[1] |
Pendry, J. B. Negative refraction makes a perfect lens. Phys. Rev. Lett. 85, 3966–3969 (2000). doi: 10.1103/PhysRevLett.85.3966 |
[2] |
Cubukcu, E., Aydin, K., Ozbay, E., Foteinopoulo, S. & Soukoulis, C. M. Negative refraction by photonic crystals. Nature 423, 604–605 (2003). doi: 10.1038/423604b |
[3] |
Fang, N. Sub-diffraction-limited optical imaging with a silver superlens. Science 308, 534–537 (2005). doi: 10.1126/science.1108759 |
[4] |
Jacob, Z., Alekseyev, L. V. & Narimanov, E. Optical hyperlens: far-field imaging beyond the diffraction limit. Opt. Express 14, 8247–8256 (2006). doi: 10.1364/OE.14.008247 |
[5] |
Engheta, N. Circuits with light at nanoscales: optical nanocircuits inspired by metamaterials. Science 317, 1698–1702 (2017). doi: 10.1126/science.1133268 |
[6] |
Liu, Z., Lee, H., Xiong, Y., Sun, C. & Zhang, X. Far-field optical hyperlens magnifying sub-diffraction-limited objects. Science 315, 1686–1686 (2007). doi: 10.1126/science.1137368 |
[7] |
MacDonald, K. F., Sámson, Z. L., Stockman, M. I. & Zheludev, N. I. Ultrafast active plasmonics. Nat. Photon. 3, 55–58 (2009). doi: 10.1038/nphoton.2008.249 |
[8] |
Lin, D., Fan, P., Hasman, E. & Brongersma, M. L. Dielectric gradient metasurface optical elements. Science 345, 298–302 (2014). doi: 10.1126/science.1253213 |
[9] |
Yu, N. & Capasso, F. Flat optics with designer metasurfaces. Nat. Mater. 13, 139–150 (2014). doi: 10.1038/nmat3839 |
[10] |
Kuznetsov, A. I., Miroshnichenko, A. E., Brongersma, M. L., Kivshar, Y. S. & Luk'yanchuk, B. Optically resonant dielectric nanostructures. Science 354, aag2472 (2016). doi: 10.1126/science.aag2472 |
[11] |
Shalaev, V. M. Optical negative-index metamaterials. Nat. Photon. 1, 41–48 (2007). doi: 10.1038/nphoton.2006.49 |
[12] |
Chen, H. -T., Taylor, A. J. & Yu, N. A review of metasurfaces: physics and applications. Rep. Prog. Phys. 79, 076401 (2016). doi: 10.1088/0034-4885/79/7/076401 |
[13] |
Smith, D. R. Metamaterials and negative refractive index. Science 305, 788–792 (2004). doi: 10.1126/science.1096796 |
[14] |
Yu, N. et al. Flat optics: controlling wavefronts with optical antenna metasurfaces. IEEE J. Sel. Top. Quantum Electron. 19, 4700423 (2013). doi: 10.1109/JSTQE.2013.2241399 |
[15] |
Maier, S. A. et al. Local detection of electromagnetic energy transport below the diffraction limit in metal nanoparticle plasmon waveguides. Nat. Mater. 2, 229–232 (2003). doi: 10.1038/nmat852 |
[16] |
Alù, A. & Engheta, N. Achieving transparency with plasmonic and metamaterial coatings. Phys. Rev. E 72, 016623 (2005). doi: 10.1103/PhysRevE.72.016623 |
[17] |
Schurig, D. et al. Metamaterial electromagnetic cloak at microwave frequencies. Science 314, 977–980 (2006). doi: 10.1126/science.1133628 |
[18] |
Pendry, J. B. Controlling electromagnetic fields. Science 312, 1780–1782 (2006). doi: 10.1126/science.1125907 |
[19] |
Cai, W., Chettiar, U. K., Kildishev, A. V. & Shalaev, V. M. Optical cloaking with metamaterials. Nat. Photon. 1, 224–227 (2007). doi: 10.1038/nphoton.2007.28 |
[20] |
Valentine, J., Li, J., Zentgraf, T., Bartal, G. & Zhang, X. An optical cloak made of dielectrics. Nat. Mater. 8, 568–571 (2009). doi: 10.1038/nmat2461 |
[21] |
Narimanov, E. E. & Kildishev, A. V. Optical black hole: broadband omnidirectional light absorber. Appl. Phys. Lett. 95, 041106 (2009). doi: 10.1063/1.3184594 |
[22] |
Oulton, R. F. et al. Plasmon lasers at deep subwavelength scale. Nature 461, 629–632 (2009). doi: 10.1038/nature08364 |
[23] |
Zhao, Y., Belkin, M. A. & Alù, A. Twisted optical metamaterials for planarized ultrathin broadband circular polarizers. Nat. Commun. 3, 870 (2012). doi: 10.1038/ncomms1877 |
[24] |
Watts, C. M. et al. Terahertz compressive imaging with metamaterial spatial light modulators. Nat. Photon. 8, 605–609 (2014). doi: 10.1038/nphoton.2014.139 |
[25] |
Estakhri, N. M., Edwards, B. & Engheta, N. Inverse-designed metastructures that solve equations. Science 363, 1333–1338 (2019). doi: 10.1126/science.aaw2498 |
[26] |
Hughes, T. W., Williamson, I. A. D., Minkov, M. & Fan, S. Wave physics as an analog recurrent neural network. Sci. Adv. 5, eaay6946 (2019). doi: 10.1126/sciadv.aay6946 |
[27] |
