Presentation is loading. Please wait.

Presentation is loading. Please wait.

System-size dependence of strangeness production, canonical strangeness suppression, and percolation Claudia Höhne, GSI Darmstadt.

Published byAbraham Hill Modified over 8 years ago

Similar presentations

Presentation on theme: "System-size dependence of strangeness production, canonical strangeness suppression, and percolation Claudia Höhne, GSI Darmstadt."— Presentation transcript:

1 System-size dependence of strangeness production, canonical strangeness suppression, and percolation Claudia Höhne, GSI Darmstadt

2 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 Outline introductiondata (central A+A, top SPS energy) statistical model percolation model percolation + statistical model discussionresults input parameters/ assumptions  s transfer to minimum bias Pb+Pb RHIC energies multistrange particles other system-size dependent variables? summary

3 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 Introduction energy system sizerelative strangeness production as possible indicator for the transition from confined to deconfined matter energy dependence maximum at ~ 30 AGeV beam energy system-size variation complementary information! [NA49, M. Gazdzicki, QM04]

4 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 Data system-size dependence of relative strangeness production fast increase with system size saturation reached at about N part =60 * pp CC, SiSi SS (2% central) PbPb (5% central) lines are to guide the eye (exponential function) * 80% of full enhancement between pp and PbPb 158 AGeV 200 AGeV 158 AGeV [NA49, PRL 94 (2005) 052301]

5 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 Statistical model [Tounsi and Redlich, J. Phys. G: Nucl. Part. Phys 28 (2002) 2095] statistical model: canonical strangeness suppression  qualitative agreement quantitatively in disagreement: 80% of enhancement reached at N part ~ 9 (s=1)  calculated for a certain V common assumption V  N part   E s [NA49, PRL 94 (2005) 052301] define V more carefully!

6 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 Percolation model [Satz, hep-ph/0212046)] microscopic picture of A+A collision: subsequent N+N collisions take place in immediate space-time density still individual „collisions“/ individual hadronization? suppose that overlapping collisions (strings) form clusters  percolation models

7 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 The Model 1) Formation of coherent clusters: “correlation volume“ percolation of collisions/ strings 2) Hadronization of clusters  relative strangeness production statistical model (canonical strangeness suppression) assume that „correlation volumes“ from percolation calculation can be identified with volume used in the statistical model Separate collision process/ particle production into two independent steps: Any effects of interactions in the final hadronic expansion stage are neglected.

8 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005... once more: step 1 – percolation calculation: clustersize vs density relate density to N wound step 2 – hadronization of clusters canonical strangeness suppression from statistical model N wound V correlation EsEs combine: E s vs. N wound

9 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 step 1 – VENUS: N wound (  VENUS simulations (2d)* collision density <  in dependence on N wound density distribution (common profile used)  coll2d (N wound ) =  percolation * simplification: 2d calculation in particular for light systems penetration time of nuclei < 1fm/c  no further subdivision of longitudinal dimension

10 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 step 1 – percolation calculation 2d: projection of collisions to transverse plane distribute strings/ collisions effective r string = 0.3 fm * form clusters from overlapping strings VENUS: 2d density distribution of strings/ collisions * lattice-QCD: see e.g. argument from Satz in PLB 442 (1998) 14 A s =  r s 2 A AcAc

11 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 step 1 – percolation calculation (II) mean cluster size rises steeply with density using density distribution of collisions weakens rise compared to uniform distribution uniform distribution of strings density distribution (VENUS) transverse area A = geometrical overlap zone of colliding nuclei using R enclosing 90% of nuclear density distribution

12 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005  areasize distribution combine N wound (  ) and A c (  )  areasize distribution vs N wound even for higher densitys small clusters are present !

