Using GEMINI to study multiplicity distributions of Light Particles

1. Using GEMINI to study multiplicity distributions of Light Particles Adil Bahalim Davidson College Summer REU 2005 – TAMU Cyclotron Institute

2. Overview • What is the JBN group doing? • Background for my project • Procedures / Programs used • Results • Summary

3. Current Events in JBN Group • Superheavy Elements – BigSol • Quark-Gluon Plasma – BRAHMS Collaboration • Nuclear EOS / Reaction Dynamics of Heavy Ion Collisions – NIMROD

4. Heavy Ion Collisions • Primary Fragments – Thermal / Chemical Equilibrium (Freezeout) • Secondary Fragments & LP’s – Reconstruction Models

5. NIMROD • Used to gather data such as: • Multiplicity distributions • Charge/Mass distributions • Energy spectra • Angular distributions • 4π Detector Array • Neutrons detected by liquid scintillators around target • Charged particles detected by modules consisting of a gas ionization chamber, one or two Si detectors and one or two CsI detectors.

6. Recent Experiments • Time-frame of the reaction and technological limitations make it difficult to gather important information about the properties of the nuclear matter (e.g. stiffness of EOS) • Most recent experiment devised in which neutrons and charged particles measured in coincidence with intermediate mass fragments (IMF’s) originating from primary fragments • 64Zn and 64Ni beams incident on: • 58Ni, 64Ni, 112Sn, 124Sn, 197Au, 232Th targets • IMF’s detected by Si-CsI telescope • Neutrons detected by detectors borrowed from DEMON Array • LCP’s detected by CsI crystals

7. Reconstruction • Main hurdle is secondary decay (IMF’s) which makes it difficult to reconstruct primary fragments • Antisymmetrized Molecular Dynamics (AMD) calculations used have shown to be good models for reconstruction • Mean multiplicities (obtained from experiment) and distributions widths (difficult to obtain) of LP’s are used as input parameters in GEMINI • GEMINI is a statistical modeling code that uses the Monte-Carlo method to simulate sequential binary decays of nuclei

8. AMD Model Reconstruction

9. Procedure • Simulated 1000 decay events for each nucleus from Z=3 to Z=40 with at least one from each: • Stability line (i.e. ~ Z = N) • Proton-rich side (~ Z > N) • Neutron-rich side (N > Z) • Excitation energies ranged from 2 to 5 MeV/amu in .5 MeV/amu increments • Assumed constant inverse level density parameter (8)

10. ROOT • Relation between mean multiplicities and the distribution widths of light particles emitted from system • Width = 1σ = • Used the program ROOT to create histograms and calculate the distribution widths and the average multiplicities of each particle

12. Results • Found correlation between the mean multiplicities and distribution widths • The best fit at specific Excitation Energies was a power fit (i.e. y=AxB)

17. Power-Function Parameters A & B (y=AxB)

18. Conclusion • As expected, we found the relation between the mean multiplicities and distribution widths of the LP’s • These relations can be used as references to determine the distribution widths from the experimental data on mean multiplicities and implement them as input parameters for the reconstruction models

19. Acknowledgements JBN Group REU 2005 Staff

20. Special Thanks Dr. Seweryn Kowalski, Adil Bahalim, Dr. Joe Natowitz