Speaker
Description
Intra-beam stripping (IBSt) is a critical beam-loss mechanism in high-intensity H- linacs and presents a significant limitation to increasing beam power. This work presents a computational framework to evaluate IBSt-induced beam losses along the Spallation Neutron Source (SNS) linac for arbitrary bunch distributions. The calculation is based on evaluating the IBSt loss integral using a probability density function (PDF) trained on discrete-particle bunch distributions with normalizing flows. The input distribution is transformed to scaled normal-form coordinates, which improves both normalizing-flow training and Monte Carlo (MC) sampling. The method is benchmarked against simplified analytically solvable Gaussian bunches and then applied to canonical-angular-momentum-dominated (CAM-dominated) beam distributions, which contains strong inter-plane correlations. The results show that the normal-form-coordinate approach improves MC sampling stability and enables efficient IBSt loss calculations for correlated beam distributions.
| Paper status | Proceeding files received |
|---|