application/xmlHard single diffraction in [formula omitted] collisions at [formula omitted] and 1800 GeVDØ CollaborationV.M. AbazovB. AbbottA. AbdesselamM. AbolinsV. AbramovB.S. AcharyaD.L. AdamsM. AdamsS.N. AhmedG.D. AlexeevA. AltonG.A. AlvesE.W. AndersonY. ArnoudC. AvilaM.M. BaarmandV.V. BabintsevL. BabukhadiaT.C. BaconA. BadenB. BaldinP.W. BalmS. BanerjeeE. BarberisP. BaringerJ. BarretoJ.F. BartlettU. BasslerD. BauerA. BeanF. BeaudetteM. BegelA. BelyaevS.B. BeriG. BernardiI. BertramA. BessonR. BeuselinckV.A. BezzubovP.C. BhatV. BhatnagarM. BhattacharjeeG. BlazeyF. BlekmanS. BlessingA. BoehnleinN.I. BojkoT.A. BoltonF. BorcherdingK. BosT. BoseA. BrandtR. BreedonG. BriskinR. BrockG. BrooijmansA. BrossD. BuchholzM. BuehlerV. BuescherV.S. BurtovoiJ.M. ButlerF. CanelliW. CarvalhoD. CaseyZ. CasilumH. Castilla-ValdezD. ChakrabortyK.M. ChanS.V. ChekulaevD.K. ChoS. ChoiS. ChopraJ.H. ChristensonM. ChungD. ClaesA.R. ClarkL. ConeyB. ConnollyW.E. CooperD. CoppageS. Crépé-RenaudinM.A.C. CummingsD. CuttsG.A. DavisK. DeS.J. de JongM. DemarteauR. DeminaP. DemineD. DenisovS.P. DenisovS. DesaiH.T. DiehlM. DiesburgS. DoulasY. DucrosL.V. DudkoS. DuensingL. DuflotS.R. DugadA. DuperrinA. DyshkantD. EdmundsJ. EllisonJ.T. EltzrothV.D. ElviraR. EngelmannS. EnoG. EppleyP. ErmolovO.V. EroshinJ. EstradaH. EvansV.N. EvdokimovT. FahlandD. FeinT. FerbelF. FilthautH.E. FiskY. FisyakE. FlattumF. FleuretM. FortnerH. FoxK.C. FrameS. FuS. FuessE. GallasA.N. GalyaevM. GaoV. GavrilovR.J. Genik IIK. GenserC.E. GerberY. GershteinR. GilmartinG. GintherB. GómezP.I. GoncharovH. GordonL.T. GossK. GounderA. GoussiouN. GrafP.D. GrannisJ.A. GreenH. GreenleeZ.D. GreenwoodS. GrinsteinL. GroerS. GrünendahlA. GuptaS.N. GurzhievG. GutierrezP. GutierrezN.J. HadleyH. HaggertyS. HagopianV. HagopianR.E. HallS. HansenJ.M. HauptmanC. HaysC. HebertD. HedinJ.M. HeinmillerA.P. HeinsonU. HeintzM.D. HildrethR. HiroskyJ.D. HobbsB. HoeneisenY. HuangI. IashviliR. IllingworthA.S. ItoM. JaffréS. JainR. JesikK. JohnsM. JohnsonA. JonckheereH. JöstleinA. JusteW. KahlS. KahnE. KajfaszA.M. KalininD. KarmanovD. KarmgardR. KehoeA. KhanovA. KharchilavaS.K. KimB. KlimaB. KnutesonW. KoJ.M. KohliA.V. KostritskiyJ. KotcherB. KothariA.V. KotwalA.V. KozelovE.A. KozlovskyJ. KraneM.R. KrishnaswamyP. KrivkovaS. KrzywdzinskiM. KubantsevS. KuleshovY. KulikS. KunoriA. KupcoV.E. KuznetsovG. LandsbergW.M. LeeA. LeflatC. LeggettF. LehnerC. LeonidopoulosJ. LiQ.Z. LiJ.G.R. LimaD. LincolnS.L. LinnJ. LinnemannR. LiptonA. LucotteL. LuekingC. LundstedtC. LuoA.K.A. MacielR.J. MadarasV.L. MalyshevV. ManankovH.S. MaoT. MarshallM.I. MartinA.A. MayorovR. McCarthyT. McMahonH.L. MelansonM. MerkinK.W. MerrittC. MiaoH. MiettinenD. MihalceaC.S. MishraN. MokhovN.K. MondalH.E. MontgomeryR.W. MooreM. MostafaH. da MottaY. MutafE. NagyF. NangM. NarainV.S. NarasimhamN.A. NaumannH.A. NealJ.P. NegretA. NomerotskiT. NunnemannD. O'NeilV. OguriB. OlivierN. OshimaP. PadleyL.J. PanK. PapageorgiouN. ParasharR. PartridgeN. ParuaM. PaternoA. PatwaB. PawlikO. PetersP. PétroffR. PiegaiaB.G. PopeE. PopkovH.B. ProsperS. ProtopopescuM.B. PrzybycienJ. QianR. RajaS. RajagopalanE. RambergP.A. RapidisN.W. ReayS. ReucroftM. RidelM. RijssenbeekF. RizatdinovaT. RockwellM. RocoC. RoyonP. RubinovR. RuchtiJ. RutherfoordB.M. SabirovG. SajotA. SantoroL. SawyerR.D. SchambergerH. SchellmanA. SchwartzmanN. SenE. ShabalinaR.K. ShivpuriD. ShpakovM. ShupeR.A. SidwellV. SimakH. SinghV. SirotenkoP. SlatteryE. SmithR.P. SmithR. SnihurG.R. SnowJ. SnowS. SnyderJ. SolomonY. SongV. Sorı́nM. SosebeeN. SotnikovaK. SoustruznikM. SouzaN.R. StantonG. SteinbrückR.W. StephensD. StokerV. StolinA. StoneD.A. StoyanovaM.A. StrangM. StraussM. StrovinkL. StutteA. SznajderM. TalbyW. TaylorS. Tentindo-RepondS.M. TripathiT.G. TrippeA.S. TurcotP.M. TutsV. VanievR. Van KootenN. VarelasL.S. VertogradovF. Villeneuve-SeguierA.A. VolkovA.P. VorobievH.D. WahlH. WangZ.