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All issues Volume 305 (2024) EPJ Web Conf., 305 (2024) 00008 References
Open Access
Issue
EPJ Web Conf.
Volume 305, 2024
6th International Conference on Applications of Optics and Photonics (AOP2024)
Article Number 00008
Number of page(s) 8
DOI https://doi.org/10.1051/epjconf/202430500008
Published online 15 October 2024
  1. Dhote, C., Singh, A., Kumar, S.: Silicon Photonics Sensors for Biophotonic Applications A Review. IEEE Sens. J. 22, 18228–18239 (2022). https://doi.org/10.1109/JSEN.2022.3199663 [CrossRef] [Google Scholar]
  2. Bernabé, S., Wilmart, Q., Hasharoni, K., Hassan, K., Thonnart, Y., Tissier, P., Désières, Y., Olivier, S., Tekin, T., Szelag, B.: Silicon photonics for terabit/s communication in data centers and exascale computers. Solid. State. Electron. 179, (2021). https://doi.org/10.1016/j.sse.2020.107928 [Google Scholar]
  3. Adcock, J.C., Bao, J., Chi, Y., Chen, X., Bacco, D., Gong, Q., Oxenløwe, L.K., Wang, J., Ding, Y.: Advances in Silicon Quantum Photonics. IEEE J. Sel. Top. Quantum Electron. 27, (2021). https://doi.org/10.1109/JSTQE.2020.3025737 [CrossRef] [Google Scholar]
  4. Shastri, B.J., Huang, C., Tait, A., Ferreira de Lima, T., Prucnal, P.R.: Silicon photonic neural network applications and prospects. 52 (2022). https://doi.org/10.1117/12.2614865 [Google Scholar]
  5. Ma, W., Liu, Z., Kudyshev, Z.A., Boltasseva, A., Cai, W., Liu, Y.: Deep learning for the design of photonic structures. Nat. Photonics. 15, 77–90 (2021). https://doi.org/10.1038/s41566-020-0685-y [CrossRef] [Google Scholar]
  6. Jiang, J., Chen, M., Fan, J.A.: Deep neural networks for the evaluation and design of photonic devices. Nat. Rev. Mater. 6, 679–700 (2021). https://doi.org/10.1038/s41578-020-00260-1 [Google Scholar]
  7. Mao, S., Cheng, L., Zhao, C., Khan, F.N., Li, Q., Fu, H.Y.: Inverse design for silicon photonics: From iterative optimization algorithms to deep neural networks. Appl. Sci. 11, (2021). https://doi.org/10.3390/app11093822 [Google Scholar]
  8. Hammond, A.M., Camacho, R.M.: Designing integrated photonic devices using artificial neural networks. Opt. Express. 27, 29620–29638 (2019). https://doi.org/10.1364/oe.27.029620 [CrossRef] [Google Scholar]
  9. Miyatake, Y., Sekine, N., Toprasertpong, K., Takagi, S., Takenaka, M.: Computational design of efficient grating couplers using artificial intelligence. Jpn. J. Appl. Phys. 59, (2020) [Google Scholar]
  10. Vitali, V., Lacava, C., Domínguez Bucio, T., Gardes, F.Y., Petropoulos, P.: Highly efficient dual-level grating couplers for silicon nitride photonics. Sci. Rep. 12, 1–12 (2022). https://doi.org/10.1038/s41598-022-19352-9 [CrossRef] [Google Scholar]
  11. Marchetti, R., Lacava, C., Khokhar, A., Chen, X., Cristiani, I., Richardson, D.J., Reed, G.T., Petropoulos, P., Minzioni, P.: High-efficiency grating-couplers: Demonstration of a new design strategy. Sci. Rep. 7, 1–8 (2017). https://doi.org/10.1038/s41598-017-16505-z [CrossRef] [Google Scholar]
  12. Fantoni, A., Costa, J., Lourenço, P., Vieira, M.: Computer simulation study about the dependence of amorphous silicon photonic waveguides efficiency on the material quality. EPJ Appl. Phys. 90, 1–10 (2020). https://doi.org/10.1051/epjap/2020190250 [Google Scholar]
  13. Almeida, D., Rossi, M., Lourenço, P.J.P.S., Fantoni, A., Costa, J., Vieira, M.: Amorphous silicon grating couplers based on random and quadratic variation of the refractive index. In: Proc. SPIE 12880, Physics and Simulation of Optoelectronic Devices XXXII, 128800J (11 March 2024). p. 38 (2024) [CrossRef] [Google Scholar]
  14. Synopsys Inc.: RSoft Photonic Device Tools, https://www.synopsys.com/photonic-solutions/rsoft-photonic-device-tools/rsoftproducts.html [Google Scholar]
  15. Fantoni, A., Lourenco, P., Vieira, M.: A model for the refractive index of amorphous silicon for FDTD simulation of photonics waveguides. Proc. Int. Conf. Numer. Simul. Optoelectron. Devices, NUSOD. 167–168 (2017). https://doi.org/10.1109/NUSOD.2017.8010044 [Google Scholar]
  16. Corning Inc.: Corning® SMF-28TM Optical Fiber, http://www.photonics.byu.edu/FiberOpticConnectors.parts/images/smf28.pdf [Google Scholar]
  17. Chollet, F.: Deep Learning with Python. Manning Publications Co. (2021) [Google Scholar]

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