Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil Hard Diffraction at DØ During Run I Michael Strang DØ Collaboration / Fermilab University of Texas, Arlington Central Rapidity Gaps (Hard Color Singlet Exchange) Forward Rapidity Gaps (Hard Single Diffraction)

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil DØ Detector EM Calorimeter L0 Detector beam (n l0 = # tiles in L0 detector with signal 2.3 < |  | < 4.3) Central Gaps EM CalorimeterE T > 200 MeV|  | < 1.0 Forward Gaps EM Calorimeter E > 150 MeV2.0 < |  | < 4.1 Had. CalorimeterE > 500 MeV3.2 < |  | < 5.2) Central Drift Chamber (n trk = # charged tracks with |  | < 1.0) End Calorimeter Central Calorimeter (n cal = # cal towers with energy above threshold) Hadronic Calorimeter

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil Particle Multiplicity Distributions

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil Measuring CSE

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil Hard Color Singlet Studies jet    QCD color-singlet signal observed in ~ 1 % opposite-side events ( p ) Publications DØ: PRL 72, 2332(1994) CDF: PRL 74, 885 (1995) DØ: PRL 76, 734 (1996) Zeus: Phys Lett B369, 55 (1996) (7%) CDF: PRL 80, 1156 (1998) DØ: PLB 440, 189 (1998) CDF: PRL 81, 5278 (1998) Newest Results FColor-Singlet fractions at  s = 630 & 1800 GeV  Color-Singlet Dependence on: , E T,  s (parton-x)

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil Data Selection Four data samples collected during :  s = 1800 GeV high, medium, & low jet E T triggers  s = 630 GeV low E T trigger Require centered event vertex Cut events with spurious jets Require single interaction Leading jets with |  | > 1.9  > 4.0 (Opposite-side events) E T cut : E T > 12 GeV ( low-E T 630, 7k events ) ( low-E T 1800, 48k events ) E T > 25 GeV ( med-E T 1800, 21k events) E T > 30 GeV (high-E T 1800, 72k events) (Also same-side control samples at both CM energies using L0 trigger to suppress SD signal for background studies)

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil Measurement of f s Count tracks and EM Calorimeter Towers in |  | < 1.0 E T >30 GeV f S 1800 = 0.94  0.04 stat  0.12 sys % jet    Negative binomial fit to “QCD” multiplicity f S = color-singlet fraction =(N data - N fit )/N total (Includes correction for multiple interaction contamination. Sys error dominated by background fitting.) High-E T sample (E T > 30 GeV,  s = 1800 GeV)

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil 630 vs Multiplicities Jet E T > 12 GeV, Jet |  | > 1.9,  > 4.0 R 1800 = 3.4  1.2 Opposite-Side DataSame-Side Data 1800 GeV: 630 Gev: n cal n trk f S 1800 (E T =19.2 GeV) = 0.54  0.06 stat  0.16 sys % f S 630 (E T = 16.4 GeV) = 1.85  0.09 stat  0.37 sys % 630

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil Color Singlet Models If color-singlet couples preferentially to quarks or gluons, fraction depends on initial quark/gluon densities (parton x) larger x  more quarks Gluon preference: perturbative two-gluon models have 9/4 color factor for gluons  Naive Two-Gluon model (Bj)  BFKL model: LLA BFKL dynamics Predictions: f S (E T ) falls, f S (  ) falls (2 gluon) / rises (BFKL) Quark preference:  Soft Color model: non-perturbative “rearrangement” prefers quark initiated processes (easier to neutralize color)  Photon and U(1): couple only to quarks Predictions: f S (E T ) & f S (  ) rise

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil Model Fits to Data Using Herwig 5.9 Soft Color model describes data  s = 1800 GeV

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil Fit Results Data favor “free-factor” and “soft-color” models “single-gluon” not excluded, but all other models excluded (assuming S not dependent on E T and  ) Apply Bayesian fitting method, calculate likelihood relative to “free-factor model” (parametrization as weighted sums of relative fractions of quarks and gluons in pdf) Color factors for free-factor model: C qq : C qg : C gg = 1.0 : 0.04 : 0 (coupling to quarks dominates)

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil Survival Probability Assumed to be independent of parton x (E T,  ) Originally weak  s dependence Gotsman, Levin, Maor Phys. Lett B 309 (1993) Subsequently recalculated GLM hep-ph/ Using free-factor and soft-color model (uncertainty from MC stats and model difference) with

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil Hard Color Singlet Conclusions DØ has measured color-singlet fraction for: 630 GeV and 1800 GeV same E T,  as a function of E T and  at 1800 GeV f S shows rising trend with E T,  Measured fraction rises with initial quark content (Assuming the Survival Probability is constant with E T and  ):  Consistent with a soft color rearrangement model preferring initial quark states  Inconsistent with two-gluon, photon, or U(1) models  Cannot exclude single-gluon model

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil Modifications to Theory  BFKL: Cox, Forshaw (manhep99-7) use a non- running  s to flatten the falling E T prediction of BFKL (due to higher order corrections at non-zero t)  Soft Color: Gregores subsequently performed a more careful counting of states that produce color singlets to improve prediction.