-M. WangJ. WarcholG. WattsM. WayneH. WeertsA. WhiteJ.T. WhiteD. WhitesonD.A. WijngaardenS. WillisS.J. WimpennyJ. WomersleyD.R. WoodQ. XuR. YamadaP. YaminT. YasudaY.A. YatsunenkoK. YipS. YoussefJ. YuM. ZanabriaX. ZhangH. ZhengB. ZhouZ. ZhouM. ZielinskiD. ZieminskaA. ZieminskiV. ZutshiE.G. ZverevA. ZylberstejnPhysics Letters B 531 (2002) 52-60. doi:10.1016/S0370-2693(02)01364-3journalPhysics Letters BCopyright © 2002 Elsevier Science B.V. All rights reserved.Elsevier B.V.0370-26935311-24 April 20022002-04-0452-60526010.1016/S0370-2693(02)01364-3http://dx.doi.org/10.1016/S0370-2693(02)01364-3doi:10.1016/S0370-2693(02)01364-3http://vtw.elsevier.com/data/voc/oa/OpenAccessStatus#Full2014-01-01T00:14:32ZSCOAP3 - Sponsoring Consortium for Open Access Publishing in Particle Physicshttp://vtw.elsevier.com/data/voc/oa/SponsorType#FundingBodyhttp://creativecommons.org/licenses/by/3.0/JournalsS300.3PLB18487S0370-2693(02)01364-310.1016/S0370-2693(02)01364-3Elsevier Science B.V.ExperimentsFig. 1Multiplicity distributions at s=1800 GeV for (a) forward and (b) central jet events, and at s=630 GeV for (c) forward and (d) central jet events.Fig. 2The fitted (a) signal and (b) background from the data of Fig. 1(a).Fig. 3Distributions of the (a) number of jets, (b) jet width, (c) Δφ between leading jets, for central diffractive (solid) and non-diffractive (dashed) jet events at s=1800 GeV. (d) The relative ratio of diffractive to non-diffractive events as a function of the average ET of the two leading jets.Fig. 4The ξ distributions for s=1800 GeV (a) forward and (c) central jets and for s=630 GeV (b) forward and (d) central jets, using the SV trigger with nCAL=nLØ=0. The shaded region shows the variance in the distribution due to energy scale uncertainties (see text).Table 1Attributes of the final data samplesData sampleJet |η|Jet ET (GeV)L (nb−1)Events1800 GeV forward>1.6>1262.9508521800 GeV central<1.0>154.5516567630 GeV forward>1.6>1216.928421630 GeV central<1.0>128.06481231800 GeV SV−>155700170393630 GeV SV−>1252964772Table 2The measured and predicted gap fractions and their ratiosGap fractionsSampleData (%)(i) Hard gluon (%)(ii) Flat gluon (%)(iii) Soft gluon (%)(iv) Quark (%)1800 GeV |η|>1.60.65±0.042.2±0.32.2±0.31.4±0.20.79±0.121800 GeV |η|<1.00.22±0.052.5±0.43.5±0.50.05±0.010.49±0.06630 GeV |η|>1.61.19±0.083.9±0.93.1±0.81.9±0.42.2±0.5630 GeV |η|<1.00.90±0.065.2±0.76.3±0.90.14±0.041.6±0.2Ratios of gap fractions630/1800 |η|>1.61.8±0.21.7±0.41.4±0.31.4±0.32.7±0.6630/1800 |η|<1.04.1±0.92.1±0.41.8±0.33.1±1.13.2±0.51800 |η|>1.6/|η|<1.03.0±0.70.88±0.180.64±0.1230.0±8.01.6±0.3630 |η|>1.6/|η|<1.01.3±0.10.75±0.160.48±0.1213.0±4.01.4±0.3Hard single diffraction in p̄p collisions at s=630 and 1800 GeVDØ CollaborationV.M.AbazovwB.AbbottbgA.AbdesselamkM.AbolinsaxV.AbramovzB.S.AcharyaqD.L.AdamsbgM.AdamsakS.N.AhmeduG.D.AlexeevwA.AltonawG.A.AlvesbE.W.AndersonapY.ArnoudiC.AvilaeM.M.BaarmandbbV.V.BabintsevzL.BabukhadiabbT.C.BaconabA.BadenatB.BaldinajP.W.BalmtS.BanerjeeqE.BarberisadP.BaringeraqJ.BarretobJ.F.BartlettajU.BasslerlD.BauerabA.BeanaqF.BeaudettekM.BegelbaA.BelyaevaiS.B.BerioG.BernardilI.BertramaaA.BessoniR.BeuselinckabV.A.BezzubovzP.C.BhatajV.BhatnagaroM.BhattacharjeebbG.BlazeyalF.BlekmantS.BlessingaiA.BoehnleinajN.I.BojkozT.A.BoltonarF.BorcherdingajK.BostT.BoseazA.Brandtbgbrandta@hepmail.uta.eduR.BreedonaeG.BriskinbfR.BrockaxG.BrooijmansajA.BrossajD.BuchholzamM.BuehlerakV.BueschernV.S.BurtovoizJ.M.ButlerauF.CanellibaW.CarvalhocD.CaseyaxZ.CasilumbbH.Castilla-ValdezsD.ChakrabortyalK.M.ChanbaS.V.ChekulaevzD.K.ChobaS.ChoiahS.ChoprabcJ.H.ChristensonajM.ChungakD.ClaesayA.R.ClarkadL.ConeyaoB.ConnollyaiW.E.CooperajD.CoppageaqS.Crépé-RenaudiniM.A.C.CummingsalD.CuttsbfG.A.DavisbaK.DebgS.J.de