Search for Centauro Events at RHIC-PHENIX

1. Search for Centauro Events at RHIC-PHENIX Contents • History of Centauro Search • Search Strategy • Observable and Analysis Method • Analysis Results • Summary and Future Plan Kensuke Homma / Tomoaki Nakamura for the PHENIX Collaboration Hiroshima University

2. Centauro / Anti Centauro Event Anti Centauro Cosmic ray experiments • Brazil-Japan collaboration in Bolivia Y.Fujimoto and S.Hasegawa, Phys. Rep. 65, 151 (1980) • JACEE J.J.Lord and Iwai, Paper No. 515, International Conference on High Energy Physics, Dallas (1992) This is an anomalous domain based on isospin symmetry. O : Photon, + : Charged Particle

3. List of Centauro Searches

4. PHENIX Experiment at Run2 Using Magnetic Field-off data Gamma-like Cluster (Electro-Magnetic Calorimeter) Charged Track(BBC Z-Vertex, Drift Chamber and Pad Chamber1) |η| < 0.35 ⊿φ < π/2 in each arm

5. Disoriented Chiral Condensate V V π π σ σ restoration Quench Mechanism K.Rajagopal and F.Wilczek : Nucl. Phys. B379, 395 (1993) quench QCD vacuum DCC Linear sigma model Chiral transformation Chiral symmetry breaking term due to finite masses

6. Search Strategy No DCC (binomial) probability : P(f) DCC (Centauro type) fraction : f If every event could contain largely deviated domains on isospin symmetry and most of domains per event could be detected within a limited detector acceptance, we would be able to discuss anomaly based on the probability distribution by the statistical treatment like: However, we do not know domain information on the numbers and sizes a priory, and our detector acceptance is very limited. Therefore we need to search for rare events containing anomalous domain like cosmic ray experiments rather than the simple statistical treatment.

7. We search for a most largely deviated domain per event by looking at differences between number of charged and gamma clusters by changing regions of interest as we do by eyes, because we don’t know what the size is and where the position is. For example, we want to pick up this domain. We must do this search in several million events.

8. Observables Define an asymmetry between number of charged tracks and neutral clusters in event-by-event base as a function of subdivided h-f phase spaces normalized by one standard deviation for a given multiplicity class. Domain Size Domain size and domain position of largely deviated regions can be obtained at the same time by using Multi Resolution Analysis (MRA) technique. δAI3 Deviation Size Domain Position η,φ

9. Multi Resolution Analysis (MRA) Levelj-1: 2j-1bins Levelj : 2jbins φ(x) 0.7 Scaling function x 1 φ(2x) 1 φ(2x-1) (＋) -0.7 ＝ 1 x 1 x ψ(x) (－) -1 0.7 -1 Wavelet function x -0.7 φ(2x)= 1/√2 {φ(x)+ψ(x)} φ(2x-1)= 1/√2 {φ(x)- ψ(x)} Total number of bins is 2j Level j represents a resolution level

10. Signal Decomposition Look for a maximum Djk per event Signal j=4 22 20 φ ψ Cjk Djk j=3 + j=2 + j=1 + j=0 + k k j : resolution level k : k-th bin Cjk : coefficients of φ Djk : coefficients of ψ 24/2j→ Domain Size k → Domain Position Cjk → Deviation Size Djk → used to pick up k

11. Quiz Pink dots are distributed around 0 based on Gaussian (mean=0, s=1.0) over 28 bins. A single domain is hidden with Gaussian (mean=Ns, s=1.0) • Where is an anomalous domain? • What is the domain size?

12. Answers Ns=3 j=5 Ns=2 j=4 Ns=1 j=3 Ns=0.5 j=2

13. Example of 2-D MRA by Djkmax Domain C: AI3= ~20 x 8bins (h, f)=(3, 7) (jh , jf)=(3, 2) A B C phi(j=4) eta (j=4) Result:Correct (h,f)=(3,7) (jh,jf)=(3,2) Result:Wrong (h,f)=(7,1) (jh,jf)=(2,4) 1) projection on eta 1) projection on phi Select a domain with larger Djkmax in the second projection 2) projection on phi 2) projection on eta

