolution is measured in data using momentum conservation in the transverse plane for events with exactly two jets, and is found to be approximately 13% (7%) at (400) GeV in the CC and EC, and 16% (11%) at (400) GeV in the ICR. The bin-to-bin migrations due to experimental resolution are determined using the parametrized detector model. To minimize migrations between bins due to resolution effects, we use the simulation to obtain a rescaling function in that optimizes the correlation between the reconstructed and true values. The total experimental corrections to the data are less than 2% across the whole dijet invariant mass range for , vary from 0.5% at TeV to 22% at 1.2 TeV for , and from 1% at TeV to 11% at 1.3 TeV for .

We compute the doubly differential dijet cross section as a function of dijet invariant mass and corrected for all selection efficiencies and migrations due to resolution, and for the energies of minimum ionizing muons and non-interacting neutrinos associated with the jet as determined from our detector simulation. The result is plotted in all six rapidity regions in Fig. 1 and tabulated in Tables 1 through 6. The quoted central value of in each bin is the location where the differential cross section has the same value as the bin average LaffertyWyatt:1995 ().

The systematic uncertainties on the cross section are dominated by the uncertainties in the jet energy calibration, which range from 6% to 22% in the CC, 8% to 30% in the ICR, and 15% to 45% in the EC region. The second largest systematic uncertainty comes from the resolution uncertainty, which ranges between 2% and 10% in all regions. The luminosity determination has an uncertainty of 6.1%, which is completely correlated across all bins. The systematic uncertainties on the jet identification efficiency corrections, corrections due to misvertexing and angular resolutions, and MC reweighting are calculated using the parameterized model of the detector and affect the measured cross section by less than 2% in all regions.

The data are compared to the next-to-leading order (NLO) prediction computed using fastnlo Kluge:2006xs () based on nlojet++ Nagy:2003tz (); Nagy:2001fj () for MSTW2008NLO PDFs with . The NLO prediction is corrected for hadronization and underlying event effects using corrections which range between % and +23% depending on the mass in all rapidity regions. The correction factors are obtained by turning these effects on and off individually in pythia. The uncertainty due to the nonperturbative corrections is estimated as 50% of the individual corrections, with the uncertainty determined by adding the individual contributions in quadrature. The renormalization and factorization scales are set to where and are the of the two highest jets. The effect of varying these scales simultaneously from to is shown in Fig. 2 where the ratio of data to theory is plotted.

