Crossguide Coupler Design using Deep-Learning model

Abstract

Crossguide couplers are essential components in high power applications, where a sample is collected from the forward and reverse path to ensure operation. The design of the coupling section was intensively investigated but no accurate model exists. Accordingly, most of the literature models are used as starting points followed by lengthy numerical optimization. Here, we introduced a deep learningbased design for the first time. The proposed design is used to generate several design, where the recorded coupling value error is below 2 % for the validation cases. The generated designs satisfied a coupling flatness within ±1.5dB and the directivity beyond 15 dB.