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Sept 2006WPCF 2006, Sao Paulo Brazil - lisa Non-gaussian effects1 Fitted HBT radii versus space-time variances in flow-dominated models Mike Lisa Ohio State University Frodermann, Heinz, MAL, PRC73 044908 (2006); nucl-th/0602023
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Sept 2006WPCF 2006, Sao Paulo Brazil - lisa Non-gaussian effects2 Outline motivation: possible problems in comparing models to data new formula for “fitting” model calculations application to two common models conclusions
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Sept 2006WPCF 2006, Sao Paulo Brazil - lisa Non-gaussian effects3 The many estimates of length scale HBT radii : parameters of Gaussian fits 3D fit to 3D CF R experimental procedure 1D fit to projections of 3D CF R 1D (and 3 ’s) questionable shortcut FWHM of 1D projections R* Space-time variances R-hat quick to calculate if S P (x) Gaussian, then C(q) Gaussian* and R = R 1D = R* = R-hat * Coulomb ignored throughout
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Sept 2006WPCF 2006, Sao Paulo Brazil - lisa Non-gaussian effects4 But neither S(x) nor C(q) is “ever” Gaussian * Coulomb ignored throughout STAR Phys. Rev. C 71 (2005) 044906 dN/dx Retiere & MAL PRC70 044907 (2004) Kisiel, Florkowski, Broniowski, Pluta PRC73 064902 (2006) if S P (x) Gaussian, then C(q) Gaussian* and R = R 1D = R* = R-hat The many estimates of length scale
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Sept 2006WPCF 2006, Sao Paulo Brazil - lisa Non-gaussian effects5 But neither S(x) nor C(q) is “ever” Gaussian * Coulomb ignored throughout if S P (x) Gaussian, then C(q) Gaussian* and R = R 1D = R* = R-hat What do experimentalists do? STAR Phys. Rev. C 71 (2005) 044906 Fit with ad-hoc alternate forms ? what to do with the parameters? Paic and Skowronski J. Phys. G31 1045 (2005) R o (fm) 4 6 R s (fm) 4 6 R l (fm) 4 6 q max (GeV/c) 0.10.2 “fit-range study” syst. err. “typical” study from STAR surely the way of the future... imaging
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Sept 2006WPCF 2006, Sao Paulo Brazil - lisa Non-gaussian effects6 But neither S(x) nor C(q) is “ever” Gaussian How much does this (rather than physics) dominate model comparisons? hydro Hirano:R 1D Soff:R-hat ZschiescheR* Heinz:R-hat if S P (x) Gaussian, then C(q) Gaussian* and R = R 1D = R* = R-hat What do theorists do? cascade AMPTR MPCR-hat RQMDR HRMR
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Sept 2006WPCF 2006, Sao Paulo Brazil - lisa Non-gaussian effects7 It can matter (how much, is model-dependent) AMPT, RQMD, HRM reproduce HBT radii best. Only these use “right” method coincidence? Hardtke & Voloshin PRC61 024905 (2000) RQMD - some difference R-hat R AMPT - huge difference Lin, Ko, Pal PRL89 152301 (2002)
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Sept 2006WPCF 2006, Sao Paulo Brazil - lisa Non-gaussian effects8 Our plan Examine two popular models which have published R-hat Blast-wave Heinz/Kolb B.I. hydro Compare R versus R 1D versus R-hat for fits (R and R 1D ), perform experimentalist’s “fit-range study” But first... an explanation of our “fit” procedure...
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Sept 2006WPCF 2006, Sao Paulo Brazil - lisa Non-gaussian effects9 The “data” to be “fit” Straight-forward to calculate CF outside long hydro CE EOSBlastwave
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Sept 2006WPCF 2006, Sao Paulo Brazil - lisa Non-gaussian effects10 Analytic calculation of radii (“fit”) 3D functional form: only good for C>1 not for noisy data F.O.M. to minimize:
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Sept 2006WPCF 2006, Sao Paulo Brazil - lisa Non-gaussian effects11 non-homogeneous linear equations invertable to find parameters P as per data, we take = fixed (not ´) (its value does not matter) Analytic calculation of radii (“fit”) 3D
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Sept 2006WPCF 2006, Sao Paulo Brazil - lisa Non-gaussian effects12 rather than one 4x4 set of equations for 4 parameters... 3 sets of 2x2 equations for 6 parameters similar technique used by Wiedemann, others Analytic calculation of radii (“fit”) 1D Similarly, for R 1D...
