Modal classification in optical waveguides using deep learning

References

• Bishop, C.M. Pattern Recognition and Machine Learning; Springer: Singapore, 2016.
   Google Scholar
• Angra S.; Ahuja S. Machine Learning and its Applications: A Review. International Conference on Big Data Analytics and Computational Intelligence (ICBDAC), Chirala, 57–60, 2017.
   Google Scholar
• Ramprasad, R.; Batra, R.; Pilania, G.; Mannodi-Kanakkithodi, A.; Kim, C. Machine Learning in Materials Informatics: Recent Applications and Prospects. Comput. Mater. 2017, 3, 54. doi: 10.1038/s41524-017-0056-5
   Google Scholar
• Goh, G.B.; Hodas, N.O.; Vishnu, A. Deep Learning for Computational Chemistry. Comput. Chem. 2017, 38, 1291–1307. doi: 10.1002/jcc.24764
   Google Scholar
• Baldi, P.; Sadowski, P.; Whiteson, D. Searching for Exotic Particles in High-Energy Physics with Deep Learning. Nat. Commun. 2014, 5, 4308. doi: 10.1038/ncomms5308
   PubMed Web of Science ®Google Scholar
• Zibar, D.; Wymeersch, H.; Lyubomirsky, I. Machine Learning Under the Spotlight. Nat. Phot. 2017, 11, 749–751. doi: 10.1038/s41566-017-0058-3
   Web of Science ®Google Scholar
• Rivenson, Y.; Göröcs, Z.; Günaydin, H.; Zhang, Y.; Wang, H.; Ozcan, A. Deep Learning Microscopy. Optica. 2017, 4, 1437–1443. doi: 10.1364/OPTICA.4.001437
   Web of Science ®Google Scholar
• Sinha, A.; Lee, J.; Li, S.; Barbastathis, G. Lensless Computational Imaging Through Deep Learning. Optica. 2017, 4, 1117–1125. doi: 10.1364/OPTICA.4.001117
   Web of Science ®Google Scholar
• Turduev, M.; Bor, E.; Latifoglu, C.; Giden, I.H.; Hanay, Y.S.; Kurt, H. Ultracompact Photonic Structure Design for Strong Light Confinement and Coupling Into Nanowaveguide. J. Light. Technol. 2018, 36, 2812–2819. doi: 10.1109/JLT.2018.2821361
   Web of Science ®Google Scholar
• Malkiel I.; Nagler A.; Mrejen M.; Arieli U.; Wolf L.; Suchowski H. Deep Learning for Design and Retrieval of Nanophotonic Structures. arXiv:1702.07949, 2017.
   Google Scholar
• Ma, W.; Cheng, F.; Liu, Y. Deep-Learning-Enabled On-Demand Design of Chiral Metamaterials. ACS Nano. 2018, 12, 6326–6334. doi: 10.1021/acsnano.8b03569
   PubMed Web of Science ®Google Scholar
• Liu, D.; Tan, Y.; Khoram, E.; Yu, Z. Training Deep Neural Networks for the Inverse Design of Nanophotonic Structures. ACS Photonics. 2018, 5, 1365–1369. doi: 10.1021/acsphotonics.7b01377
   Web of Science ®Google Scholar
• Kojima K.; Wang B.; Kamilov U.; Koike-Akino T.; Parsons K. Acceleration of FDTD-based Inverse Design Using a Neural Network Approach. In Advanced Photonics 2017 (IPR, NOMA, Sensors, Networks, SPPCom, PS), OSA Technical Digest (online) (Optical Society of America, 2017). Paper ITu1A.4.
   Google Scholar
• LeCun, Y.; Bengio, Y.; Hinton, G. Deep Learning. Nature. 2015, 521, 436–444. doi: 10.1038/nature14539
   PubMed Web of Science ®Google Scholar
• Courville, A.; Goodfellow, I.; Bengio, Y. Deep Learning; MIT Press: Cambridge, 2016.