13 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 step 2 – hadronization of clusters correlate relative s-production to clustersize  statistical model: strangeness suppression factor  (V) [Rafelski and Danos, Phys. Lett. B97 (1980) 279] r 0 nucleon radius s-content in partonic/ hadronic phase? in practice: both assumptions yield similar result s=1

14 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 combine results & compare to data data well described! r s = 0.3fm, V h = 3.8fm 3 experimentally Wroblewski factor s not accessible: approximate by E s, assume E s   V  N wound calculation taking clustersize distribution into account

15 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 Summary (I) good description of data with physically reasonable parameters essential for good description of data: take clustersize distribution into account, not only mean values  makes all the difference! (steep increase of  (V))  statistical model can also be successfully applied! even if partonic scenario is used for calculation of  (V), no real statement concerning the nature of the „correlation volumes“ is made – only that s- production is correlated to clustersize plausible: same nature as in central Pb+Pb but smaller size in e.g. C+C p+p collisions – strings, Pb+Pb collisions – essentially one large cluster A+A collisions with small A, e.g. C+C: several independent clusters of small/ medium size

16 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 Discussion sensitivity of model to assumptions/ input/ parameters?  s ? transfer to other systems (s=1): minimum bias Pb+Pb at 158 AGeV RHIC energies multistrange particles? percolation ansatz  relate system-size dependence of s-production to geometrical properties can the same ansatz be used for the system-size dependence of other variables?

17 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 Assumptions/ input assumptions/ input/ parameters for this model: 2dimensional calculation  essential features already covered! scaling parameter a: E s = a   determined by data percolation calculation: r s, V h  V h total enhancement, r s shape standard (r s =0.3fm, V h =3.8 fm 3 ) r s =0.2fm, V h =3.1 fm 3 r s, V h not uniquely defined, can be played against each other to certain extend

18 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 Assumptions/ input (II) statistical model:  (V,T,m s )  change in m s can e.g. be accomplished by V h standard (T=160 MeV, m s =280 MeV) T=160 MeV, m s =150 MeV, V h =2.7 fm 3

19 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 Assumptions/ input (III) collision density distribution  only very slight change standard (2d density distribution) uniform distribution (V h =4 fm 3 ) there is a certain sensitivity to parameter variation several reasonable pairs can be found to describe data always: main effect comes from clustersize distribution!

20 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 ss here: any possible strangeness undersaturation (   s ) neglected total increase of relative strangeness production adjusted with V h however: note similar ansatz in Becattini et al., PRC 69 (2004) 024905 Manninen, SQM04  two component model: fix  s =1 but allow for N s single collisions similar to percolation result!

21 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 Transfer: minimum bias Pb+Pb main difference to central collisions: slower increase of collision density A(N wound ) more difficult to define  increase in E s slower (observed in experiment!) grey area: A defined as geometrical overlap zone of colliding nuclei using R enclosing 90% (50%) of nuclear density distribution in qualitative agreement with preliminary NA49 data

22 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 [PHENIX, PRC 69 (2004) 034909] midrapidity Transfer: other energies (RHIC) assume that same s-production mechanism holds for top-SPS and RHIC energies  transfer calculation only change: calculate N wound (  ), A(N wound ) for Au+Au at different centralities  Cu+Cu: basically same dependence expected (dashed line)! AGS energies more complicated? hadronic scenario, rescattering [PHENIX, PRC 69 (2004) 034909] midrapidity

23 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 Transfer: multistrange particles in principle simple to extend: however: here a calculation for a partonic scenario is used  for translation to hadronic yields some kind of „coalescence“ assumption needed calculation for canonical strangeness suppression for all s=1,2,3 particles  definition of E s for s=2,3 needed

24 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 Transfer: multistrange particles (II) [NA57, nucl-ex/0403036 (QM04)] s=2:  s=3: (   +   )/N wound should be comparable NA57 data – normalization to pBe (errors!) characteristic features also captured for s=2,3

25 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 percolation & system-size dependence percolation ansatz: connect system-size dependence of variables with geometrical properties of the collision system increase of V cluster  relate physical properties to V cluster strangeness production several clusters in small systems  fluctuations! ? strangeness ?

