Adil Bahalim Davidson College Dr. Joseph Natowitz (Advisor), Dr. Seweryn Kowalski (Mentor) Summer REU 2005 – TAMU Cyclotron Institute Reconstruction Main hurdle is secondary decay (intermediate mass fragments) 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 Heavy Ion Collisions Background AMD Model Reconstruction Figure 1. Immediately after the collision, the system undergoes a multifragmentation process. Primary fragments emerge from the projectile and target nuclei. These fragments separate and de-excite during secondary emission, decaying to secondary fragments while giving off light charged particles and neutrons. Figure 2. In this previous study, AMD Model calculations were used to reconstruct simulated decays of several IMF’s. The filled stars represent the original parent nuclei. The open stars show the reconstructed parent nuclei. There is a good fit between the two, making this a reasonable model for reconstruction. 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) Procedure Distribution Widths vs. Mean MultiplicitiesSimulation Data Figure 3. A typical sample of data gathered by GEMINI of each of the light particles emitted during decay. These data were collected for the decay of the 95 Zr. Figure 4. Global plots of all series from Z=3 to Z=40 with excitation energies from 2.5 MeV/amu to 5 MeV/amu for each of the light particles emitted. Though on different scales, all plots show a positive trend as the mean multiplicities of the particles increase. 4 He has a greater spread than the rest of the particles. A possible cause is the limitation of the computer code. GEMINI Simulations Conclusion As expected, we found the relation between the mean multiplicities and distribution widths of the LCP’s and neutrons 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 Results Best Fit Function at Exc. Energy = 3 MeV/amu Figure 5. Width vs. Mean Multiplicity plots for each light particle for all nuclei simulations at an excitation energy of 3 MeV/amu. Power functions had the best fits to these plots. All fits, excluding 4 He, have a correlation coefficient, R 2, of greater than.90. Neutron Power-Function Parameters A & B (y=Ax B ) Figure 6. The graph on the right shows the values of the power-function fit parameter A at each of the excitation energies. The graph on the left shows the values for B. There is an almost linear trend for each parameter. Using GEMINI to study multiplicity distributions of light charged particles and neutrons