JonguM.DemarteauajR.DeminaarP.DemineiD.DenisovajS.P.DenisovzS.DesaibbH.T.DiehlajM.DiesburgajS.DoulasavY.DucrosmL.V.DudkoyS.DuensinguL.DuflotkS.R.DugadqA.DuperrinjA.DyshkantalD.EdmundsaxJ.EllisonahJ.T.EltzrothbgV.D.ElviraajR.EngelmannbbS.EnoatG.EppleybiP.ErmolovyO.V.EroshinzJ.EstradabaH.EvansazV.N.EvdokimovzT.FahlandagD.FeinacT.FerbelbaF.FilthautuH.E.FiskajY.FisyakbcE.FlattumajF.FleuretlM.FortneralH.FoxamK.C.FrameaxS.FuazS.FuessajE.GallasajA.N.GalyaevzM.GaoazV.GavrilovxR.J.GenikIIaaK.GenserajC.E.GerberakY.GershteinbfR.GilmartinaiG.GintherbaB.GómezeP.I.GoncharovzH.GordonbcL.T.GossbhK.GounderajA.GoussiouabN.GrafbcP.D.GrannisbbJ.A.GreenapH.GreenleeajZ.D.GreenwoodasS.GrinsteinaL.GroerazS.GrünendahlajA.GuptaqS.N.GurzhievzG.GutierrezajP.GutierrezbeN.J.HadleyatH.HaggertyajS.HagopianaiV.HagopianaiR.E.HallafS.HansenajJ.M.HauptmanapC.HaysazC.HebertaqD.HedinalJ.M.HeinmillerakA.P.HeinsonahU.HeintzauM.D.HildrethaoR.HiroskybjJ.D.HobbsbbB.HoeneisenhY.HuangawI.IashviliahR.IllingworthabA.S.ItoajM.JaffrékS.JainqR.JesikabK.JohnsacM.JohnsonajA.JonckheereajH.JöstleinajA.JusteajW.KahlarS.KahnbcE.KajfaszjA.M.KalininwD.KarmanovyD.KarmgardaoR.KehoeaxA.KhanovarA.KharchilavaaoS.K.KimrB.KlimaajB.KnutesonadW.KoaeJ.M.KohlioA.V.KostritskiyzJ.KotcherbcB.KothariazA.V.KotwalazA.V.KozelovzE.A.KozlovskyzJ.KraneapM.R.KrishnaswamyqP.KrivkovafS.KrzywdzinskiajM.KubantsevarS.KuleshovxY.KulikarS.KunoriatA.KupcogV.E.KuznetsovahG.LandsbergbfW.M.LeeaiA.LeflatyC.LeggettadF.Lehneraj1C.LeonidopoulosazJ.LibgQ.Z.LiajJ.G.R.LimacD.LincolnajS.L.LinnaiJ.LinnemannaxR.LiptonajA.LucotteiL.LuekingajC.LundstedtayC.LuoanA.K.A.MacielalR.J.MadarasadV.L.MalyshevwV.ManankovyH.S.MaodT.MarshallanM.I.MartinalA.A.MayorovzR.McCarthybbT.McMahonbdH.L.MelansonajM.MerkinyK.W.MerrittajC.MiaobfH.MiettinenbiD.MihalceaalC.S.MishraajN.MokhovajN.K.MondalqH.E.MontgomeryajR.W.MooreaxM.MostafaaH.da MottabY.MutafbbE.NagyjF.NangacM.NarainauV.S.NarasimhamqN.A.NaumannuH.A.NealawJ.P.NegreteA.NomerotskiajT.NunnemannajD.O'NeilaxV.OguricB.OlivierlN.OshimaajP.PadleybiL.J.PanamK.PapageorgiouakN.ParasharavR.PartridgebfN.ParuabbM.PaternobaA.PatwabbB.PawlikvO.PeterstP.PétroffkR.PiegaiaaB.G.PopeaxE.PopkovauH.B.ProsperaiS.ProtopopescubcM.B.Przybycienam2J.QianawR.RajaajS.RajagopalanbcE.RambergajP.A.RapidisajN.W.ReayarS.ReucroftavM.RidelkM.RijssenbeekbbF.RizatdinovaarT.RockwellaxM.RocoajC.RoyonmP.RubinovajR.RuchtiaoJ.RutherfoordacB.M.SabirovwG.SajotiA.SantorocL.SawyerasR.D.SchambergerbbH.SchellmanamA.SchwartzmanaN.SenbiE.ShabalinaakR.K.ShivpuripD.ShpakovavM.ShupeacR.A.SidwellarV.SimakgH.SinghahV.SirotenkoajP.SlatterybaE.SmithbeR.P.SmithajR.SnihuramG.R.SnowayJ.SnowbdS.SnyderbcJ.SolomonakY.SongbgV.Sorı́naM.SosebeebgN.SotnikovayK.SoustruznikfM.SouzabN.R.StantonarG.SteinbrückazR.W.StephensbgD.StokeragV.StolinxA.StoneasD.A.StoyanovazM.A.StrangbgM.StraussbeM.StrovinkadL.StutteajA.SznajdercM.TalbyjW.TaylorbbS.Tentindo-RepondaiS.M.TripathiaeT.G.TrippeadA.S.TurcotbcP.M.TutsazV.VanievzR.Van KootenanN.VarelasakL.S.VertogradovwF.Villeneuve-SeguierjA.A.VolkovzA.P.VorobievzH.D.WahlaiH.WangamZ.-M.WangbbJ.WarcholaoG.WattsbkM.WayneaoH.WeertsaxA.WhitebgJ.T.WhitebhD.WhitesonadD.A.WijngaardenuS.WillisalS.J.WimpennyahJ.WomersleyajD.R.WoodavQ.XuawR.YamadaajP.YaminbcT.YasudaajY.A.YatsunenkowK.YipbcS.YoussefaiJ.YubgM.ZanabriaeX.ZhangbeH.ZhengaoB.ZhouawZ.ZhouapM.ZielinskibaD.ZieminskaanA.ZieminskianV.ZutshibcE.G.ZverevyA.ZylberstejnmaUniversidad de Buenos Aires, Buenos Aires, ArgentinabLAFEX, Centro Brasileiro de Pesquisas Fı́sicas, Rio de Janeiro, BrazilcUniversidade do Estado do Rio de Janeiro, Rio de Janeiro, BrazildInstitute of High Energy Physics, Beijing, People's Republic of ChinaeUniversidad de los Andes, Bogotá, ColombiafCharles University, Center for Particle Physics, Prague, Czech RepublicgInstitute