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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 equire storing bunch-by-bunch and turn-by-turn centroid position histories, resulting in excessive memory consumption, which leads to computational inefficiency. This study proposes fitting the long-range transverse RW wakefield through a sum of exponentials. 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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