How nanophotonics can drive optical computing toward practical applications – Nature Nanotechnology

Guo, D. et al. DeepSeek-R1 incentivizes reasoning in LLMs through reinforcement learning. Nature 645, 633–638 (2025).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Xiao, C. et al. Densing law of LLMs. Nat. Mach. Intell. 7, 1823–1833 (2025).

Article  Google Scholar 

Gehrig, D. & Scaramuzza, D. Low-latency automotive vision with event cameras. Nature 629, 1034–1040 (2024).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Ates, H. C. et al. End-to-end design of wearable sensors. Nat. Rev. Mater. 7, 887–907 (2022).

Article  PubMed  PubMed Central  Google Scholar 

Mehonic, A. & Kenyon, A. J. Brain-inspired computing needs a master plan. Nature 604, 255–260 (2022).

Article  CAS  PubMed  Google Scholar 

Fu, T. et al. Optical neural networks: progress and challenges. Light Sci. Appl. 13, 263 (2024).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zhou, H. et al. Photonic matrix multiplication lights up photonic accelerator and beyond. Light Sci. Appl. 11, 30 (2022). A review article on comprehensive implementation methods for optical matrix multiplication, including free-space and waveguide-based methods.

Article  PubMed  PubMed Central  Google Scholar 

He, C., Shen, Y. & Forbes, A. Towards higher-dimensional structured light. Light Sci. Appl. 11, 205 (2022).

Article  CAS  PubMed  Google Scholar 

Zheng, Y.-W., Wang, D., Li, Y.-L., Li, N.-N. & Wang, Q.-H. Holographic near-eye display system with large viewing area based on liquid crystal axicon. Opt. Express 30, 34106–34116 (2022).

Article  PubMed  Google Scholar 

Zhou, T., Jiang, Y., Xu, Z., Xue, Z. & Fang, L. Hundred-layer photonic deep learning. Nat. Commun. 16, 10382 (2025).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Yuan, X., Wang, Y., Xu, Z., Zhou, T. & Fang, L. Training large-scale optoelectronic neural networks with dual-neuron optical-artificial learning. Nat. Commun. 14, 7110 (2023).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Chen, Y. et al. All-analog photoelectronic chip for high-speed vision tasks. Nature 623, 48–57 (2023). A paper on a chip-level demonstration of high system-level performance in optical computing with efficient photoelectronic interfaces and eliminating ADCs.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Hua, S. et al. An integrated large-scale photonic accelerator with ultralow latency. Nature 640, 361–367 (2025). A paper on corporate-developed integrated photonic accelerator for ultralow-latency scientific computing with advanced packaging solutions.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Ahmed, S. R. et al. Universal photonic artificial intelligence acceleration. Nature 640, 368–374 (2025). A paper on a universal photonic processor for extensive AI workloads from commercial enterprises with near-electronic precision.

Article  CAS  PubMed  Google Scholar 

Chen, Y. et al. All-optical synthesis chip for large-scale intelligent semantic vision generation. Science 390, 1259–1265 (2025). A paper on an all-optical chip for large-scale cutting-edge generative AI, such as high-resolution semantic generation, with millions of integrated optical neurons.

Article  CAS  PubMed  Google Scholar 

Inagaki, T. et al. Large-scale Ising spin network based on degenerate optical parametric oscillators. Nat. Photon. 10, 415–419 (2016).

Article  CAS  Google Scholar 

Kumar, S., Zhang, H. & Huang, Y.-P. Large-scale Ising emulation with four body interaction and all-to-all connections. Commun. Phys. 3, 108 (2020).

Article  Google Scholar 

Tong, L. et al. Programmable nonlinear optical neuromorphic computing with bare 2D material MoS₂. Nat. Commun. 15, 10290 (2024).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Sozos, K. et al. High-speed photonic neuromorphic computing using recurrent optical spectrum slicing neural networks. Commun. Eng. 1, 24 (2022).

Article  PubMed Central  Google Scholar 

Kalinin, K. P. et al. Analog optical computer for AI inference and combinatorial optimization. Nature 645, 354–361 (2025).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Cheng, J. et al. Multimodal deep learning using on-chip diffractive optics with in situ training capability. Nat. Commun. 15, 6189 (2024).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Tan, M. et al. Photonic signal processor based on a Kerr microcomb for real-time video image processing. Commun. Eng. 2, 94 (2023).