14. Data Analysis (East Arm) Number of Selected Charged Track [uncorrected] Number of Selected Photon-like Clusters [uncorrected] • Magnetic Field-off • Minimum bias 818,507 events number of charged tracks > 0 number of photon-like clusters >0 • Charged Track BBC Z-Vertex, Drift Chamber and Pad Chamber1 associated straight-line track • Photon-like Cluster Cluster of Electro-Magnetic Calorimeter 1) Photon cluster shower shape 2) Time of flight of photon 3) Not associated with charged track 4) dead and hot channels are rejected

15. Baseline fluctuations Map for charged tracks f h • Binomial sample • Produce hit maps (28 x 28 bins in h-f) per short run segment for g clusters and charged tracks respectively from real data to reproduce inefficient area of the detector as realistic as possible. • Randomly distribute g clusters and charged tracks to all h-f space, but if there is no entry in the hit map, discard the cluster or track until # of accepted clusters and tracks coincide with those observed in a given real event. Map for g clusters f h

16. Example of binomial distribution W/O hit map With hit map (Nch, Ng)=(200,100) • DC component of Nch-Ng per event is subtracted in advance before the 2D MRA. This gives almost symmetric shape in the maximum deviation distribution, even if the slope in the correlation plot is different from one, unless a given hit map biases partial phase space.

17. Maximum Deviation Size • PHENIX magnetic field-off data Au+Au 200 GeV 818,507 events East Arm [uncorrected] • Binomial sample with hit map 100 times larger statistics using same multiplicity-set Maximum Deviation Size (A.U.)

18. Level-by-Level Deviation Size [East Arm, uncorrected] ⊿φ :2.813°5.625°11.25° 22.50° 45.00° -- Data --Binomial ⊿η: 0.044 0.088 0.175 0.350 -1.0 -0.5 0 0.5 1.0 -1.0 -0.5 0 0.5 1.0 -1.0 -0.5 0 0.5 1.0 -1.0 -0.5 0 0.5 1.0 -1.0 -0.5 0 0.5 1.0

19. Positive Deviation(Centauro Type) ⊿η=0.175 azimuthal angle :φ[rad] azimuthal angle :φ[rad] ⊿φ=22.5 pseudo rapidity :η pseudo rapidity :η ＋ : charged track = 46 ○ : photon-like cluster = 0

20. Summary and Future Plan • We have demonstrated two dimensional multi-resolution analysis on the asymmetry between the number of the charged tracks and γ-like clusters in the η-φ phase space. • Detector biases will be more rigorously studied. • We will set a reasonably tight significance level to define the degree of anomaly based on realistic physical models with normal fluctuations. • We will measure signal to background ratios above the significance level . • We will discuss characters of those events such as centrality dependence and azimuthal correlation with respect to reaction plane.

21. Back up slides

22. Centrality Determination peripheral central ZDC Total Energy BBC Charge Sum Central Arm participant to ZDC b to BBC Central Arm spectator • Event characterization in terms of impact parameter (b) in Au+Au collisions. • Large : peripheral collision • Small : central collision • Coincidence between BBC and ZDC. • Determine collision centrality. • 92 % of inelastic cross section can be seen. • Extract variables using Glauber Model • Number of participants (N_part). • Number of nucleons participate in a collision. • Represents centrality. • Related with soft physics. • Number of binary collisions (N_binary). • Number of Nucleon-Nucleon collisions. • Related with hard physics. • Incoherent sum of N-N collisions becomes a baseline for A-A collisions.

23. Normalization per centrality bin Correlation between Nch vs. Ng Normalization factor per centrality [uncorrected] Centrality <Nt>+<Ng> Factor 10 0-10% 221.5 0.067 9 10-20% 158.3 0.079 8 20-30% 109.2 0.096 7 30-40% 72.36 0.118 6 40-50% 44.92 0.149 5 50-60% 25.88 0.196 4 60-70% 13.87 0.269 3 70-80% 7.744 0.360 2 80-90% 5.319 0.434 1 90-94% 4.223 0.487 Number of Photon-like Clusters Number of Charged Tracks

24. Top 10% 100843 events 50-60% 98685 60-70% 92970 10-20% 101585 20-30% 98416 70-80% 68048 30-40% 98673 80-90% 42529 40-50% 98898 90-94% 5589 -- Data --Binomial Centrality-by-Centrality Maximum Deviation Size -1.0 -0.5 0 0.5 1.0 -1.0 -0.5 0 0.5 1.0