WCI 2004: 3- SORTING Catania January 2004 WCI 2004 session 3: DATA SORTING Can we extract mechanism? Can we extract sources in space-time? What are the differences between p-A and A-A collisions?

WCI 2004: 3- SORTING Catania January 2004 SORTING : Why? Two complementary philosophies 1- Global overview of data versus collision violence, energy, global comparison with models : IPS = geometry (e.g. M tot,E T,E T12,Z TOT,TKEL…)  IPS do not allow to select mechanisms.  IPS = impact parameter mixing around Fermi energy SORTING IS DETECTOR DEPENDENT 2 – Select a given mechanism, an emission source : Use several global variables, statistical techniques.  « Physics of the sorting » ? Check what you select  Mechanism  impact parameter (large fluctuations E  100 AMeV) OR

WCI 2004: 3- SORTING Catania January 2004 Impact parameter selector and detector response Llope et al. PRC 51(1995) 1325 INDRA Correlations between N IMF and IPS is Detector dependent A powerful detector gives closer variances and normalised variances of IMF distributions whatever the IPS (but also lower mean values for IPS based on lcp ) Central collisions : upper 10% of IPS distributions  N c  E T  Z MR  Z det  N H  Z LCP

WCI 2004: 3- SORTING Catania January 2004 IPS : event mixing DYWAN simulation (wavelets) Jouault et al. NPA 628(1998) 119 De la Mota &Sébille EPJA 12 (2001) 479 Experimental data Doré et al. (INDRA) PLB491(2000) 15 IPS = transverse energy Verify IPS range data/model Treat both in same way

WCI 2004: 3- SORTING Catania January 2004 IPS : Disentangle QP and MR emissions Get proportions and properties of both types of emissions (sources ?), which may differently depend on b See Olmi Most peripheral collisions b  0.6 b max. IPS=TKEL Results depend on assumption for QP emission (isotropic or not)

WCI 2004: 3- SORTING Catania January 2004 Coulomb proximity decay: evaporation from PLF Simulation :  inv in  j for emitting j from PLF parameterised as  j (E) =  R 2 fj (1-U c /E) Modified Uc=Z f Z j /R fj + Z TLF Z j /R TLFj + Z TLF Z f /R TLFf - Z TLF Z/R TLFPLF Lower B  emission favoured between PLF and TLF in early emission : R TLFPLF =30-70 fm (t  250 fm/c)  Data 50 AMeV Cd+Mo:  from PLF (E  22 MeV) Including early emission increases A PLF and  * from 2.3 to 4 MeV. Influence on mid-rapidity « source ». Hudan et al. Nucl-ex/

WCI 2004: 3- SORTING Catania January 2004 Data sorting: Identify mechanisms use complete events (QP or single source)  see M. Bruno, Srivastava, INDRA Peripheral collisions select events with minimum MR emission : velocity, momentum criteria (Bruno, Bougault) Charge density (INDRA) Remove preequilibrium Au+C (Srivastava) Central collisions:  Complete events and event shape (flow) (Bruno, INDRA)  Multidimensional analyses (INDRA)

WCI 2004: 3- SORTING Catania January 2004 Data sorting: from pure binary events to single source Tool: charge density vs c.m. velocity along event axis 36 Ar+ 58 Ni 95 AMeV Complete events: 80% of total charge and linear momentum detected (semi-central and central collisions) mb (5.2%  R ) E. Galichet PhD thesis, and NIM A 441 (2000) 517 Parallel velocity 2.5mb 0.7 mb

WCI 2004: 3- SORTING Catania January 2004 Data sorting: selection of central events Au+C, Au + Cu, Au + Au Nucl. Phys. A 724 (2003) 455 ISOTROPY Well detected >90% A p+T and spherical events θ flow > 60 o Some percent of the measured cross section

WCI 2004: 3- SORTING Catania January 2004 Selection of compact single source: complete events and flow angle Flow angle Calculated with Fragments only (Z  5) INDRA J.D. Frankland et al. NPA 689 (2001) lcp properties show evolution from binary to fusion collisions 

WCI 2004: 3- SORTING Catania January 2004 Sorting :Statistical techniques  Work in multidimensional space  Project on a discriminant plane, or axis Principal Component Analysis Chimera variable Discriminant Analysis Neuronal Network Enlarge the samples Their properties must be carefully verified INDRA central collisions See N. Le Neindre

WCI 2004: 3- SORTING Catania January 2004 Data sorting is equivalent to creating a statistical ensemble Characterize The pertinent variables The type of statistical ensemble See Francesca Gulminelli

WCI 2004: 3- SORTING Catania January 2004 Space-time extent of sources Interferometry New technique to partly avoid space and time mixing Imaging (B. Lynch) Velocity correlations (lcp-IMF, IMF-IMF) (Geraci, De Souza, Natowitz) Can we disentangle space and time ?

WCI 2004: 3- SORTING Catania January 2004 Bill Lynch

WCI 2004: 3- SORTING Catania January 2004 p -A versus A-A Similarities and differences between reactions Ar+Au & Kr+Au Nautilus F-F emission time vs E * ( Beaulieu PRL84(2000)5971) Similar above 4-5 AMeV : Multifragmentation region

WCI 2004: 3- SORTING Catania January 2004 single source – no neck emission simplest case for thermal effects negligible deformation, angular momentum effects formation of hot residue in a dilute state no compression entropy per nucleon reaches maximum very rapidly residues formed over full range of E * with one beam limited maximum E * /A due to transparency effects In p-A reactions V. Viola See Karnaukhov

WCI 2004: 3- SORTING Catania January 2004 MF: more or less compression in central HI collisions Depends on entrance channel asymmetry 2 systems, 1  th (same partitions) Different KE of fragments 1 asymmetric system, 2  th. Same KE of fragments Bellaize et al. (INDRA) NPA709 (2002) 367

WCI 2004: 3- SORTING Catania January 2004 p-A and A-A at high excitation Z s =75  th  6.5 MeV  M IMF  /Z S  Z s =68  th  6.2 MeV  M IMF  /Z S  0.10  th and Z S from SMM (backtr) Z s =59  th  6.5MeV  M IMF  /Z S  =0.065 Bellaize et al. (INDRA) O. Lopez (INDRA) Beaulieu et al (ISiS) PRC64 (2001) KE : Coulomb In p-A vs central A-A for  th  6. MeV : less fragments, and similar fragment KE. Uncertainties on  th ? On Z S ? Detector efficiencies on M IMF