Alpha clustering from relativistic collisions

Transcription

1 Alpha clustering from relativistic collisions Wojciech Broniowski UJK Kielce & IFJ PAN Cracow STAR Regional Meeting: Heavy Quark Production, Jets and Correlations 1-4 January 14, WUT [based on WB& E. Ruiz Arriola, arxiv:11.89] WB (UJK & IFJ PAN) α clusters STAR 14 1 / 19

2 Instead of outline (WPCF 1 α) Two phenomena are related: α clustering in light nuclei harmonic flow in ultra-relativistic A+B collisions low-energy structure highest energy mini bangs (!) WB (UJK & IFJ PAN) α clusters STAR 14 / 19

3 History David Brink: After Gamow s theory of α-decay it was natural to investigate a model in which nuclei are composed of α-particles. Gamow developed a rather detailed theory of properties in his book Constitution of Nuclei published in 191 before the discovery of the neutron in 19. He supposed that 4n-nuclei like 8 Be, 1 C, 16 O... were composed of α-particles Generated by CamScanner from intsig.com Generated by CamScanner from intsig.com WB (UJK & IFJ PAN) α clusters STAR 14 / 19

4 Present status ground Hoyle + other excited 9 Be 1 C [M. Freer, WPCF1, H. Fynbo+Freer, Physics 4 (11) 94] ab initio calculations up to 16 O strong α clusterization WB (UJK & IFJ PAN) α clusters STAR 14 4 / 19

5 From α clusters to flow in relativistic collisions α clusters asymmetry of shape asymmetry of initial fireball hydro or transport collective harmonic flow Generated by CamScanner from intsig.com What are the chances of detection? Related idea: triton/ He Au at RHIC in 15 [Sickles (PHENIX) 1] The case of light nuclei is more promising, as it leads to abundant fireballs WB (UJK & IFJ PAN) α clusters STAR 14 5 / 19

6 1 C- 8 Pb single event 4 y [fm] x [fm] Imprints of the α clusters clearly visible WB (UJK & IFJ PAN) α clusters STAR 14 6 / 19

7 1 C- 8 Pb intrinsic average over events Intrinsic distributions: α s in a triangular arrangement 4 y [fm] x [fm] y [fm] x [fm] clustered unclustered WB (UJK & IFJ PAN) α clusters STAR 14 7 / 19

8 Constraints from EM form factor Ρ r fm q F em r fm q fm 1 Electric charge density (thin lines) and the corresponding distribution of the centers of nucleons (thick lines) in 1 C for the data and BEC calculations (dashed lines), and for the FMD calculations (solid lines), plotted against the radius. Central depletion WB (UJK & IFJ PAN) α clusters STAR 14 8 / 19

9 ] Distribution of pairs Radial density in the relative NN distance r ) [fm (r ρ r r 1 [fm] Our Monte Carlo The α cluster structure is modeled sufficiently accurately [Buendia et al. 4] WB (UJK & IFJ PAN) α clusters STAR 14 9 / 19

10 1 C 8 Pb collision Mixed Glauber model at SPS conditions: n 1 a N w + an bin, a =.1 Intrinsic distributions in the transverse plane in the fireball, N w > 7 large multiplicity 4 y [fm] x [fm] y [fm] x [fm] clustered unclustered WB (UJK & IFJ PAN) α clusters STAR 14 1 / 19

11 Eccentricity parameters Eccentricity parameters ɛ n e inφn = j ρn j einφ j j ρn j describe the shape (j labels the sources in the event, n=rank) Two components: intrinsic (from existent mean deformation of the fireball) from fluctuations WB (UJK & IFJ PAN) α clusters STAR / 19

12 Digression: d-pb Initial entropy density in a d-pb collision with N part = 4 [Bozek 1] y fm x fm Fluctuations around the intrinsic ellipticity WB (UJK & IFJ PAN) α clusters STAR 14 1 / 19

13 Geometry vs multiplicity in 1 C-Pb The triangle plane parallel or perpendicular to the transverse plane: higher multiplicity higher triangularity lower ellipticity Generated by CamScanner from intsig.com lower multiplicity lower triangularity higher ellipticity WB (UJK & IFJ PAN) α clusters STAR 14 1 / 19

14 Ellipticity and triangularity vs multiplicity σ( )/< > σ( ))/< > < > < >.5.5 N w N w clustered unclustered Clusters: When N w then ɛ and ɛ and σ(ɛ )/ɛ, σ(ɛ )/ɛ tending to 4/π 1.5 No clusters: similar behavior for n = and n = WB (UJK & IFJ PAN) α clusters STAR / 19

15 Shape-flow transmutation The eccentricity parameters are transformed (in all models based on collective dynamics) into asymmetry of the transverse-momentum flow. It has been found that v n A ɛ n WB (UJK & IFJ PAN) α clusters STAR / 19

16 E-by-e fluctuations σ(v n ) v n σ(ɛ n) ɛ n Measured flow coefficients reflect the initial shape eccentricities WB (UJK & IFJ PAN) α clusters STAR / 19

17 Triangularity vs ellipticity clustered unclustered Clusters: Anticorrelation: ρ(ɛ, ɛ ). WB (UJK & IFJ PAN) α clusters STAR / 19

18 Dependence on the collision energy σ( ))/< > < > < >.5 inel σ NN =mb, a=.145 N w inel =4mb, a=.145 σ NN σ( ))/< > < > < >.5 N w inel =7mb, a=.1 σ NN σ( ))/< > < > < >. N w mb (SPS) 4mb (RHIC) 7mb (LHC) Qualitative conclusions remain from SPS to the LHC WB (UJK & IFJ PAN) α clusters STAR / 19

19 Conclusions Signatures of clustered 1 C- 8 Pb collisions Increase of ɛ and v with multiplicity for the highest multiplicity events Decrease of scaled variance ɛ and v with multiplicity for the highest multiplicity events Anticorrelation of ɛ and ɛ, or v and v Extensions: Other systems More detailed modeling Possible future data (NA61?) in conjunction with a detailed knowledge of the dynamics of the evolution of the fireball would allow to place constrains on the α-cluster structure of the colliding nuclei. Conversely, the knowledge of the clustered nuclear distributions may help to verify the fireball evolution models WB (UJK & IFJ PAN) α clusters STAR / 19