Figure 1: (color online) The dijet production cross section as a function of invariant mass in intervals of compared to NLO predictions that include non-perturbative corrections. The uncertainties shown are statistical only.
Figure 2: (color online) Ratio of data over theoretical expectation using MSTW2008NLO PDFs in all six bins. The measurement systematic uncertainty is shown as a shaded band. There is an additional fully correlated uncertainty of 6.1% due to the integrated luminosity determination which is not shown in the plots. The legend for all six plots shown is spread out over the three bottom plots with other relevant information in the top three plots. PDF uncertainties show a 90% C.L. band.
Mass Central Measured Systematic Statistical Theory Non-perturbative corrections
range value Cross Section uncertainty uncertainty Cross Section Hadron- Underlying Total
TeV TeV pb/TeV % % pb/TeV ization event
0.150–0.175 0.162 2.74 +7.3,6.6 1.9 2.74 0.917 1.180 1.082
0.175–0.200 0.187 1.22 +7.3,6.6 2.6 1.22 0.930 1.147 1.066
0.200–0.225 0.212 6.00 +7.3,6.6 1.4 5.93 0.939 1.125 1.056
0.225–0.250 0.237 3.02 +7.3,6.6 1.8 3.10 0.945 1.110 1.049
0.250–0.300 0.272 1.32 +7.3,6.6 1.3 1.36 0.950 1.095 1.041
0.300–0.350 0.323 4.69 +7.5,6.8 1.6 4.85 0.955 1.083 1.035
0.350–0.400 0.373 1.90 +7.3,6.7 1.3 1.96 0.959 1.075 1.030
0.400–0.450 0.423 8.48 +7.4,6.8 1.4 8.60 0.961 1.069 1.027
0.450–0.500 0.473 3.93 +7.6,7.1 1.7 4.01 0.963 1.065 1.025
0.500–0.560 0.528 1.84 +7.9,7.4 2.1 1.85 0.965 1.058 1.022
0.560–0.620 0.588 7.93 +8.3,8.0 3.1 8.17 0.967 1.054 1.019
0.620–0.690 0.652 3.50 +9.1,8.8 4.2 3.53 0.966 1.056 1.020
0.690–0.770 0.727 1.23 +10.4,10.0 6.5 1.37 0.967 1.054 1.019
0.770–0.860 0.811 4.83 +12.1,11.7 9.8 4.77 0.968 1.052 1.018
0.860–0.950 0.901 1.69 +14.3,13.7 15.8 1.52 0.968 1.050 1.017
0.950–1.050 0.995 4.95 +16.7,15.8 31.6 4.49 0.969 1.049 1.016
1.050–1.300 1.144 4.56 +22.1,20.0 57.7 5.83 0.970 1.047 1.015
Table 1: Dijet double differential cross section, , for , compared to theoretical predictions with non-perturbative corrections. There is an additional fully correlated uncertainty of 6.1% due to the integrated luminosity determination which is not shown in the table.
Mass Central Measured Systematic Statistical Theory Non-perturbative corrections
range value Cross Section uncertainty uncertainty Cross Section Hadron- Underlying Total
TeV TeV pb/TeV % % pb/TeV ization event
0.150–0.175 0.162 1.08 +7.4,7.4 1.3 1.07 0.946 1.127 1.066
0.175–0.200 0.187 4.67 +7.5,7.4 1.6 4.73 0.951 1.109 1.055
0.200–0.225 0.212 2.24 +7.5,7.5 1.1 2.29 0.955 1.094 1.045
0.225–0.250 0.237 1.14 +7.6,7.5 1.2 1.19 0.958 1.084 1.040
0.250–0.300 0.272 4.91 +7.9,7.8 1.1 5.14 0.960 1.077 1.034
0.300–0.350 0.323 1.74 +7.6,7.6 1.2 1.81 0.961 1.072 1.030
0.350–0.400 0.373 6.77 +7.9,7.7 1.1 7.15 0.963 1.067 1.028
0.400–0.450 0.423 2.89 +8.0,7.9 1.2 3.07 0.964 1.064 1.025
0.450–0.500 0.473 1.28 +8.3,8.2 1.3 1.40 0.964 1.061 1.023
0.500–0.560 0.528 5.97 +8.7,8.6 1.4 6.25 0.965 1.058 1.021
0.560–0.620 0.589 2.50 +9.4,9.2 1.9 2.68 0.966 1.056 1.020
0.620–0.690 0.652 1.04 +10.3,10.1 2.5 1.11 0.966 1.054 1.018
0.690–0.770 0.726 3.78 +11.7,11.3 3.8 4.12 0.967 1.052 1.017
0.770–0.860 0.811 1.38 +13.5,13.0 5.7 1.35 0.967 1.050 1.016
0.860–0.950 0.901 4.20 +15.714.9 10.7 4.08 0.968 1.047 1.014
0.950–1.050 0.994 9.90 +18.4,17.0 20.4 1.13 0.969 1.045 1.012
1.050–1.300 1.142 6.08 +23.5,20.9 50.0 1.36 0.969 1.045 1.012
Table 2: Dijet double differential cross section, , for , compared to theoretical predictions with non-perturbative corrections. There is an additional fully correlated uncertainty of 6.1% due to the integrated luminosity determination which is not shown in the table.
Mass Central Measured Systematic Statistical Theory Non-perturbative corrections
range value Cross Section uncertainty uncertainty Cross Section Hadron- Underlying Total
TeV TeV pb/TeV % % pb/TeV ization event