Article  PubMed Central  Google Scholar 

Yi, S. et al. 32-bit photonic processor beyond noise limitation based on parallelized bit-slicing. Opt. Express 33, 37257–37266 (2025).

Article  PubMed  Google Scholar 

Bogaerts, W. et al. Programmable photonic circuits. Nature 586, 207–216 (2020).

Article  CAS  PubMed  Google Scholar 

Xu, Z. et al. Large-scale photonic chiplet Taichi empowers 160-TOPS/W artificial general intelligence. Science 384, 202–209 (2024).

Article  CAS  PubMed  Google Scholar 

Ríos, C. et al. Integrated all-photonic non-volatile multi-level memory. Nat. Photon. 9, 725–732 (2015).

Article  Google Scholar 

Fang, Z. et al. Ultra-low-energy programmable non-volatile silicon photonics based on phase-change materials with graphene heaters. Nat. Nanotechnol. 17, 842–848 (2022).

Article  CAS  PubMed  Google Scholar 

Wang, Y. et al. Electrical tuning of phase-change antennas and metasurfaces. Nat. Nanotechnol. 16, 667–672 (2021).

Article  CAS  PubMed  Google Scholar 

Zhang, Y. et al. Electrically reconfigurable non-volatile metasurface using low-loss optical phase-change material. Nat. Nanotechnol. 16, 661–666 (2021).

Article  CAS  PubMed  Google Scholar 

Wang, Q. et al. Optically reconfigurable metasurfaces and photonic devices based on phase change materials. Nat. Photon. 10, 60–65 (2016).

Article  CAS  Google Scholar 

Li, S.-Q. et al. Phase-only transmissive spatial light modulator based on tunable dielectric metasurface. Science 364, 1087–1090 (2019).

Article  CAS  PubMed  Google Scholar 

Khorasaninejad, M. et al. Metalenses at visible wavelengths: diffraction-limited focusing and subwavelength resolution imaging. Science 352, 1190–1194 (2016).

Article  CAS  PubMed  Google Scholar 

Zetie, K. P., Adams, S. F. & Tocknell, R. M. How does a Mach–Zehnder interferometer work? Phys. Educ. 35, 46–48 (2000).

Article  Google Scholar 

Xu, Q., Schmidt, B., Pradhan, S. & Lipson, M. Micrometre-scale silicon electro-optic modulator. Nature 435, 325–327 (2005).

Article  CAS  PubMed  Google Scholar 

Tomko, J. A. et al. Long-lived modulation of plasmonic absorption by ballistic thermal injection. Nat. Nanotechnol. 16, 47–51 (2021).

Article  CAS  PubMed  Google Scholar 

Haffner, C. et al. Low-loss plasmon-assisted electro-optic modulator. Nature 556, 483–486 (2018).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Ayata, M. et al. High-speed plasmonic modulator in a single metal layer. Science 358, 630–632 (2017).

Article  CAS  PubMed  Google Scholar 

Goodman, J. W., Dias, A. R. & Woody, L. M. Fully parallel, high-speed incoherent optical method for performing discrete Fourier transforms. Opt. Lett. 2, 1–3 (1978).

Article  CAS  PubMed  Google Scholar 

Wang, T. et al. An optical neural network using less than 1 photon per multiplication. Nat. Commun. 13, 123 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Ma, S.-Y., Wang, T., Laydevant, J., Wright, L. G. & McMahon, P. L. Quantum-limited stochastic optical neural networks operating at a few quanta per activation. Nat. Commun. 16, 359 (2025).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Xu, S. et al. Optical coherent dot-product chip for sophisticated deep learning regression. Light Sci. Appl. 10, 221 (2021).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Shen, Y. et al. Deep learning with coherent nanophotonic circuits. Nat. Photon. 11, 441–446 (2017).

Article  CAS  Google Scholar 

Clements, W. R., Humphreys, P. C., Metcalf, B. J., Kolthammer, W. S. & Walmsley, I. A. Optimal design for universal multiport interferometers. Optica 3, 1460–1465 (2016).

Article  Google Scholar 

Feldmann, J. et al. Parallel convolutional processing using an integrated photonic tensor core. Nature 589, 52–58 (2021).

Article  CAS  PubMed  Google Scholar 

Lin, X. et al. All-optical machine learning using diffractive deep neural networks. Science 361, 1004–1008 (2018).

