Advanced Photonics, Volume. 4, Issue 6, 064002(2022)
Computation at the speed of light: metamaterials for all-optical calculations and neural networks
Fig. 1. Required optical transfer functions for all-optical calculations for (a) first- and (b) second-order differentiation and (c) integration. The black lines represent the required transmission or reflection coefficients, whereas the red dashed lines denote the required phase. Note the
Fig. 2. All-optical calculations using planar films. (a) Experimentally measured (green dots) and numerically fitted (solid lines) spatial transfer functions for three different samples.
Fig. 3. Plasmonic-based metamaterials for all-optical calculations. (a) (i) Reflection coefficient and (ii) meta-atom dimensions for
Fig. 4. All-dielectric metamaterials for all-optical calculations. (a) Calculated optical transfer function for p-polarization at 1120 nm (red and green lines) and quadratic fitting (blue dashed line). (b) (i) Optical image of the 3D macroscopic imaging target of a plastic flower and its bright-field and differentiated imaging results. (ii) The same with a second target. (c) Imaging results for (i) bright-field and (ii) differentiated onion cells. Scale bars:
Fig. 5. Multiplexed and tunable metamaterials for all-optical calculations. (a) Calculated and experimental demonstrations of the two spin-dependent masking functions under 530 nm incidence. (i) The intensity distribution and (ii) phase profile of a Gaussian beam for LCP incidence, and (iii) donut-shaped intensity distribution and (iv) spiral phase profile for a 1ℏ OAM beam for RCP incidence. (v) and (vii) show measured nonparaxial interference patterns with a plane wavefront and (vi) and (viii) show the output states corresponding to LCP and RCP incidence. Insets, handedness of the incident light. (b) Images of undyed onion epidermal cells with a 20× objective lens. (i)–(iv) Bright-field images captured with LCP incident light at the wavelengths of 480, 530, 580, and 630 nm. (v)–(viii) Spiral phase contrast images captured under RCP incidence at the same wavelengths. Scale bar,
Fig. 6. Machine learning using all-optical neural networks. (a) Comparison of the correspondence between ANNs and ONNs. The ANN is made up of neurons and hidden layers, which relate to the physical meta-atoms and cascaded metasurfaces in ONNs. (b) The coordinate system required to design ONNs using diffraction.
Fig. 7. Utilization of metasurfaces for ONNs. (a) Schematic of the input mask layer, showing the logic operation of “1 + 0.” (b) Amplitude and phase response of the dielectric meta-atoms. (c) Experimental setup of the two cascaded metasurfaces. (d) Distribution of the measured normalized intensity of the EM field. Most of the energy is focused to the region denoted for 0 or 1. (e), (f) ONNs for image classification and imager. (e) Schematic of the (i) MNIST data set classification and (ii) imager. (f) (i) An example of an input image expressed in phase and (ii) the output energy distribution. (iii) Confusion matrices and (iv) energy distribution percentages for experimental and numerical results of the fashion data set. (g) On-chip ONN working at visible wavelengths for image classification tasks using (i) MNIST and (ii) fashion data sets for
Fig. 8. Programmable metasurfaces for ONNs. (a) Optical images and reconstructions from the single-layer programmable metasurface. Experimental demonstrations of (b) image classification between the letter “I” and square brackets, (c) simultaneous transmission of four orthogonal codes, and (d) on-site reinforcement learning using the programmable five-layer ONN. Image (a) reproduced with permission from Ref. 131. Copyright 2022 Springer Nature Group. Images (b)–(d) reproduced with permission from Ref. 132. Copyright 2022 Springer Nature Group.
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Trevon Badloe, Seokho Lee, Junsuk Rho, "Computation at the speed of light: metamaterials for all-optical calculations and neural networks," Adv. Photon. 4, 064002 (2022)
Category: Reviews
Received: Oct. 18, 2022
Accepted: Nov. 29, 2022
Posted: Nov. 29, 2022
Published Online: Dec. 23, 2022
The Author Email: Rho Junsuk (jsrho@postech.ac.kr)