Abstract
Calculating the field pattern arising from an array of radiating sources is a central problem in Computational ElectroMagnetics (CEM) and a critical operation for designing and developing antenna systems. Yet, it is a computationally expensive operation when using traditional numerical approaches, including finite-difference in the time and spectral domains. To address this issue, we develop a new data-driven surrogate model for fast and accurate calculation of the field radiation pattern. The method is based on the Fourier Neural Operator (FNO) technique. We show that we achieve a performance improvement of 31x when compared to the performance of the Meep CEM solver when running on a desktop laptop CPU at the cost of a small accuracy loss.
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Pornthisan, N., Markidis, S. (2023). Fast Electromagnetic Field Pattern Calculation with Fourier Neural Operators. In: Mikyška, J., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M. (eds) Computational Science – ICCS 2023. ICCS 2023. Lecture Notes in Computer Science, vol 14074. Springer, Cham. https://doi.org/10.1007/978-3-031-36021-3_24
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DOI: https://doi.org/10.1007/978-3-031-36021-3_24
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