of Physics, Academy of Sciences, Center for Particle Physics, Prague, Czech RepublichUniversidad San Francisco de Quito, Quito, EcuadoriInstitut des Sciences Nucléaires, IN2P3-CNRS, Universite de Grenoble 1, Grenoble, FrancejCPPM, IN2P3-CNRS, Université de la Méditerranée, Marseille, FrancekLaboratoire de l'Accélérateur Linéaire, IN2P3-CNRS, Orsay, FrancelLPNHE, Universités Paris VI and VII, IN2P3-CNRS, Paris, FrancemDAPNIA/Service de Physique des Particules, CEA, Saclay, FrancenUniversität Mainz, Institut für Physik, Mainz, GermanyoPanjab University, Chandigarh, IndiapDelhi University, Delhi, IndiaqTata Institute of Fundamental Research, Mumbai, IndiarSeoul National University, Seoul, South KoreasCINVESTAV, Mexico City, MexicotFOM-Institute NIKHEF and University of Amsterdam/NIKHEF, Amsterdam, The NetherlandsuUniversity of Nijmegen/NIKHEF, Nijmegen, The NetherlandsvInstitute of Nuclear Physics, Kraków, PolandwJoint Institute for Nuclear Research, Dubna, RussiaxInstitute for Theoretical and Experimental Physics, Moscow, RussiayMoscow State University, Moscow, RussiazInstitute for High Energy Physics, Protvino, RussiaaaLancaster University, Lancaster, United KingdomabImperial College, London, United KingdomacUniversity of Arizona, Tucson, AR 85721, USAadLawrence Berkeley National Laboratory and University of California, Berkeley, CA 94720, USAaeUniversity of California, Davis, CA 95616, USAafCalifornia State University, Fresno, CA 93740, USAagUniversity of California, Irvine, CA 92697, USAahUniversity of California, Riverside, CA 92521, USAaiFlorida State University, Tallahassee, FL 32306, USAajFermi National Accelerator Laboratory, Batavia, IL 60510, USAakUniversity of Illinois at Chicago, Chicago, IL 60607, USAalNorthern Illinois University, DeKalb, IL 60115, USAamNorthwestern University, Evanston, IL 60208, USAanIndia University, Bloomington, IN 47405, USAaoUniversity of Notre Dame, Notre Dame, IN 46556, USAapIowa State University, Ames, IA 50011, USAaqUniversity of Kansas, Lawrence, KS 66045, USAarKansas State University, Manhattan, KS 66506, USAasLouisiana Tech University, Ruston, LA 71272, USAatUniversity of Maryland, College Park, MD 20742, USAauBoston University, Boston, MA 02215, USAavNortheastern University, Boston, MA 02115, USAawUniversity of Michigan, Ann Arbor, MI 48109, USAaxMichigan State University, East Lansing, MI 48824, USAayUniversity of Nebraska, Lincoln, NA 68588, USAazColumbia University, New York, NY 10027, USAbaUniversity of Rochester, Rochester, NY 14627, USAbbState University of New York, Stony Brook, NY 11794, USAbcBrookhaven National Laboratory, Upton, NY 11973, USAbdLangston University, Langston, OK 73050, USAbeUniversity of Oklahoma, Norman, OK 73019, USAbfBrown University, Providence, RI 02912, USAbgUniversity of Texas, Arlington, TX 76019, USAbhTexas A&M University, College Station, TX 77843, USAbiRice University, Houston, TX 77005, USAbjUniversity of Virginia, Charlottesville, VA 22901, USAbkUniversity of Washington, Seattle, WA 98195, USA1Visitor from University of Zurich, Zurich, Switzerland.2Visitor from Institute of Nuclear Physics, Krakow, Poland.Editor: L. MontanetAbstractUsing the DØ detector, we have studied events produced in p̄p collisions that contain large forward regions with very little energy deposition (“rapidity gaps”) and concurrent jet production at center-of-mass energies of s=630 and 1800 GeV. The fraction of events with forward or central jets associated with rapidity gaps is compared to predictions for hard diffraction. We also extract the momentum loss for scattered protons in such processes.Inelastic diffractive collisions are responsible for 10–15% of the p̄p total cross section, and have been described by Regge theory through the exchange of a pomeron [1]. Such events are characterized by a proton (or antiproton) carrying most of the beam momentum and by the absence of significant hadronic particle activity over a large region of pseudorapidity (η=−ln[tan(θ/2)], where θ is the polar angle relative to the beam). This empty region is called a rapidity gap and can be used as an experimental signature for diffraction. Recent interest in diffraction has primarily centered on the possibility of a partonic structure of the pomeron [2] in the framework of quantum chromodynamics (QCD). The soft color interaction model [3] provides an alternate description of diffraction without invoking pomeron dynamics, by hypothesizing that non-peturbative gluon emissions can create rapidity gaps. Experimental studies of hard single diffraction (HSD), which combines diffraction and a hard scatter (such as jet or W-boson production), can be used to determine the properties of the pomeron, or whether pomeron-based models are useful.The partonic nature of the pomeron was first inferred by the UA8 experiment [4] at the CERN Spp̄S collider at s=630 GeV from studies of diffractive jet events using a proton tag. Recent rapidity-gap-based analyses of diffractive jet [5–7], b-quark [8], and W-boson production [9] are consistent with a predominantly hard gluonic pomeron, but the production cross section at the Fermilab Tevatron is far lower than predictions based on data from the DESY ep collider HERA [5,10]. Recent results from the CDF collaboration using an antiproton tag show a difference in both shape and normalization between Tevatron (s=1800 GeV) and HERA data [11]. In this Letter we present new measurements of the characteristics of diffractive jet events, and of the fraction of central and forward jet events that contain forward rapidity gaps (“gap fraction”) at center-of-mass energies s=630 and 1800 GeV. These unique measurements place significant new constraints on the pomeron and diffractive models.In the DØ detector [12], jets are measured using the uranium/liquid-argon calorimeters with electromagnetic coverage to |η|<4.1 and coverage for hadrons to |η|<5.2. Jets are reconstructed using a fixed-cone algorithm with radius R=(Δη)2+(Δφ2)=0.7 (φ is the azimuthal angle). The jet energy is corrected as described in Ref. [13], except that we choose not to subtract energy from spectator parton interactions, which are unlikely for rapidity gap events.To identify rapidity gaps, we measure the number of tiles containing a signal in the LØ forward scintillator arrays (nLØ), and calorimeter towers (Δη×Δφ=0.1×0.1) above threshold (nCAL). The LØ arrays provide partial coverage in the region 2.3<|η|<4.3. A portion of the two forward calorimeters (3.0<|η|<5.2) is used to measure the calorimeter multiplicity, with a particle tagged by the deposition of more than 150 (500) MeV of energy in an electromagnetic (hadronic) tower. These thresholds are set to minimize noise from uranium decays, while maximizing sensitivity to energetic particles [14].For s=630 and 1800 GeV, we use triggers that required at least two jets with transverse energy ET>12 or 15 GeV (see Table 1) to study the dependence of the gap fraction on jet location. The forward jet triggers required the two leading jets to both have η>1.6 (or η<−1.6), while the central jet triggers had an offline requirement of |η|<1.0. These data were obtained during special low luminosity runs (1×1028–1×1030 cm−2s−1). At each s, we also implemented the so-called single veto trigger (SV), which, in addition to two jets, also required no hits in either the north or south LØ forward arrays. This trigger was used to obtain large samples of single diffractive candidate events. All final events require a single p̄p interaction, a vertex position within 50 cm of the