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|Title:||Integrated silicon photonic device design by attractor selection mechanism based on artificial neural networks: Optical coupler and asymmetric light transmitter.||Authors:||Bor, E.
Hanay, Y. S.
|Issue Date:||29-Oct-2018||Publisher:||OSA - The Optical Society||Source:||Bor, E., Alparslan, O., Turduev, M., Hanay, Y. S., Kurt, H., Arakawa, S. I., & Murata, M. (2018). Integrated silicon photonic device design by attractor selection mechanism based on artificial neural networks: optical coupler and asymmetric light transmitter. Optics express, 26(22), 29032-29044.||Abstract:||Recently, different nanophotonic computational design methods based on optimization algorithms have been proposed which revolutionized the conventional design techniques of photonic integrated devices. The intelligently designed photonic devices have small footprints and high operating performance along with their fabrication feasibility. In this study, we introduce a new approach based on attractor selection algorithm to design photonic integrated devices. In order to demonstrate the potential of the proposed approach, we designed two structures: An optical coupler and an asymmetric light transmitter. The designed photonic devices operate at telecom wavelengths and have compact dimensions. The designed optical coupler has a footprint of only 4 × 2 μm2 and coupling efficiency of 87.5% at a design wavelength of 1550 nm with spatial beam width compression ratio of 10:1. Moreover, the designed optical coupler operates at a wide bandwidth of 6.45% where the transmission efficiency is above 80%. In addition, the designed asymmetric light transmitter with a size of 2 × 2 μm2 has the forward and backward transmission efficiencies of 88.1% and 8.6%, respectively. The bandwidth of 3.47% was calculated for the designed asymmetric light transmitter where the forward transmission efficiency is higher than 80% and the backward efficiency transmission is under 10%. In order to evaluate the operating performance of the designed photonic devices, coupling losses are analyzed. The presented results show that the attractor selection algorithm, which is based on artificial neural networks, can bring a conceptual breakthrough for the design of efficient integrated nanophotonic devices.||URI:||https://doi.org/10.1364/OE.26.029032
|Appears in Collections:||Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering|
PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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