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil Hard Single Diffraction Studies  Measure min multiplicity here  OR FGap fractions (central and forward) at  s = 630 & 1800 GeV  Single diffractive  distribution hep-ex/ , submitted to PLB Measure multiplicity here

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil Data Selection Require single interaction Require central vertex Gap Fraction : (diffractive dijet events / all dijet events) *Forward Jet Trigger two 12GeV Jets |  |> , 28k events) 1800, 50k events) * Central Jet Trigger two 15(12) GeV Jets |  |< (12), 48k events) 1800(15), 16k events) SD Event Characteristics: *Single Veto Trigger two 15(12) GeV Jets and no hits in L0 North of South array 630(12), 64k events) 1800(15), 170k events)

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil Event Characteristics 1800 Forward Jets Solid lines show show HSD candidate events Dashed lines show non-diffractive events Less jets in diffractive events Jets are narrower and more back-to-back Diffractive events have less overall radiation Gap fraction has little dependence on average jet E T

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil 630 vs Multiplicities  s = 1800 GeV:  s = 630 GeV:

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil Fitting Method Example of fit for 1800 forward sample Signal is fit with a 2D falling exponential while background is fit with a 4 parameter polynomial surface Shapes are in agreement with Monte Carlo, the residual distributions are well behaved Distributions have  2 /dof < 1.2

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil Single Diffractive Results Data Sample Measured Gap Fraction 1800 Forward Jets 0.65% % % 1800 Central Jets 0.22% % % 630 Forward Jets 1.19% % % 630 Central Jets 0.90% % % * Forward Jets Gap Fraction > Central Jets Gap Fraction * 630 GeV Gap Fraction > 1800 GeV Gap Fraction Data Sample Ratio 630/1800 Forward Jets /1800 Central Jets Fwd/Cent Jets Fwd/Cent Jets  or Measure Multiplicity here (Gap Fraction = # diffractive Dijet Events / # All Dijets)

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil Comparison to MC f visible =  gap · f predicted   gap *Add diffractive multiplicity from MC to background data distribution *Fit to find percent of signal events extracted  Find predicted rate POMPYT x 2 / PYTHIA *Apply same jet  cuts as data, jet E T >12GeV *Full detector simulation * Model pomeron exchange in POMPYT26 (Bruni & Ingelman) * based on PYTHIA * define pomeron as beam particle * Use different structure functions

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil Pomeron Structure Fits  Demand data fractions composed of linear combination of hard and soft gluons, let overall  s normalization and fraction of hard and soft at each energy be free parameters  If we have a  s independent normalization then the data prefer : –1800: hard gluon 0.18±0.05( stat ) ( syst ) –630: hard gluon 0.39±0.04( stat ) ( syst ) –Normalization: 0.43±0.03( stat ) ( syst ) with a confidence level of 56%.  If the hard to soft ratio is constrained the data prefer: –Hard gluon: 0.30±0.04( stat ) ( syst ) –Norm. 1800: 0.38±0.03( stat ) ( syst ) –Norm. 630: 0.50±0.04( stat ) ( syst ) with a confidence level of 1.9%.  To significantly constrain quark fraction requires additional experimental measurements.  CDF determined 56% hard gluon, 44% quark but this does not describe our data without significant soft gluon or 100% quark at 630

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil Where  is the momentum fraction lost by the proton *Can use calorimeter only to measure *Weights particles in well-measured region *Can define for all events *  calculation works well * not dependent on structure function or center-of- mass energy *Collins (hep-ph/ )  true =  calc · 2.2± 0.3  Calculation

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil  distribution for forward and central jets using (0,0) bin  p p =   0.2 for  s = 630 GeV  s = 1800 GeV forward central  s = 630 GeV forward central Single Diffractive  Distributions

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil Summary  Measurements at both CM energies with same detector adds critical new information for examining pomeron puzzle –The higher rates at 630 were not widely predicted before the measurements  Pioneering work in Central Rapidity Gaps –Assuming x-independent survival probability, data support soft color rearrangement models (single gluon not excluded) –Modifications to theory based on data have occured  Forward gaps data –In a partonic pomeron framework require reduced flux factor combined with gluonic pomeron containing significant hard and soft components –Found larger fractional momentum lost by scattered proton than expected by traditional pomeron exchange –Results imply a non-pomeron based model should be considered.

Michael Strang Lishep02, Feb 5, 2002, Rio de Janeiro, Brazil Gap Efficiencies  Efficiency tag events with gap =  gap *Add diffractive multiplicity from MC to background data distribution *Fit to find percent of signal events extracted *Statistical error + MC energy scale error MC Sample1800 FWD JET1800 CENT JET Hard Gluon74%  10%34%  5% Flat Gluon66%  9%55%  7% Quark61%  8%18%  2% Soft Gluon22%  3%2.2%  0.8% MC Sample630 FWD JET630 CENT JET Hard Gluon92%  16%48%  6% Flat Gluon71%  14%60%  8% Quark55%  11%26%  3% Soft Gluon23%  4% 6.0%  4.8%