center of the interaction region, and two leading jets that satisfy standard quality criteria [15]. The final data samples and their integrated luminosities (L) are listed in Table 1.Plots of nLØ versus nCAL for central and forward jet events at s=630 and 1800 GeV are shown in Fig. 1. For forward jet events, these quantities are defined by the η region on the side opposite the two leading jets, while for central jet events they are defined by the forward η interval that has the lower multiplicity. The distributions peak at zero multiplicity (nCAL=nLØ=0), in qualitative agreement with expectations for a diffractive component in the data. Overflow events with large multiplicity are not shown.The gap fraction is extracted from a fit to the data in Fig. 1. The non-diffractive (high multiplicity) background in the signal region is represented by a four-parameter polynomial surface, and the signal by a two-dimensional falling exponential. Fig. 2 shows the fitted (a) signal and (b) background from the data of Fig. 1(a). The shapes are in agreement with Monte Carlo simulations [14], the residual distributions for all four data samples are well-behaved, and all distributions have χ2/dof<1.2.Table 2 shows the gap fractions obtained for the four event samples. The values range from (0.22±0.05)% for central jets at s=1800 GeV to (1.19±0.08)% for forward jets at s=630 GeV. Uncertainties are dominated by those on the fit parameters. Additional small uncertainties from the dependence on the range of multiplicities used in the fits were added in quadrature. Potential sources of systematic error, such as the number of fit parameters, jet energy scale, trigger turn-on, tower threshold, luminosity, residual noise, and jet quality, yield only negligible variations in the gap fractions [14].Table 2 indicates that, for the data, gap fractions at s=630 GeV are larger than gap fractions at s=1800 GeV, and that gap fractions for forward jets are larger than for central jets. Table 2 also lists predicted gap fractions for several pomeron structure functions.We compare the data to Monte Carlo (MC) simulations using the hard diffractive event generator pompyt [16], which is based on the non-diffractive pythia [17] program. In pompyt, the pomeron is emitted from the proton with a certain probability (the flux factor [2]) and has a structure function s(β), where β is the fractional momentum of the pomeron (P) carried by the hard parton. We used the standard Donnachie–Landshoff flux factor [18] in this analysis: (1)fP/p(xP,t)=9βo24π2[F1(t)]21xP2α(t)−1, where βo=3.24 GeV−2 is the effective pomeron–quark coupling and F1(t) is the elastic form factor. The standard pomeron Regge trajectory is given by (2)α(t)=1+ϵ+α′t, where ϵ≃0.085 and the slope α′=0.025 are obtained by fits to world data.We then compared our data to four MC structure functions: (i) “hard gluon”, a pomeron consisting of two gluons, s(β)=6β(1−β); (ii) “flat gluon”, a constant pomeron structure, s(β)=1; (iii) “soft gluon”, a pomeron composed of many soft gluons, s(β)=6(1−β)5; and (iv) “quark”, the quark analog of (i), s(β)=(6/4)β(1−β). The normalization is determined by applying the momentum sum rule, ∫01s(β)dβ=1 (although this would only be applicable if the pomeron were a real particle). In each case, the gap fraction is defined as the cross section for jet events with a rapidity gap based on pompyt, divided by the jet cross section from pythia. Many uncertainties, such as the choice of proton parton densities, cancel in the ratio. A version of the fitting method is applied to correct for MC diffractive events that fail the gap selection criteria. Applying such corrections to the MC rather than the data keeps our measurement model independent. These correction factors range from a few