Publication: The design of potter horns for THz applications using a genetic algorithm
Issued Date
2007-12-01
Resource Type
ISSN
15729559
01959271
01959271
Other identifier(s)
2-s2.0-36049018648
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Mahidol University
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SCOPUS
Bibliographic Citation
International Journal of Infrared and Millimeter Waves. Vol.28, No.12 (2007), 1103-1114
Suggested Citation
P. Kittara, A. Jiralucksanawong, G. Yassin, S. Wangsuya, J. Leech The design of potter horns for THz applications using a genetic algorithm. International Journal of Infrared and Millimeter Waves. Vol.28, No.12 (2007), 1103-1114. doi:10.1007/s10762-007-9290-0 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/24438
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Title
The design of potter horns for THz applications using a genetic algorithm
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Abstract
We describe the design and performance of Potter horns at millimetre and submillimetre wavelength employing a novel software package that we have developed, using Genetic Algorithm. The horn is easy to fabricate and exhibits excellent beam circularity and low cross polarization over a 15% bandwidth which is sufficient for many applications. Excitation of the required higher order modes is done by either a step or a flare discontinuity at the horn throat. In each case we provide design curves that give the optimum parameters of the horn geometry as a function of frequency and beamwidth. The range of values provided covers the parameters required for the design of horns for telescope feeds and various other instruments. The design curves show clearly that the flare-step performance is superior to the traditional groove-step Potter horn. The simulations for designing these horns were carried out at millimetre and submillimetre wavelengths but the results can be scaled to lower or higher frequencies. A key component in the design method is the optimization software that searches for the correct magnitude and location of the flare discontinuities. We have developed a software package based on the combination of modal matching, a genetic algorithm (GA) and downhill simplex optimization. The genetic code is first used to locate the proximity of the global minimum. The set of parameters obtained are then used as a starting point for the simplex method, which refines the parameters to the required accuracy. © 2007 Springer Science+Business Media, LLC.