   Google Scholar
• Okamoto, K. Fundamentals of Optical Waveguides 2nd ed.; Elsevier: London, 2016.
   Google Scholar
• Chuang, S.L. Physics of Optoelectronic Devices; John Wiley & Sons: New York, 1995.
   Google Scholar
• Gorin, A.; Jaouad, A.; Grondin, E.; Aimez, V.; Charette, P. Fabrication of Silicon Nitride Waveguides for Visible-Light Using PECVD: A Study of the Effect of Plasma Frequency on Optical Properties. Opt. Express. 2008, 16, 13509–13516. doi: 10.1364/OE.16.013509
   PubMed Web of Science ®Google Scholar
• Zhao, H.; Kuyken, B.; Clemmen, S.; Leo, F.; Subramanian, A.; Dhakal, A.; Helin, P., et al. Visible-to-Near-Infrared Octave Spanning Supercontinuum Generation in a Silicon Nitride Waveguide. Opt. Lett. 2015, 40, 2177–2180. doi: 10.1364/OL.40.002177
   PubMed Web of Science ®Google Scholar
• Gondarenko, A.; Levy, J.S.; Lipson, M. High Confinement Micron-Scale Silicon Nitride High Q Ring Resonator. Opt. Express. 2009, 17, 11366–11370. doi: 10.1364/OE.17.011366
   PubMed Web of Science ®Google Scholar
• Sun, X.; Alam, M.Z.; Aitchison, J.S.; Mojahedi, M. Compact and Broadband Polarization Beam Splitter Based on a Silicon Nitride Augmented Low-Index Guiding Structure. Opt. Lett. 2016, 41, 163–166. doi: 10.1364/OL.41.000163
   PubMed Web of Science ®Google Scholar
• Chen, L.; Doerr, C.R.; Chen, Y.-K. Compact Polarization Rotator on Silicon for Polarization-Diversified Circuits. Opt. Lett. 2011, 36, 469–471. doi: 10.1364/OL.36.000469
   PubMed Web of Science ®Google Scholar
• Levy, J.S.; Foster, M.A.; Gaeta, A.L.; Lipson, M. Harmonic Generation in Silicon Nitride Ring Resonators. Opt. Express. 2011, 19, 11415–11421. doi: 10.1364/OE.19.011415
   PubMed Web of Science ®Google Scholar
• Hu, Q., et al. Rainbow Trapped in a Self-Similar Coaxial Optical Waveguide. Appl. Phys. Lett. 2010, 96, 161101. doi: 10.1063/1.3399778
   Web of Science ®Google Scholar
• Hu, Q., et al. Position-sensitive Spectral Splitting with a Plasmonic Nanowire on Silicon Chip. Sci. Rep. 2013, 3, 3095. doi: 10.1038/srep03095
   PubMed Web of Science ®Google Scholar
• Yu, C.P.; Chang, H.C. Yee-mesh-based Finite Difference Eigenmode Solver with PML Absorbing Boundary Conditions for Optical Waveguides and Photonic Crystal Fibers. Opt. Express. 2004, 12, 6165–6177. doi: 10.1364/OPEX.12.006165
   PubMed Web of Science ®Google Scholar
• Heaton, J. Introduction to Neural Networks for Java, 2nd ed.; Heaton Research: Chesterfield, 2008.
   Google Scholar
• Møller, M.F. A Scaled Conjugate Gradient Algorithm for Fast Supervised Learning. Neural Netw. 1993, 6, 525. doi: 10.1016/S0893-6080(05)80056-5
   Web of Science ®Google Scholar
• Hagan, M.T.; Menhaj, M.B. Training Feedforward Networks with the Marquardt Algorithm. IEEE Trans. Neural Networks. 1994, 5 (6), 989–993. doi: 10.1109/72.329697
   PubMed Web of Science ®Google Scholar
• https://www.mathworks.com/help/nnet/ug/multilayer-neural-network-architecture.html
   Google Scholar