Detecting resonance of radio-frequency cavities using fast direct integral equation solvers and augmented Bayesian optimization

This paper presents a computationally efficient framework for identifying resonance modes of 3D radio-frequency (RF) cavities with damping waveguide ports. The proposed framework relies on surface integral equation (IE) formulations to convert the task of resonance detection to the task of finding resonance frequencies at which the lowest few eigenvalues of the system matrix is close to zero. For the linear eigenvalue problem \rev{with a fixed frequency}, we propose leveraging fast direct solvers to efficiently invert the system matrix; for the frequency search problem, we develop a hybrid optimization algorithm that combines Bayesian optimization with down-hill simplex optimization. The proposed IE-based resonance detection framework (IERD) has been applied to detection of high-order resonance modes (HOMs) of realistic accelerator RF cavities to demonstrate its efficiency and accuracy.