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What we’ll discuss..

What we’ll discuss. Techniques used to scale and compare from pp to NN Description of ingredients recipes used by experiments caveats and uncertainties Aim: everyone on same page for rest of workshop. pp data: What do we have?. ISR  s = 24 - 64 GeV pp SppS  s = 200 - 900 GeV

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What we’ll discuss..

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  1. What we’ll discuss.. • Techniques used to scale and compare from pp to NN Description of • ingredients • recipes used by experiments • caveats and uncertainties • Aim: everyone on same page for rest of workshop.

  2. pp data: What do we have? ISR s = 24 - 64 GeV pp SppS s = 200 - 900 GeV Tevatron s = 500 - 1800 GeV • Ignore difference btw and , small compared to other uncertainties • UA1 and CDF: (h++ h-)/2 • ISR: p, K, p and p

  3. Parameterization: The power law fits Phys. Rep. 23 (1976) 1 Sivers, Brodsky, Blankenbecler CERN-ISR A+B  C + X: N depends on particle, for pp  0 + X q-q : ~ p^ -4 from QCD h-h : ~ p^ -8?, no real guidance … current form (used already by UA1) : perhaps born out of desperation?

  4. Compilation Data available over wide range of s, but not for 130 GeV

  5. Consistency in data: same experiment UA1 at 500 GeV Data and power law are consistent UA1 at 200 GeV Data and reported power law are offset

  6. Consistency in Data: between experiments CDF UA1 Difference of ~3 at 6 GeV

  7. pp @ s = 130 GeV • Obtain  (needed for Npart and Ncoll) • Obtain power law parameters A, p0 and n • Procedure: • Use the available data and interpolate • Not all data sets are of equal quality • Not all data sets are for h+, h- • Check for consistency • difficult to estimate systematic uncertainties

  8. Cross section •  @ 200 GeV not measured • UA5 measured at 900 GeV, and ratio 200/900 • Must use parameterization • e.g. PDG gives

  9. Obtaining parameters... • One way… • Interpolate the s dependence of the fit parameters • need care, p0 and n are highly correlated • Another way… • Interpolate the measured cross sections at several fixed p^ • Gives interpolated p^ distribution • Fit this distribution, obtain parameters

  10. First method: use scaling with s

  11. First method:Constraints on p0 and n • Can constrain <pt> and dNch/d • Useful relations for power law

  12. First Method: Extrapolate • Try various fits: 1st & 2nd deg. poly., exp, etc. • Fit p0, obtain n via <pt> and vice versa Errors above denote: STAR: variations in fits to parameters PHENIX: variations in parameters from different data interpolations (2nd method) Leads to a 20-30% uncertainty at p^=6 GeV

  13. Resulting pt-Uncertainties, and “R(130/200)” Power law: E d3/dp3 = A (1+pt/p0) –n Ratio between power law at 130 to power law at 200 GeV PHENIX n=12.4, p0 = 1.71 STAR n=12.98, p0=1.895

  14. pp to AA: Glauber model and TAB • Calculation can be done (even on the web)… but how big are the uncertainties? • Woods-Saxon: from e-A • Overlap Integral: • s: • Binary Collisions: • Participants:

  15. Uncertainties! For 5% most central collisions: <Ncoll> = 1050-1100 TAB=26±2 mb-1 Calculate Npart and Ncoll What happens for peripheral? PHOBOS M.C. study P. Steinberg QM’01

  16. Plotting the data: RAA • High p^ processes ~ Ncoll • Nuclear modification factor : • If no anomalous effects, data at high p^ should approach 1 when plotted in this form. • … the deviations from 1 are what this workshop is all about...

  17. Conclusions • s = 200 GeV • Ok, since measure pp @ RHIC (maybe pA too?) • s = 130 GeV • Uncertainties, no data, so must extrapolate • currently available data differ by ~3 at high pt • will there be pp at this energy at RHIC? • Ratios • central/pp • Ok, measure with same systematics (== same experiment) • central/peripheral • Ok for trends, syst. cancel in same experiment • Uncertainties in normalization, Ncoll for peripheral of the order of 20-30%

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