Speaker
Description
In high-intensity storage rings, long-range transverse
resistive-wall (RW) wakefield is a dominant source of
coupled-bunch instability. Conventional particle tracking
algorithms handling this wakefield require storing bunch-
by-bunch and turn-by-turn centroid position histories, re-
sulting in excessive memory consumption, which leads to
computational inefficiency. This study proposes fitting the
long-range transverse RW wakefield through a sum of expo-
nentials. This method eliminates the need for bunch centroid
histories during tracking computations while facilitating
GPU-based parallel implementation, thereby significantly
enhancing computational efficiency. This work demonstrates
the dependence of the fitting performance on the number of
exponential functions and the fitting interval.
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