0.250–0.300 0.272 1.21 +10.3,10.0 1.1 1.34 0.949 1.126 1.069
0.300–0.350 0.323 4.18 +9.7,9.5 1.3 4.63 0.953 1.111 1.059
0.350–0.400 0.373 1.63 +9.4,9.1 1.7 1.80 0.956 1.100 1.052
0.400–0.450 0.423 6.86 +9.3,9.0 1.4 7.55 0.958 1.092 1.046
0.450– 0.500 0.473 3.10 +9.3,9.0 1.9 3.38 0.960 1.083 1.041
0.500–0.600 0.544 1.07 +9.6,9.3 1.2 1.17 0.963 1.076 1.035
0.600–0.700 0.644 2.57 +10.6,10.4 1.8 2.83 0.964 1.070 1.031
0.700–0.830 0.756 5.95 +12.7,12.6 2.5 6.30 0.965 1.065 1.028
0.830–0.960 0.886 1.08 +16.4,16.0 5.4 1.10 0.966 1.062 1.026
0.960–1.080 1.012 2.10 +20.6,19.7 12.5 1.95 0.967 1.058 1.023
1.080–1.400 1.186 1.43 +28.5,24.5 28.9 1.50 0.969 1.053 1.020
Table 3: Dijet double differential cross section, , for , compared to theoretical predictions with non-perturbative corrections. There is an additional fully correlated uncertainty of 6.1% due to the integrated luminosity determination which is not shown in the table.
Mass Central Measured Systematic Statistical Theory Non-perturbative corrections
range value Cross Section uncertainty uncertainty Cross Section Hadron- Underlying Total
TeV TeV pb/TeV % % pb/TeV ization event
0.300–0.350 0.323 1.00 +10.7,10.4 1.2 1.19 0.949 1.143 1.085
0.350–0.400 0.373 3.79 +10.4,10.1 1.3 4.60 0.951 1.133 1.077
0.400–0.450 0.423 1.61 +10.4,9.9 1.7 1.91 0.952 1.125 1.071
0.450–0.500 0.473 7.11 +10.7,10.0 2.3 8.60 0.954 1.116 1.065
0.500–0.600 0.544 2.54 +11.3,10.4 1.6 2.97 0.955 1.109 1.059
0.600–0.700 0.644 5.94 +12.3,11.7 1.3 7.16 0.956 1.103 1.055
0.700–0.800 0.744 1.58 +14.1,13.4 2.1 1.84 0.957 1.098 1.051
0.800–0.960 0.866 3.16 +17.8,16.8 2.9 3.57 0.958 1.095 1.048
0.960–1.080 1.012 5.08 +22.7,21.4 8.0 4.78 0.958 1.091 1.045
1.080–1.400 1.186 4.77 +29.5,27.9 15.8 3.67 0.959 1.084 1.040
Table 4: Dijet double differential cross section, , for , compared to theoretical predictions with non-perturbative corrections. There is an additional fully correlated uncertainty of 6.1% due to the integrated luminosity determination which is not shown in the table.
Mass Central Measured Systematic Statistical Theory Non-perturbative corrections
range value Cross Section uncertainty uncertainty Cross Section Hadron- Underlying Total
TeV TeV pb/TeV % % pb/TeV ization event
0.450–0.500 0.473 2.01 +12.013.5 2.2 2.27 0.940 1.151 1.083
0.500–0.600 0.544 6.88 +13.8,14.6 2.3 7.82 0.940 1.141 1.073
0.600–0.700 0.644 1.58 +16.3,17.3 3.2 1.87 0.941 1.132 1.065
0.700–0.800 0.744 4.10 +19.9,18.7 2.3 4.74 0.941 1.125 1.058
0.800–0.920 0.852 9.30 +21.1,17.0 2.8 1.10 0.941 1.119 1.054
0.920–1.040 0.972 1.93 +27.1,20.3 4.9 2.16 0.941 1.112 1.047
1.040–1.160 1.092 3.15 +32.5,24.3 11.2 3.68 0.942 1.104 1.040
1.160–1.500 1.266 1.92 +36.3,33.4 25.1 2.34 0.942 1.100 1.037
Table 5: Dijet double differential cross section, , for , compared to theoretical predictions with non-perturbative corrections. There is an additional fully correlated uncertainty of 6.1% due to the integrated luminosity determination which is not shown in the table.
Mass Central Measured Systematic Statistical Theory Non-perturbative corrections
range value Cross Section uncertainty uncertainty Cross Section Hadron- Underlying Total
TeV TeV pb/TeV % % pb/TeV ization event
0.450–0.500 0.473 4.95 +16.1,13.7 2.1 6.08 0.928 1.229 1.141
0.500–0.600 0.544 1.81 +16.2,14.1 2.1 2.15 0.925 1.222 1.130
0.600–0.700 0.644 4.36 +16.5,15.2 2.5 5.21 0.923 1.216 1.122
0.700–0.800 0.744 1.02 +17.4,17.0 2.1 1.31 0.920 1.211 1.115
0.800–0.920 0.852 2.37 +20.0,19.9 2.4 2.998 0.919 1.208 1.110
0.920–1.040 0.972 4.43 +24.8,23.9 3.5 5.66 0.917 1.203 1.103
1.040–1.160 1.091 7.25 +33.0,28.0 7.3 9.86 0.915 1.198 1.095
1.160–1.500 1.263 4.12 +46.1,33.8 16.5 6.09 0.913 1.195 1.092
Table 6: Dijet double differential cross section, , for , compared to theoretical predictions with non-perturbative corrections. There is an additional fully correlated uncertainty of 6.1% due to the integrated luminosity determination which is not shown in the table.

