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Main Authors: Bosak, Stepan, Capek, Miloslav, Matas, Jiri
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2506.00595
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author Bosak, Stepan
Capek, Miloslav
Matas, Jiri
author_facet Bosak, Stepan
Capek, Miloslav
Matas, Jiri
contents This paper presents a novel bi-level topology optimization strategy within the method-of-moments paradigm. The proposed approach utilizes an auxiliary variables called edge resistivities related to the Rao-Wilton-Glisson method-of-moments basis functions, for a definition of a fast local optimization algorithm. The local algorithm combines automatic differentiation with adaptive gradient descent. A Bayesian optimization scheme is applied on top of the local algorithm to search for an optimum position of the delta-gap feeding and optimizer hyperparameters. The strength of the algorithm is demonstrated on Q-factor minimization for electrically small antennas. Auxiliary edge resistivity topology optimization outperforms current state-of-the-art topology optimization methods, including material density-based approaches and memetic schemes, in terms of convergence. However, due to the nature of gradient descent, careful tuning of the optimizer hyperparameters is required. Furthermore, the proposed method solves the known binarization issue. Two designs that achieved self-resonance and approached the Q-factor lower bound were further assessed in CST Microwave Studio.
format Preprint
id arxiv_https___arxiv_org_abs_2506_00595
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Antenna Q-Factor Topology Optimization with Auxiliary Edge Resistivities
Bosak, Stepan
Capek, Miloslav
Matas, Jiri
Computational Physics
This paper presents a novel bi-level topology optimization strategy within the method-of-moments paradigm. The proposed approach utilizes an auxiliary variables called edge resistivities related to the Rao-Wilton-Glisson method-of-moments basis functions, for a definition of a fast local optimization algorithm. The local algorithm combines automatic differentiation with adaptive gradient descent. A Bayesian optimization scheme is applied on top of the local algorithm to search for an optimum position of the delta-gap feeding and optimizer hyperparameters. The strength of the algorithm is demonstrated on Q-factor minimization for electrically small antennas. Auxiliary edge resistivity topology optimization outperforms current state-of-the-art topology optimization methods, including material density-based approaches and memetic schemes, in terms of convergence. However, due to the nature of gradient descent, careful tuning of the optimizer hyperparameters is required. Furthermore, the proposed method solves the known binarization issue. Two designs that achieved self-resonance and approached the Q-factor lower bound were further assessed in CST Microwave Studio.
title Antenna Q-Factor Topology Optimization with Auxiliary Edge Resistivities
topic Computational Physics
url https://arxiv.org/abs/2506.00595