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Selected topics in Heavy Ion Physics Primorsko 2014 Peter Hristov
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Lecture 2 QCD phase diagram Yields, spectra, thermodynamics 2
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Phase diagram of quark-gluon plasma (QGP) 3 Temperature Baryon Density Neutron stars Early Universe Nuclei Nuclon gas Hadron gas “color superconductor” Quark-gluon plasma TcTc 00 Critical point? vacuum “Color-Flavor Locking” High temperature High baryon density Free quarks Restoration of chiral symmetry Increased collision energy
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Yields, spectra, thermodynamics 4 Based on the lectures of R.Bellwied, A.Kalweit, J.Stachel and QM2014 overview of J.F. Grosse-Oetringhaus
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Statistical hadronization models 5 Assume systems in thermal and chemical equilibrium Chemical freeze-out: defines yields & ratios inelastic interactions cease particle abundances fixed (except maybe resonances) Thermal freeze-out: defines the shapes of p T, m T spectra: elastic interactions cease particle dynamics fixed
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Reminder: Boltzmann thermodynamics 6 The maximum entropy principle leads to the thermal most likely distribution for different particle species. Macro-state is defined by given set of macroscopic variables (E, V, N) Entropy S = k B ln Ω, where Ω is the number of micro-states compatible with the macro-state Compatibility to a given macroscopic state can be realized exactly or only in the statistical mean. L. Boltzmann
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Ensembles in statistical mechanics 7 Micro-canonical ensemble: isolated system with fixed number of particles ("N"), volume ("V"), and energy ("E"). Micro-states have the same energy and probability. Statistical model for e+e - collisions. Canonical ensemble: system with constant number of particles ("N") and the volume ("V”), and with well defined temperature ("T"), which specifies fluctuation of energy (system coupled with heat bath). in small system, with small particle multiplicity, conservation laws must be implemented locally on event-by-event basis (Hagedorn 1971, Shuryak 1972, Rafelski/Danos 1980, Hagedorn/Redlich 1985) => severe phase space reduction for particle production “canonical suppression” Examples: Strangeness conservation in peripheral HI collisions; low energy HI collisions (Cleymans/Redlich/Oeschler 1998/1999); high energy hh or e+e - collisions (Becattini/Heinz 1996/1997) Grand canonical ensemble: system with fixed volume ("V") which is in thermal and chemical equilibrium with a reservoir. Both, energy ("T") and particles ("N") are allowed to fluctuate. To specify the ("N") fluctuation it introduces a chemical potential (“ μ ”) in large system, with large number of produced particles, conservation of additive quantum numbers (B, S, I 3 ) can be implemented on average by use of chemical potential; asymptotic realization of exact canonical approach Example: Central relativistic heavy-ion collisions
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Example: barometric formula 8 Describes the density of the atmosphere at a fixed temperature Probability to find a particle on a given energy level j: Energy on a given level is simply the potential energy: E pot = mgh Boltzmann factor Partition function Z (Zustandssumme = “sum over states”)
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Thermal model for heavy ion collisions 9 Grand-canonical partition function for an relativistic ideal quantum gas of hadrons of particle type i (i = π, K, p,…): quantum gas: (+) for bosons, (-) for fermions g i – spin degeneracy – relativistic dispersion relation – chemical potential representing each conserved quantity Only two free parameters are needed (T, μ B ), since the conservation laws permit to calculate Baryon number: V Σ n i B i = Z+N =>V Strangeness and charm: V Σ n i S i = 0 => μ S ; V Σ n i C i = 0 => μ C Charge: V Σ n i I 3i = (Z-N)/2 => μ I3 See the derivation i.e. in the textbook of R. Vogt
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Thermal model for heavy ion collisions 10 From the partition function we can calculate all other thermodynamic quantities: The model uses iterative minimization procedure: For a given set of (T, μ B ) the other quantities are recalculated to ensure conservation laws; Compare calculated particle yields/ratios with experimental results in a 2 - minimization in (T, μ B ) plane (thermal fit).
