A multiple objective evolutionary algorithm approach to find optimal design parameters for beam position monitoring systems

Abstract

Diagnostic systems are key components for all accelerators, and Beam Position Monitor (BPM) systems are one of the primary functional units. Such systems allow us to observe the beam characteristics and hence interpret and adjust the beam parameters to achieve the required parameter range. This study aims to specify BPM parameters like antenna radius, capacitance, signal-to-noise ratio (SNR), etc. for Turkish Accelerator and Radiation Laboratory in Ankara (TARLA). Searching optimal values for such parameters is conventionally performed using methods including Finite Element Methods (FEM) or analytical approximation. Here, Multiple Objective Evolutionary Algorithms (MOEA) were employed as an alternative. We aimed to obtain a wide range of available results for possible production constraints. Considering TARLA beam parameters, button-type BPMs can be employed as diagnostic tools due to their low cost and simple mechanical structure. SNR levels of 20–40[Formula: see text]dB were achieved using antennas with radius parameters of 3–10[Formula: see text]mm. It is known that these SNR levels are in the acceptable range for the read-out electronic system.