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Sept 2006WPCF 2006, Sao Paulo Brazil - lisa Non-gaussian effects13 BW projections - approximately Gaussian k T =0k T =0.3 GeV/c projection of 3D fit projection of 3D CF L projection appears least Gaussian
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Sept 2006WPCF 2006, Sao Paulo Brazil - lisa Non-gaussian effects14 BW - 1D studies Transverse radii: R 1D R-hat Longitudinal R 1D R-hat signif. fit-range systematic p T =0.1 p T =0.9 “HBT radii” from variances radii from ‘fit’ using various q-ranges STAR Au+Au @ 200 GeV 0-5% Phys. Rev. C 71 (2005) 044906 RoRo RsRs RLRL o s L RoRo RsRs RLRL o s L q max (GeV/c) K T (GeV/c)
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Sept 2006WPCF 2006, Sao Paulo Brazil - lisa Non-gaussian effects15 BW - 3D studies -coupling / 3D structure Ro fit range systematic still, BW agreement w/data persists “HBT radii” from variances radii from ‘fit’ using various q-ranges STAR Au+Au @ 200 GeV 0-5% Phys. Rev. C 71 (2005) 044906 q max (GeV/c) K T (GeV/c) RoRo RsRs RLRL RoRo RsRs RLRL
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Sept 2006WPCF 2006, Sao Paulo Brazil - lisa Non-gaussian effects16 CE Hydro projections - Gaussian fits “look bad” k T =0.3 GeV/ck T =0.6 GeV/c CF projections appear Gaussian projections of 3D Gaussian fit match poorly (unseen) 3D q structure of CF drives fit
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Sept 2006WPCF 2006, Sao Paulo Brazil - lisa Non-gaussian effects17 CE Hydro - 3D studies larger fit-range systematic (side is least affected, despite “looking” worst in projections) significant difference b/t R, R-hat “fitted” R agree better with data “HBT radii” from variances radii from ‘fit’ using various q-ranges STAR Au+Au @ 200 GeV 0-5% Phys. Rev. C 71 (2005) 044906 q max (GeV/c) RoRo RsRs RLRL K T (GeV/c) RoRo RsRs RLRL
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Sept 2006WPCF 2006, Sao Paulo Brazil - lisa Non-gaussian effects18 Hydro using 2 EoS similar non-Gaussian effects NCE always compared better to data, for R-hat and (by construction) for yields. apples::apples comparison further improves agreement K T (GeV/c) RoRo RsRs RLRL K T (GeV/c) RoRo RsRs RLRL “CE” EoS assuming Chem. Equilib until FO - original publications - More realistic “NCE” EoS STAR data Variance 3D “fit”
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Sept 2006WPCF 2006, Sao Paulo Brazil - lisa Non-gaussian effects19 BW & Hydro Qualitatively sim non-Gauss effects magnitude much smaller for BW conclusions about BW agreement ~same (still “good” but will increase) hydro agreement (for R o, R l ) improves in apples::apples comparison K T (GeV/c) RoRo RsRs RLRL “CE” EoS K T (GeV/c) RoRo RsRs RLRL “NCE” EoS Blast-wave K T (GeV/c) RoRo RsRs RLRL
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Sept 2006WPCF 2006, Sao Paulo Brazil - lisa Non-gaussian effects20 Summary / Conclusions Variety of length-scale estimators are compared to experimental HBT radii danger of apples::oranges comparison magnitude of difference is model-dependent analytic calculation of “fit” parameters in models R versus R 1D versus R-hat non-Gaussian features generate differences, fit-range systematic R≠R 1D : importance of global 3D fit (as experimentally done) R < R-hat in temporal components (long & out) agreement w/hydro much improved in apples::apples impact on “puzzles” effect significantly smaller for BW
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