Preliminary results coupling "Stochastic Mean Field" and "Boltzmann-Langevin One Body" models with Geant4

C Mancini-Terracciano, M Asai, B Caccia, G A P Cirrone, A Dotti, R Faccini, P Napolitani, L Pandola, D H Wright, M Colonna

Research output: Contribution to journalArticlepeer-review

Abstract

PURPOSE: Monte Carlo (MC) simulations are widely used for medical applications and nuclear reaction models are fundamental for the simulation of the particle interactions with patients in ion therapy. Therefore, it is of utmost importance to have reliable models in MC simulations for such interactions. Geant4 is one of the most used toolkits for MC simulation. However, its models showed severe limitations in reproducing the yields measured in the interaction of ion beams below 100 MeV/u with thin targets. For this reason, we interfaced two models, SMF ("Stochastic Mean Field") and BLOB ("Boltzmann-Langevin One Body"), dedicated to simulate such reactions, with Geant4.

METHODS: Both SMF and BLOB are semi-classical, one-body approaches to solve the Boltzmann-Langevin equation. They include an identical treatment of the mean-field propagation, on the basis of the same effective interaction, but they differ in the way fluctuations are included. Furthermore, we tested a correction to the excitation energy calculated for the light fragments emerging from the simulations and a simple coalescence model.

RESULTS: While both SMF and BLOB have been developed to simulate heavy ion interactions, they show very good results in reproducing the experimental yields of light fragments, up to alpha particles, obtained in the interaction of 12C with a thin carbon target at 62 MeV/u.

CONCLUSIONS: BLOB in particular gives promising results and this stresses the importance of integrating it into the Geant4 toolkit.

Original languageEnglish
Pages (from-to)116-122
Number of pages7
JournalPhysica Medica
Volume67
DOIs
Publication statusPublished - Nov 2019

Keywords

  • Monte Carlo Method
  • Radiotherapy
  • Radiation protection
  • radiation dose distribution

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