Qian, C. et al. Performing optical logic operations by a diffractive neural network. Light. Sci. Appl. 9, 59 (2020). doi: 10.1038/s41377-020-0303-2 |
[28] |
Psaltis, D., Brady, D., Gu, X. -G. & Lin, S. Holography in artificial neural networks. Nature 343, 325–330 (1990). doi: 10.1038/343325a0 |
[29] |
Shen, Y. et al. Deep learning with coherent nanophotonic circuits. Nat. Photon. 11, 441–446 (2017). doi: 10.1038/nphoton.2017.93 |
[30] |
Shastri, B. J. et al. Neuromorphic photonics, principles of. In Encyclopedia of Complexity and Systems Science (eds Meyers, R. A. ) 1–37 (Springer, Berlin Heidelberg, 2018). https://doi.org/10.1007/978-3-642-27737-5_702-1. |
[31] |
Bueno, J. et al. Reinforcement learning in a large-scale photonic recurrent neural network. Optica 5, 756 (2018). doi: 10.1364/OPTICA.5.000756 |
[32] |
Feldmann, J., Youngblood, N., Wright, C. D., Bhaskaran, H. & Pernice, W. H. P. All-optical spiking neurosynaptic networks with self-learning capabilities. Nature 569, 208–214 (2019). doi: 10.1038/s41586-019-1157-8 |
[33] |
Miscuglio, M. et al. All-optical nonlinear activation function for photonic neural networks [Invited]. Opt. Mater. Express 8, 3851 (2018). doi: 10.1364/OME.8.003851 |
[34] |
Tait, A. N. et al. Neuromorphic photonic networks using silicon photonic weight banks. Sci. Rep. 7, 7430 (2017). doi: 10.1038/s41598-017-07754-z |
[35] |
George, J. et al. Electrooptic nonlinear activation functions for vector matrix multiplications in optical neural networks. in Advanced Photonics 2018 (BGPP, IPR, NP, NOMA, Sensors, Networks, SPPCom, SOF) SpW4G. 3 (OSA, 2018). https://doi.org/10.1364/SPPCOM.2018.SpW4G.3. |
[36] |
Mehrabian, A., Al-Kabani, Y., Sorger, V. J. & El-Ghazawi, T. PCNNA: a photonic convolutional neural network accelerator. In Proc. 31st IEEE International System-on-Chip Conference (SOCC) 169–173 (2018). https://doi.org/10.1109/SOCC.2018.8618542. |
[37] |
Sande, G. V., der, Brunner, D. & Soriano, M. C. Advances in photonic reservoir computing. Nanophotonics 6, 561–576 (2017). doi: 10.1515/nanoph-2016-0132 |
[38] |
Lin, X. et al. All-optical machine learning using diffractive deep neural networks. Science 361, 1004–1008 (2018). doi: 10.1126/science.aat8084 |
[39] |
Li, J., Mengu, D., Luo, Y., Rivenson, Y. & Ozcan, A. Class-specific differential detection in diffractive optical neural networks improves inference accuracy. AP 1, 046001 (2019). doi: 10.1075/ap.19006.li |
[40] |
Mengu, D., Luo, Y., Rivenson, Y. & Ozcan, A. Analysis of diffractive optical neural networks and their integration with electronic neural networks. IEEE J. Select. Top. Quantum Electron. 26, 1–14 (2020). doi: 10.1109/JSTQE.2019.2921376 |
[41] |
Veli, M. et al. Terahertz pulse shaping using diffractive surfaces. Nat. Commun. https://doi.org/10.1038/s41467-020-20268-z (2021). |
[42] |
Luo, Y. et al. Design of task-specific optical systems using broadband diffractive neural networks. Light Sci. Appl. 8, 112 (2019). doi: 10.1038/s41377-019-0223-1 |
[43] |
Mengu, D. et al. Misalignment resilient diffractive optical networks. Nanophotonics 9, 4207–4219 (2020). doi: 10.1515/nanoph-2020-0291 |
[44] |
Li, J. et al. Machine vision using diffractive spectral encoding. https://arxiv.org/abs/2005.11387 (2020). [cs, eess, physics] |
[45] |
Esmer, G. B., Uzunov, V., Onural, L., Ozaktas, H. M. & Gotchev, A. Diffraction field computation from arbitrarily distributed data points in space. Signal Process. : Image Commun. 22, 178–187 (2007). http://www.sciencedirect.com/science/article/pii/S0923596506001305 |
[46] |
Goodman, J. W. in Introduction to Fourier Optics. (Roberts and Company Publishers, Englewood, CO, 2005). |
[47] |
Zhang, Z., You, Z. & Chu, D. Fundamentals of phase-only liquid crystal on silicon (LCOS) devices. Light: Sci. Appl. 3, e213 (2014). doi: 10.1038/lsa.2014.94 |
[48] |
Moon, T. K. & Sterling, W. C. in Mathematical methods and algorithms for signal processing (Prentice Hall, Upper Saddle River, NJ, 2000). |
[49] |
CIFAR-10 and CIFAR-100 datasets. https://www.cs.toronto.edu/~kriz/cifar.html (2009). |
[50] |
Kingma, D. P. & Ba, J. Adam: a method for stochastic optimization. https://arxiv.org/abs/1412.6980 (2014). |