Random Forest and Extra Trees trained on PIC data predict planar multipactor susceptibility maps about as well as a Monte Carlo benchmark, while neural networks generalize more poorly to unseen materials.
Demonstration of Niobium Tin in 218 MHz Low-beta Quarter Wave Accelerator Cavity
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abstract
A 218 MHz quarter wave niobium cavity has been fabricated for the purpose of demonstrating Nb3Sn technology on a low-beta accelerator cavity. Niobiumtin has been established as a promising next generation SRF material, but development has focused primarily in high-beta elliptical cell cavities. This material has a significantly higher TC than niobium, allowing for design of higher frequency quarter wave cavities (that are subsequently smaller) as well as for significantly lowered cooling requirements (possibly leading to cryocooler based designs). The fabrication, initial cold testing, and Nb3Sn coating are discussed as well as test plans and details of future applications.
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2025 1verdicts
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A Supervised Machine Learning Framework for Multipactor Breakdown Prediction in High-Power Radio Frequency Devices and Accelerator Components: A Case Study in Planar Geometry
Random Forest and Extra Trees trained on PIC data predict planar multipactor susceptibility maps about as well as a Monte Carlo benchmark, while neural networks generalize more poorly to unseen materials.