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Colour Reconnection in W  W 

Colour Reconnection in W  W . “Particle Flow” CR analysis used by ADLO Basis for combination by LEP WG L published -1.5yr, D ~end 2004, A perhaps not? O -> Ed. Board (tomorrow) Outline Particle flow method Particle flow distributions in data Quantitative measures

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Colour Reconnection in W  W 

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  1. Colour Reconnection in WW • “Particle Flow” CR analysis used by ADLO • Basis for combination by LEP WG • L published -1.5yr, D ~end 2004, A perhaps not? • O -> Ed. Board (tomorrow) • Outline • Particle flow method • Particle flow distributions in data • Quantitative measures • Inclusive multiplicity (Miriam Watson) • Systematics • Summary Nige Watson

  2. Colour Reconnection in WW Highest energy jet • WWqqqq, default selection • W-j-j association,WWJPLH • 4 planes defined by jet axes from 4-c fit j1 j2 W1 W2 j4 j3 • Most energetic jet jet 1; jet 2 from same W • Choose jets 3, 4 to minimise  angles: (j2-j3)+ (j4-j3) • Particles projected onto 4 planes • Interested in particles “between”jets • True for >1 plane? Assign to closest in angle Nige Watson

  3. All data 189-206 GeV • Normalised particle density • no-CR models (upper) • Sk CR models (lower) • (to be added, with reduced data sample, 189/200/206) • Correlationsbetween bins • Compare • intra-W with • inter-W Nige Watson

  4. Particle Flow • Ratio intra-W/inter-W particle density: Rflow • no-CR models (upper) • CR models (lower) • Most sensitivity outside jet cores Nige Watson

  5. Quantitative measure • Quantify using ratio of sums, RN • Inverted since PN448 for ADLO consistency • bin-bin correlations important, integrate event-by-event • Range of integral must avoid jet-cores • D assign error as variance in MC subsets, AL use empirical correlation matrix from MC, O calculate error. Nige Watson

  6. Inclusive Multiplicity 206 GeV • First OPAL analyses used inclusive measurements (Nch, xp, etc.) • Main measure used by theorists in all CR papers • From all data, 189-206GeV n4q: 38.76 +- 0.13 +- 0.27 nqqlv: 19.39 +- 0.11 +- 0.09 D=-0.04 +- 0.25 +- 0.02 nqq: 19.39 +- 0.06 +- 0.11 Nige Watson

  7. Inclusive Multiplicity 206 GeV • Taus not used due to poorly defined tails in distribution qqtn only Nige Watson

  8. Ecm evolution of multiplicities 4q qqlv • Measure <Nch> for • 4q, qqlv, difference • Points are fully corrected data (stat. errs. shown) • Curves hadron level predictions • Data show • No significant Ecm dep. • No diff. 4q/qqlv • Average to give W->qq multiplicity 4q-2*qqlv Nige Watson

  9. Summary of systematics • Harmonise systematics in the two analyses as appropriate • Average of all s made, assuming • Flat energy dependence • Energy dependence correctly described by Koralw and Jetset • This case, average to 199.52 GeV and compare with full set CR models • WW Hadronisation • Model differences between {Jt,Hw,Ar, Jt/} • RN – model differences • Multiplicity, unfold JT as if background free data, all models • BEC, {intra-W — no-BE} • Background subtraction • Z  qq, vary production cross-section 5% qqqq, 20% qqlv • Z  qq Hadronisation model, max. effect from default to kk2f+{Py,Hw,Ar} and Py+Py • ZZ, vary production cross-section 11% (ZZ PR) • 4-f modelling: use KandY in place of Koralw/grc4f for non-WW-like 4f (+correct sWW by -2.5%) Nige Watson

  10. Summary of systematics • Detector effects • Variation of track quality cuts in data/MC • Unfolding method • Compare direct multiplicity method with (main) xp measurement • Energy dependence • Difference between Jetset parametrisation and s indep. • Cross-check or RN with qqlv events Nige Watson

  11. qqlv events for particle flow • Normalised particle density, using qqlv events • no-CR models • Data at s~200 GeV • Compare intra-W with inter-W regions intra inter intra inter Nige Watson

  12. Summary of particle flow systematics Nige Watson

  13. Summary of multiplicity systematics Nige Watson

  14. Summary of data, CR sensitivity • Predicted stat. sensitivity • Assumes CR models as at 199.5 GeV • Extreme scenario of SKI excluded • Most models completely compatible with data • Herwig the least favoured of non-CR models Nige Watson

  15. Nige Watson

  16. Scan of reconnection probability in SKI • Compare average RN with SKI • Best agreement for 34% events reconnected Better to scan in % reconnected than model parameter kI: reconnected fraction asymptotic with kI % CR Nige Watson

  17. Summary • Updated analysis using 189—208 GeV data • Data (just) exclude extreme case SKI • Data and models with/without CR compatible • Now use 2 phase Ar1 model which we implemented for qqlv • Data most consistent with SKI when 34% events reconnected • Limits weaker than previously due to detector corrections • May be changed during (by) editorial process • We find enhanced sensitivity (~x2) with Ar2/Ar1-2-phase model • Inclusive multiplicity analysis included (Miriam) • Editorial board waiting… Nige Watson

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