Article  CAS  PubMed  Google Scholar 

Kulce, O., Mengu, D., Rivenson, Y. & Ozcan, A. All-optical synthesis of an arbitrary linear transformation using diffractive surfaces. Light Sci. Appl. 10, 196 (2021).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kulce, O., Mengu, D., Rivenson, Y. & Ozcan, A. All-optical information-processing capacity of diffractive surfaces. Light Sci. Appl. 10, 25 (2021).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Fu, T. et al. Photonic machine learning with on-chip diffractive optics. Nat. Commun. 14, 70 (2023).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Bandyopadhyay, S. et al. Single-chip photonic deep neural network with forward-only training. Nat. Photon. 18, 1335–1343 (2024).

Article  CAS  Google Scholar 

Pai, S. et al. Experimentally realized in situ backpropagation for deep learning in photonic neural networks. Science 380, 398–404 (2023).

Article  CAS  PubMed  Google Scholar 

Khoram, E. et al. Nanophotonic media for artificial neural inference. Photon. Res. 7, 823–827 (2019).

Article  Google Scholar 

Wu, T., Menarini, M., Gao, Z. & Feng, L. Lithography-free reconfigurable integrated photonic processor. Nat. Photon. 17, 710–716 (2023).

Article  CAS  Google Scholar 

Nikkhah, V. et al. Inverse-designed low-index-contrast structures on a silicon photonics platform for vector–matrix multiplication. Nat. Photon. 18, 501–508 (2024).

Article  CAS  Google Scholar 

Chang, J., Sitzmann, V., Dun, X., Heidrich, W. & Wetzstein, G. Hybrid optical-electronic convolutional neural networks with optimized diffractive optics for image classification. Sci. Rep. 8, 12324 (2018).

Article  PubMed  PubMed Central  Google Scholar 

Yan, T. et al. Fourier-space diffractive deep neural network. Phys. Rev. Lett. 123, 023901 (2019).

Article  CAS  PubMed  Google Scholar 

Zhu, H. H. et al. Space-efficient optical computing with an integrated chip diffractive neural network. Nat. Commun. 13, 1044 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Yang, H. et al. Near-energy-free photonic Fourier transformation for convolution operation acceleration. Adv. Photon. 7, 056007 (2025).

Article  CAS  Google Scholar 

Sadeghzadeh, H. & Koohi, S. Translation-invariant optical neural network for image classification. Sci. Rep. 12, 17232 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Shi, W. et al. LOEN: lensless opto-electronic neural network empowered machine vision. Light Sci. Appl. 11, 121 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Song, A., Murty Kottapalli, S. N., Goyal, R., Schölkopf, B. & Fischer, P. Low-power scalable multilayer optoelectronic neural networks enabled with incoherent light. Nat. Commun. 15, 10692 (2024).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zheludev, N. I. & Kivshar, Y. S. From metamaterials to metadevices. Nat. Mater. 11, 917–924 (2012).

Article  CAS  PubMed  Google Scholar 

Zhang, Q., Yang, L. T., Chen, Z. & Li, P. A survey on deep learning for big data. Inf. Fusion 42, 146–157 (2018).

Article  Google Scholar 

Meng, X. et al. High-integrated photonic tensor core utilizing high-dimensional lightwave and microwave multidomain multiplexing. Light Sci. Appl. 14, 27 (2025).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Xu, X. et al. 11 TOPS photonic convolutional accelerator for optical neural networks. Nature 589, 44–51 (2021).

Article  CAS  PubMed  Google Scholar 

Kildishev, A. V., Boltasseva, A. & Shalaev, V. M. Planar photonics with metasurfaces. Science 339, 1232009 (2013).

Article  PubMed  Google Scholar 

Shen, C.-Y. et al. Broadband unidirectional visible imaging using wafer-scale nano-fabrication of multi-layer diffractive optical processors. Light Sci. Appl. 14, 267 (2025).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Bai, B. et al. All-optical image classification through unknown random diffusers using a single-pixel diffractive network. Light Sci. Appl. 12, 69 (2023).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Chen, Y. et al. Photonic unsupervised learning variational autoencoder for high-throughput and low-latency image transmission. Sci. Adv. 9, eadf8437 (2023).

Article  PubMed  PubMed Central  Google Scholar 

Song, M. et al. Single image dehazing algorithm based on optical diffraction deep neural networks. Opt. Express 30, 24394–24406 (2022).

Article  PubMed  Google Scholar 

Işıl, Ç et al. All-optical image denoising using a diffractive visual processor. Light Sci. Appl. 13, 43 (2024).

