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NEW RESULTS ON Δ G/G FROM COMPASS EXPERIMENT AT CERN

NEW RESULTS ON Δ G/G FROM COMPASS EXPERIMENT AT CERN. Jan Paweł Nassalski Soltan Institute for Nuclear Studies, Świerk / Warsaw, Poland On behalf of COMPASS Collaboration. momentum 160 GeV intensity 2 ∙ 10 8 µ + /spill (4.8s/16.2s) longitudinal polarization ~ -76%. Beam. LHC. SPS.

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NEW RESULTS ON Δ G/G FROM COMPASS EXPERIMENT AT CERN

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  1. NEW RESULTS ON ΔG/G FROM COMPASS EXPERIMENT AT CERN Jan Paweł Nassalski Soltan Institute for Nuclear Studies, Świerk / Warsaw, Poland On behalf of COMPASS Collaboration PANIC'08

  2. momentum 160 GeV intensity 2∙108 µ+/spill (4.8s/16.2s) longitudinal polarization ~ -76% Beam LHC SPS μ+ N 6LiD, longitudinal polarization +53%, -50% NH3 (2007) Target PANIC'08

  3. COMPASS setup Kinematic coverage From 2006: larger acceptance (new target solenoid). Also 3-cell target. PANIC'08

  4. ΔG/G(x) determined from Photon-Gluon Fusion events N 1. Open charm cross section difference in charmed meson production scale set by (2mc)2  small background experimentally difficult 2. High-pThadron pairs cross section difference in 2-hadron production scale set by Q2 > 1GeV2 (this talk) or pt2 (quasi-real photoproduction) large statistics large background  analysis is MC dependent Analysing power Gluon polarization COMPASS analysis in LO PANIC'08

  5. ΔG/G(x) from open charm events Charmed meson reconstruction • 60 cm thick 6LiD target cells  no charm decay vertex reconstruction, • only invariant mass used, • K/π identification in RICH important, • cuts on D0 decay angle and zD. Use D* tagging;  cut on PANIC'08

  6. ΔG/G(x) from open charm events Event weighting Pt target polarisation Pμbeam polarisation aLLanalysing power f dilution factor S number of signal events B number of background events Each event is assigned a weight: aLLparametrised using Neural Networks trained on MC AROMA; 81% correlation: PANIC'08

  7. ΔG/G(x) from open charm events Event weighting D0 D* S and B determined from fitting mass distribution by Gaussians and an exponentials. raw large variation over kinematic region Σ - parametrised in terms of 10 variables describing event kinematics and the RICH response. weighted PANIC'08

  8. ΔG/G(x) from open charm events Results Systematic errors: PANIC'08

  9. ΔG/G(x) from high-pt events Data selection • Cuts on inclusive variables (x): • Q2 >1 GeV2, • 0.1 < y < 0.9. • Cuts on hadronic variables: • 2 charged hadrons required • pt1,2 > 0.7 GeV, • xF1,2 >0, z1,2 >0, z1 + z2 <0.95, • m2h1,h2 > 1.5 GeV2. • ~500k events after selection. (x): COMPASS results from quasi-real photoproduction 2002-2003 data have been published in PLB 633 (2006) 25-32. PANIC'08

  10. ΔG/G(x) from high-pt events QCD- Compton LO DIS N Determination of ΔG/G The analysis is done in LO (NLO partially taken by using parton shower in MC), resolved photon neglected. Usemeasured asymmetries: ALL2hand ALLinc; they have different contributions from 3 processes: PGF + + PANIC'08

  11. ΔG/G(x) from high-pt events Determination of ΔG/G Event weighting • For each event we determine: • weight w = f D Pμβ, • Acorr.  f, D and Pμare obtained from the data. All R (fractions of processes), aLL ( analysing powers), xCand xgare obtained from inclusive and high-ptMonte Carlo (LEPTO with MRST2004LO and JETSET fragmentation).  It is important to have good agreement between data and MC. PANIC'08

  12. ΔG/G(x) from high-pt events Data vs. MC for inclusive variables xBj y Q2 PANIC'08

  13. ΔG/G(x) from high-pt events Data vs. MC for hadronic variables leading hadron subleading hadron pt1 pt2 pt12+ pt22 After tuning of JETSET fragmentation PANIC'08

  14. ΔG/G(x) from high-pt events Parametrisation using Neural Networks • R, aLL, xCand xgare given by parameterizations obtained from Neural Networks • trained on MC using following input: • xBj and Q2 – for inclusive sample, • xBj ,Q2,pl1,2,pt1,2 – for high-pt sample. Average values for high-pt events: PANIC'08

  15. ΔG/G(x) from high-pt events Results Systematic errors: PANIC'08

  16. ΔG/G(x) from COMPASS New (not published) COMPASS high-pT Hermes high-pT COMPASS open charm PANIC'08

  17. SUMMARY and PROSPECTS • New, preliminary results from open charm and high-pt events • indicate ΔG/G  0 for xg  0.1. • Prospects for new results from open charm events: • - include data from 2007, • - do NLO analysis. • Prospects for new results from high-pt events: • - include data from 2006 and 2007, • - use one high-pt hadron, • - determine ΔG/G in 2-3 bins of xg. PANIC'08

  18. SPARES PANIC'08

  19. ΔG/G(x) from open charm events Event weighting large variation over kinematic region S and B determined from fitting mass distribution by Gaussians and an exponential. Σ - parametrised in terms of 10 variables describing event kinematics and the RICH response: PANIC'08

  20. ΔG/G(x) from high-pt events Parametrisation using Neural Networks • R, aLL, xCand xgare given by parameterizations obtained from Neural Networks • trained on MC using following input: • xBj and Q2 – for inclusive sample, • xBj ,Q2,pl1,2,pt1,2 – for high-pt sample. Output variables of NN: o1 and o2, where Average values for high-pt events: PANIC'08

  21. PANIC'08

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