PROGRESS IN 3D SPACE-CHARGE CALCULATIONS IN THE GPT CODE

The mesh-based 3D space-charge routine in the GPT (General Particle Tracer, Pulsar Physics) code scales lin-early with the number of particles in terms of CPU time and allows a million particles to be tracked on a normal PC. The crucial ingredient of the routine is a non-equidistant multigrid Poisson solver to calculate the electrostatic po-tential in the rest frame of the bunch. The solver has been optimized for very high and very low aspect ratio bunches present in state-of-the-art high-brightness electron acceler-ators. In this paper, we introduce a new meshing strategy based on a wavelet decomposition of the space-charge den-sity. The numerical results show that the number of par-ticles with large numerical error, typically located at the edges of the bunch, can be reduced with this new approach enormously