per cent for central jets for (iii) to about 80% for forward jets in (i). For comparison, the CDF Collaboration (Ref. [5]) obtained a gap fraction of (0.75±0.10)% for forward jets at s=1800 GeV assuming a hard gluon structure; our corresponding measurement corrected in a similar manner is (0.88±0.05)%. We also note that Ref. [5] employed a non-standard flux factor, resulting in MC predictions about 25% larger than those using the Donnachie–Landshoff flux.The systematic uncertainties given for the MC predictions in Table 2 are dominated by the possible difference in energy scale between data and Monte Carlo, but also include uncertainties from the fitting procedure. Predicted yields for pomeron structures (i) and (ii) are far higher than we observe. While the quark structure gives a better description of our data than any of the gluon structures, it predicts too much diffractive production of W bosons [9].A hard gluonic pomeron can describe previous measurements [5–7,9], if combined with a flux factor that decreases with increasing s [19]. At s=1800 GeV a discrepancy factor (data gap fraction divided by MC fraction) of about 0.18 was obtained [5,8], but this model with a single discrepancy factor is clearly unable to describe our data. The ratios of gap fractions shown in the lower half of Table 2 provide new information that has little dependence on the flux factor. In particular, the ratios for jets with |η|>1.6 to jets with |η|<1.0 at fixed s still disagree with predictions for a hard or flat gluon structure of the pomeron, despite a complete cancellation of the flux factor.We have performed various fits of the MC results to the data and find that a gluon-dominated pomeron containing both soft and hard components, combined with a smaller flux factor, can accommodate our data. The data prefer a hard gluon component of 0.18±0.05+0.04−0.03 at s=1800 GeV and 0.39±0.04+0.02−0.01 at s=630 GeV, with an overall s-independent normalization of 0.43±0.03+0.08−0.06, where the first error is statistical and the second systematic (which includes the systematic error on both the Monte Carlo and data). Given the similar jet requirements at the two s values, it is not surprising that the data prefer a larger amount of hard gluon relative to soft at s=630 GeV. If the hard to soft ratio is constrained to be the same at both energies, we obtain 0.30±0.06 for the hard gluon fraction, and 0.38±0.08 (0.50±0.13) for the normalization at s=1800 (630) GeV, but the confidence level of the fit decreases from 56% to 1.9%. To significantly constrain the quark fraction requires additional experimental measurements. Ref. [8] found that a fit with 54% flat gluons and 46% hard quarks was able to describe their data, but applying such a constraint without allowing a significant soft gluon component or a much different quark fraction at s=630 GeV (near 100%) has a negligible probability of describing our data.Characteristics of HSD events are examined using the SV trigger. For central jets at s=1800 GeV, we plot in Fig. 3 the distributions of the number of jets (ET>8 GeV for Njets>2), the ET-weighted rms jet widths, the Δφ between the two leading jets, and the relative ratio of diffractive to non-diffractive events as a function of the average ET of the two leading jets. The solid lines in Fig. 3(a)–(c) correspond to HSD candidate events (nCAL=nLØ=0), and the dashed lines show the distributions for non-diffractive events (nCAL>0 and nLØ>0). These plots show that there are less jets in diffractive events, and that the jets are narrower and more back-to-back, indicating that diffractive events contain less overall radiation. Fig. 3(d) shows that there is little dependence of the gap fraction on average jet ET. The MC samples (not shown) have