26 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 and vs. system-size and depend on the size of the cluster (and string density) therefore p t and N ch changes with cluster size [Braun, del Moral, Pajares, PRC 65, 024907 (2002)] [Dias de Deus, Ferreiro, Pajares, Ugoccioni, hep-ph/0304068]

27 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 - fluctuations Ferreiro, del Moral, PajaresPRC 69, 034901 (2004) correlate clustersize to : Schwinger mechanism for single strings  increase with clustersize p+p and Pb+Pb: small fluctuations because essentially one system exists: single string or one large cluster in between: many differently sized clusters with (strongly) varying  fluctuations

28 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 multiplicity fluctuations ? same picture should be applicable here! [Mrowczynski, Rybczynski, Wlodarczyk, PRC 70 (2004) 054906] relate multiplicity and fluctuations strangeness fluctuations?? NA49 preliminary [Rybczynski for NA49, J.Phys.Conf.Ser 5 (2005) 74]

29 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 Summary successful description of relative strangeness production in dependence on the system-size for central A+A collisions at 158 AGeV beam energy by combining a percolation calculation with the statistical model essential: take clustersize distribution into account (not only mean values!)  p+p collisions – strings, Pb+Pb collisions – essentially one large cluster  A+A collisions with small A, e.g. C+C: several independent clusters of small/ medium size this picture can successfully be transfered to minimum bias Pb+Pb at 158 AGeV, centrality dependent Au+Au at RHIC (200 AGeV), multistrange particles percolation model also successful for describing system-size dependence of other variables: increase of, with centrality fluctuations (  multiplicity fluctuations ?) J/  suppression

30 Claudia Höhne Critical Point and Onset of Deconfinement, Bergen, March/ April 2005 J/  – suppression Nardi, Satz e.g. PLB 442 (1998) 14 deconfinement in clusters  J/  – suppression

Download ppt "System-size dependence of strangeness production, canonical strangeness suppression, and percolation Claudia Höhne, GSI Darmstadt."

Similar presentations

Mass, Quark-number, Energy Dependence of v 2 and v 4 in Relativistic Nucleus- Nucleus Collisions Yan Lu University of Science and Technology of China Many.

Mass, Quark-number, Energy Dependence of v 2 and v 4 in Relativistic Nucleus- Nucleus Collisions Yan Lu University of Science and Technology of China Many.
Elliptic flow of thermal photons in Au+Au collisions at 200GeV QNP2009 Beijing, Sep 21 - 26, 2009 F.M. Liu Central China Normal University, China T. Hirano.

Elliptic flow of thermal photons in Au+Au collisions at 200GeV QNP2009 Beijing, Sep , 2009 F.M. Liu Central China Normal University, China T. Hirano.
Equation of State in the framework of percolation C. Pajares. Univ. Santiago de Compostela In collaboration with J. Dias de Deus, B. Srivastava, A. Hirsch,

Equation of State in the framework of percolation C. Pajares. Univ. Santiago de Compostela In collaboration with J. Dias de Deus, B. Srivastava, A. Hirsch,
Physics Results of the NA49 exp. on Nucleus – Nucleus Collisions at SPS Energies P. Christakoglou, A. Petridis, M. Vassiliou Athens University HEP2006,

Physics Results of the NA49 exp. on Nucleus – Nucleus Collisions at SPS Energies P. Christakoglou, A. Petridis, M. Vassiliou Athens University HEP2006,
Heavy Quark Probes of QCD Matter at RHIC Huan Zhong Huang University of California at Los Angeles ICHEP-2004 Beijing, 2004.

Heavy Quark Probes of QCD Matter at RHIC Huan Zhong Huang University of California at Los Angeles ICHEP-2004 Beijing, 2004.
ICPAQGP, Kolkata, February 2-6, 2015 Itzhak Tserruya PHENIX highlights.

ICPAQGP, Kolkata, February 2-6, 2015 Itzhak Tserruya PHENIX highlights.
Multiplicity Distributions and Percolation of Strings J. Dias de Deus and C. Pajares CENTRA,Instituto Superior Tecnico,Lisboa IGFAE,Universidade de Santiago.

Multiplicity Distributions and Percolation of Strings J. Dias de Deus and C. Pajares CENTRA,Instituto Superior Tecnico,Lisboa IGFAE,Universidade de Santiago.
DNP03, Tucson, Oct 29, 2003 1 Kai Schweda Lawrence Berkeley National Laboratory for the STAR collaboration Hadron Yields, Hadrochemistry, and Hadronization.