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Implementations of statistical models 11 Original ideas go back to Pomeranchuk (1950s) and Hagedorn (1970s). Precise implementations and also interpretations differ from group to group: K. Redlich P. Braun-Munzinger, J. Stachel, A. Andronic (GSI) Eigen-volume correction: ideal gas → Van-der-Waals gas emphasis on complete hadron list F. Becattini non-equilibrium parameter SN J. Rafelski (SHARE) non-equilibrium parameter SN and qN J. Cleymans (THERMUS) Allows also canonical suppression in sub-volumes of the fireball W. Broniowski, W. Florkowski (THERMINATOR) space time evolution, pT-spectra, HBT, fluctuations
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Comparison to experimental data 12 A. Andronic et al., Phys.Lett.B673 (2009) 142Thermal model from: A.Andronic et al, Nucl. Phys.A 772 (2006) 167 Resonance ratios deviate Rescattering & regeneration Short life times [fm/c] medium effects K* < *< (1520) < 4 < 6 < 13 < 40
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SHM model comparison based on yields including multi- strange baryons Data: L.Milano for ALICE (QM 2012) Fit: R. Bellwied Either a bad fit with a common freeze-out….. 148 164 160 154 152..or a good fit with a flavor specific freeze-out => Potential evidence of flavor dependence in equilibrium freeze-out 13
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Thermal Fits p-Pb Statistical model fits Freeze-out temperature Volume µ b Equilibrium? ( S, q ) High-multiplicity p-Pb THERMUS 2.3 S = 0.96 ± 0.04 approximate thermal equilibrium 2 /ndf rather large though (about 30) (model – data) / data K K 0 K * p d THERMUS: CPC 180 (2009) 84 14 JFGO@QM2014
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Physics origin? Non equilibrium thermal model Baryon annihilation Freeze-out temperature hierarchy Incomplete hadron spectrum Thermal Fits Pb-Pb Equilibrium models yields T = 156-157 MeV But with 2 /ndf of about 2 Plenary: M. Floris Fits without the proton (and K*) –similar T, V but 2 /ndf drops from about 2 to about 1 proton anomaly? Thermus 2.3GSISHARE 3 (model – data) / data THERMUS: CPC 180 (2009) 84 | GSI: PLB 673 (2009) 142 | SHARE: arXiv:1310.5108 15 JFGO@QM2014
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Statistical Hadronic Models: Misconceptions 16 Model says nothing about how system reaches chemical equilibrium Model says nothing about when system reaches chemical equilibrium Model makes no predictions of dynamical quantities Some models use a strangeness suppression factor, others not Model does not make assumptions about a partonic phase; However the model findings can complement other studies of the phase diagram (e.g. Lattice-QCD)
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Experimental QCD phase diagram 17 Build accelerator capable to work at different energies and to use different nuclei Build experiments with PID capabilities Take and calibrate data For all the particles: π, K, p, Λ, Ξ, Ω, Φ, K* 0, d, 3 He we have to: Use PID detectors and topological selection to measure raw spectrum Correct for efficiency, acceptance, feed-down, contamination Fit the spectrum and extrapolate unmeasured region Determine the integrated yield dN/dy Do the thermal fit and extract (T, μ B )
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Strangeness: Two historic QGP predictions restoration of symmetry increased production of s mass of strange quark in QGP expected to go back to current value (m S ~ 150 MeV ~ T c ) Pauli suppression for (u,d) copious production of ss pairs, mostly by gg fusion [Rafelski: Phys. Rep. 88 (1982) 331] [Rafelski-Müller: P. R. Lett. 48 (1982) 1066] deconfinement stronger effect for multi-strange baryons by using uncorrelated s quarks produced in independent partonic reactions, faster and more copious than in hadronic phase strangeness enhancement increasing with strangeness content [Koch, Müller & Rafelski: Phys. Rep. 142 (1986) 167] 18
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The SPS ‘discovery plot’ (WA97/NA57) Unusual strangeness enhancement N part 19
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Strangeness enhancement: SPS, RHIC, LHC enhancement still there at RHIC and LHC effect decreases with increasing √s strange/non-strange increases with √s in pp 20
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Strangeness enhancement (in AA) or suppression (in pp)? 21 For smaller collision systems (pp, pPb, peripheral HI), the total number of produced strange quarks is small and strangeness conservation has to be explicitly taken into account => canonical ensemble => suppression in small systems Since the enhancements are quoted relative to pp they are due to a canonical suppression of strangeness in pp. s s canonical grand-canonical s s s s s s s s TBTB TBTB μ s s P. Braun-Munzinger, K. Redlich, J. Stachel arXiv:nucl-th/0304013
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“Thermal” Spectra Invariant spectrum of particles radiated by a thermal source: where:m T = (m 2 +p T 2 ) ½ transverse mass (requires knowledge of mass) = b b + s s grand canonical chem. potential (central AA) Ttemperature of source Neglect quantum statistics (small effect) and integrating over rapidity gives: R. Hagedorn, Supplemento al Nuovo Cimento Vol. III, No.2 (1965) At mid-rapidity E = m T cosh y = m T and hence: “Boltzmann” 22
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“Thermal” spectra and radial expansion (flow) The “thermal” fit fails at low p T Different spectral shapes for particles of differing mass strong collective radial flow Spectral shape is determined by more than a simple T at a minimum T, T mTmT 1/m T dN/dm T light heavy T purely thermal source explosive source T, mTmT 1/m T dN/dm T light heavy 23
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Thermal + Flow: “Traditional” Approach 1. Fit Data T2. Plot T(m) T th, T is the transverse expansion velocity. 2 nd term = KE term (½ m 2 ) common T th, . Assume common flow pattern and common temperature T th 24
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Blast wave: a hydro inspired description of spectra R ss Ref. : Schnedermann, Sollfrank & Heinz, PRC48 (1993) 2462 Spectrum of longitudinal and transverse boosted thermal source: Static Freeze-out picture, No dynamical evolution to freeze-out 25
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Momentum spectra for identified particles 26
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Ratios: K K * K 0 p d 3 He 3 H pp: no significant energy dependence Strangeness enhancement Deuteron enhancement K* Suppression p ? pp 0.9 TeV 2.76 TeV 7 TeV pp p-Pb Pb-Pb JFGO@QM2014
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