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Persistent URL http://purl.org/net/epubs/work/38005644
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Record Id 38005644
Title GPT-CSR: a New Simulation Code for CSR Effects
Abstract For future applications of high-brightness electron beams, including the design of next generation FEL's, correct simulation of Coherent Synchrotron Radiation (CSR) is essential as it potentially degrades beam quality to unacceptable levels. However, the long interaction lengths compared to the bunch length, numerical cancellation, and difficult 3D retardation conditions make accurate simulation of CSR effects notoriously difficult. To ease the computational burden, CSR codes often make severe simplifications such as an ultra-relativistic bunch travelling on a prescribed reference trajectory. Here we report on a new CSR model implemented in the General Particle Tracer (GPT) code that avoids most of the usual assumptions: It directly evaluates the LiƩnard'Wiechert potentials based on the stored history of the beam. It makes no assumptions about reference trajectories, and also takes into account the transverse size of the beam. Example results demonstrating normalised emittance growth in the first bunch compressor of FERMI@Elettra are presented.
Organisation ASTeC , ASTeC-AP , STFC
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Language English (EN)
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Paper In Conference Proceedings In 9th International Particle Accelerator Conference (IPAC 18), Vancouver, Canada, 29 Apr 2018 - 4 May 2018, (2018). thpak078.pdf 2018
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