DNP03, Tucson, Oct 29, Kai Schweda Lawrence Berkeley National Laboratory for the STAR collaboration Hadron Yields, Hadrochemistry, and Hadronization.
Statistical Model Predictions for p+p and Pb+Pb Collisions at LHC Ingrid Kraus Nikhef and TU Darmstadt.

Statistical Model Predictions for p+p and Pb+Pb Collisions at LHC Ingrid Kraus Nikhef and TU Darmstadt.
Terence Tarnowsky Long-Range Multiplicity Correlations in Au+Au at Terence J Tarnowsky Purdue University for the STAR Collaboration 22nd Winter Workshop.

Terence Tarnowsky Long-Range Multiplicity Correlations in Au+Au at Terence J Tarnowsky Purdue University for the STAR Collaboration 22nd Winter Workshop.
Charmonia production at the SPS energies Marie-Pierre COMETS IPN Orsay, FRANCE SQM2006, UCLA, Los Angeles, USA, March 26-31, 2006.

Charmonia production at the SPS energies Marie-Pierre COMETS IPN Orsay, FRANCE SQM2006, UCLA, Los Angeles, USA, March 26-31, 2006.
Experimental Results for Fluctuations And Correlations as a Signature of QCD Phase Transitions in Heavy Ion Collisions Gary Westfall Michigan State University,

Experimental Results for Fluctuations And Correlations as a Signature of QCD Phase Transitions in Heavy Ion Collisions Gary Westfall Michigan State University,
IN-MEDIUM FORMATION OF QUARKONIUM (“RECOMBINATION”) R. L. THEWS UNIVERSITY OF ARIZONA SQM2006 UCLA MARCH 26-31, 2006.

IN-MEDIUM FORMATION OF QUARKONIUM (“RECOMBINATION”) R. L. THEWS UNIVERSITY OF ARIZONA SQM2006 UCLA MARCH 26-31, 2006.
5-12 April 2008 Winter Workshop on Nuclear Dynamics STAR Particle production at RHIC Aneta Iordanova for the STAR collaboration.

5-12 April 2008 Winter Workshop on Nuclear Dynamics STAR Particle production at RHIC Aneta Iordanova for the STAR collaboration.
Percolation & The Phase Transition 1 Bring your own Phase Diagram TIFR, Mumbai, India Dec. 13-14, 2010 Brijesh K Srivastava Department of Physics West.

Percolation & The Phase Transition 1 Bring your own Phase Diagram TIFR, Mumbai, India Dec , 2010 Brijesh K Srivastava Department of Physics West.
Statistical Models A.) Chemical equilibration (Braun-Munzinger, Stachel, Redlich, Tounsi) B.) Thermal equilibration (Schnedermann, Heinz) C.) Hydrodynamics.

Statistical Models A.) Chemical equilibration (Braun-Munzinger, Stachel, Redlich, Tounsi) B.) Thermal equilibration (Schnedermann, Heinz) C.) Hydrodynamics.
1 A simple model to study the centrality dependence of observables from SPS to RHIC energies inspired by the first CuCu results to extract the physics.

1 A simple model to study the centrality dependence of observables from SPS to RHIC energies inspired by the first CuCu results to extract the physics.
Helen Caines Yale University SQM – L.A.– March 2006 Using strange hadron yields as probes of dense matter. Outline Can we use thermal models to describe.

Helen Caines Yale University SQM – L.A.– March 2006 Using strange hadron yields as probes of dense matter. Outline Can we use thermal models to describe.
1 Statistical Models and STAR’s Strange Data Sevil Salur Yale University for the STAR Collaboration.

1 Statistical Models and STAR’s Strange Data Sevil Salur Yale University for the STAR Collaboration.
8/6/2005Tomoaki Nakamura - Hiroshima Univ.1 Tomoaki Nakamura for the PHENIX collaboration Hiroshima University Measurement of event-by-event fluctuations.

8/6/2005Tomoaki Nakamura - Hiroshima Univ.1 Tomoaki Nakamura for the PHENIX collaboration Hiroshima University Measurement of event-by-event fluctuations.

Similar presentations

Ads by Google