characteristics similar to the data.Finally, we measure the fractional momentum loss of the proton, defined as [20]: (3)ξ≈1s∑iETieηi, where the summation is over all observed particles. The η of the outgoing scattered proton or antiproton (and the rapidity gap) is always defined to be positive. Eq. (3) therefore heavily weights particles in the well-measured central region near the rapidity gap, while the loss of particles down the beam pipe at negative η has a negligible effect. Using pompyt events, where ξ can be determined from the momentum of the scattered proton, we have verified that Eq. (3) is reliable at both values of s and for different pomeron structures. A scale factor (2.2±0.3) derived from Monte Carlo is used to convert ξ measured from all particles to that from just electromagnetic energy depositions in the calorimeter [14]. The ξ distributions for forward and central jet events at s=630 and 1800 GeV are displayed in Fig. 4, with the shaded region showing the variance in the distribution due to energy scale uncertainties. These uncertainties cause a shift in ξ such that if the true distribution were below the histogram at small ξ values, it would be above the histogram at large values. The resolution is a weak function of ξ in the range of our data varying from 25% at the highest value to 35% at the lowest. Due to the fairly flat distributions, the resolution has little net effect on their shapes.The ξ distributions show the kinematic behavior expected of diffraction (M=ξs, where M is the mass of the diffractive system), peaking at larger ξ for (higher mass) central jet events than for forward jet events. Forward and central jet events at s=630 GeV also peak at larger ξ values relative to the corresponding distributions at s=1800 GeV, since for fixed jet ET and η, smaller s implies larger ξ. Although pomeron exchange traditionally is considered to dominate only for ξ<0.05, the ξ-distribution trends are reproduced by pompyt.In conclusion, we have measured properties of hard single diffraction at s=630 and 1800 GeV with jets at forward and central rapidities. The extracted gap fractions have no model-dependent corrections, and can be used to constrain a variety of models. To accommodate our data within the partonic pomeron framework requires a reduced flux factor combined with a gluonic pomeron containing significant soft and hard components. The complexity needed to make a pomeron structure model work indicates that other, non-pomeron based, models should be considered. The soft color interaction model, for example, seems to be more successful at predicting rates [3], although more detailed comparisons are necessary as the Monte Carlo programs become available. We have also measured the fractional momentum lost by the scattered proton and found larger values than expected for traditional pomeron exchange.AcknowledgementsWe thank the staffs at Fermilab and collaborating institutions, and acknowledge support from the Department of Energy and National Science Foundation (USA), Commissariat à L'Energie Atomique and CNRS/Institut National de Physique Nucléaire et de Physique des Particules (France), Ministry for Science and Technology and Ministry for Atomic Energy (Russia), CAPES and CNPq (Brazil), Departments of Atomic Energy and Science and Education (India), Colciencias (Colombia), CONACyT (Mexico), Ministry of Education and KOSEF (Korea), CONICET and UBACyT (Argentina), The Foundation for Fundamental Research on Matter (The Netherlands), PPARC (United Kingdom), Ministry of Education (Czech Republic), A.P. Sloan Foundation, NATO, and the Research Corporation.References[1]P.D.B.CollinsAn Introduction to Regge Theory and High Energy Physics1977Cambridge Univ. 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