The experimental uncertainties are similar in size to both the PDF and the scale uncertainties, suggesting that the measurement will constrain theoretical models. We are quoting PDF uncertainties corresponding to a 90% C.L. The total uncertainties are smaller than those of earlier measurements at this same center-of-mass energy cdfrun2 (). In addition to comparing the D0 measurement to the theoretical predictions using MSTW2008NLO PDFs, we also compare to the theoretical predictions using CTEQ6.6 PDFs cteq66 (). The difference in the cross section due to the choice of PDFs is (40–60)% at the highest mass. Although the central value for the MSTW2008NLO PDFs are favored, it is important to note that their determination included a measurement of the D0 inclusive jet production cross section d0jet () which is based on the same dataset as the present measurement. In addition, these PDFs exclude Tevatron data taken before 2000, while the CTEQ6.6 PDFs include that data and do not include Tevatron data taken after 2000.

In summary, we have presented a new measurement of the dijet production cross section as a function of the dijet invariant mass and of the largest rapidity of the two highest jets that extends the rapidity range beyond previous measurements, with systematic uncertainties that are significantly smaller. In general, the data are described by NLO QCD predictions using MSTW2008NLO or CTEQ6.6 PDFs in all rapidity regions, though the central value of the CTEQ6.6 PDFs differs from the data for high dijet mass at larger rapidities.

We thank the staffs at Fermilab and collaborating institutions, and acknowledge support from the DOE and NSF (USA); CEA and CNRS/IN2P3 (France); FASI, Rosatom and RFBR (Russia); CNPq, FAPERJ, FAPESP and FUNDUNESP (Brazil); DAE and DST (India); Colciencias (Colombia); CONACyT (Mexico); KRF and KOSEF (Korea); CONICET and UBACyT (Argentina); FOM (The Netherlands); STFC and the Royal Society (United Kingdom); MSMT and GACR (Czech Republic); CRC Program and NSERC (Canada); BMBF and DFG (Germany); SFI (Ireland); The Swedish Research Council (Sweden); and CAS and CNSF (China).

References

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  • (b) Visitor from The University of Liverpool, Liverpool, UK.
  • (c) Visitor from SLAC, Menlo Park, CA, USA.
  • (d) Visitor from ICREA/IFAE, Barcelona, Spain.
  • (e) Visitor from Centro de Investigacion en Computacion - IPN, Mexico City, Mexico.
  • (f) Visitor from ECFM, Universidad Autonoma de Sinaloa, Culiacán, Mexico.
  • (g) Visitor from Universität Bern, Bern, Switzerland.
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