Article  PubMed  PubMed Central  Google Scholar 

Luo, X. et al. Metasurface-enabled on-chip multiplexed diffractive neural networks in the visible. Light Sci. Appl. 11, 158 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Li, J., Hung, Y.-C., Kulce, O., Mengu, D. & Ozcan, A. Polarization multiplexed diffractive computing: all-optical implementation of a group of linear transformations through a polarization-encoded diffractive network. Light Sci. Appl. 11, 153 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zheng, H. et al. Multichannel meta-imagers for accelerating machine vision. Nat. Nanotechnol. 19, 471–478 (2024).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Devlin, R. C., Ambrosio, A., Rubin, N. A., Mueller, J. P. B. & Capasso, F. Arbitrary spin-to-orbital angular momentum conversion of light. Science 358, 896–901 (2017).

Article  CAS  PubMed  Google Scholar 

Liu, M. et al. Multifunctional metasurfaces enabled by simultaneous and independent control of phase and amplitude for orthogonal polarization states. Light Sci. Appl. 10, 107 (2021).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Yu, X. et al. Parallel optical computing capable of 100-wavelength multiplexing. eLight 5, 10 (2025).

Article  Google Scholar 

Cheng, Y. et al. Photonic neuromorphic architecture for tens-of-task lifelong learning. Light Sci. Appl. 13, 56 (2024).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Duan, Z., Chen, H. & Lin, X. Optical multi-task learning using multi-wavelength diffractive deep neural networks. Nanophotonics 12, 893–903 (2023).

Article  PubMed  PubMed Central  Google Scholar 

Zhou, T. et al. Large-scale neuromorphic optoelectronic computing with a reconfigurable diffractive processing unit. Nat. Photon. 15, 367–373 (2021).

Article  CAS  Google Scholar 

Liu, C. et al. A programmable diffractive deep neural network based on a digital-coding metasurface array. Nat. Electron. 5, 113–122 (2022).

Article  Google Scholar 

Gao, X. et al. Programmable surface plasmonic neural networks for microwave detection and processing. Nat. Electron. 6, 319–328 (2023).

Article  Google Scholar 

Guo, X. et al. Efficient all-optical plasmonic modulators with atomically thin van der Waals heterostructures. Adv. Mater. 32, 1907105 (2020).

Article  CAS  Google Scholar 

Cai, H. et al. All-optical and ultrafast tuning of terahertz plasmonic metasurfaces. Adv. Opt. Mater. 6, 1800143 (2018).

Article  Google Scholar 

Xu, M. et al. High-performance coherent optical modulators based on thin-film lithium niobate platform. Nat. Commun. 11, 3911 (2020).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wang, X., Weigel, P. O., Zhao, J., Ruesing, M. & Mookherjea, S. Achieving beyond-100-GHz large-signal modulation bandwidth in hybrid silicon photonics Mach Zehnder modulators using thin film lithium niobate. APL Photon. 4, 096101 (2019).

Article  Google Scholar 

Shi, Y. et al. Nonlinear germanium-silicon photodiode for activation and monitoring in photonic neuromorphic networks. Nat. Commun. 13, 6048 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wang, C. et al. Monolithic lithium niobate photonic circuits for Kerr frequency comb generation and modulation. Nat. Commun. 10, 978 (2019).

Article  PubMed  PubMed Central  Google Scholar 

Xie, W. et al. Ultrahigh-Q AlGaAs-on-insulator microresonators for integrated nonlinear photonics. Opt. Express 28, 32894–32906 (2020).

Article  CAS  PubMed  Google Scholar 

Kim, S. et al. Dispersion engineering and frequency comb generation in thin silicon nitride concentric microresonators. Nat. Commun. 8, 372 (2017).

Article  PubMed  PubMed Central  Google Scholar 

Säynätjoki, A. et al. Ultra-strong nonlinear optical processes and trigonal warping in MoS₂ layers. Nat. Commun. 8, 893 (2017).

Article  PubMed  PubMed Central  Google Scholar 

Kumar, V. Linear and nonlinear optical properties of graphene: a review. J. Electron. Mater. 50, 3773–3799 (2021).

Article  CAS  Google Scholar 

Du, J. et al. Phosphorene quantum dot saturable absorbers for ultrafast fiber lasers. Sci. Rep. 7, 42357 (2017).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Yanagimoto, R. et al. Programmable on-chip nonlinear photonics. Nature 649, 330–337 (2025).

Article  PubMed  PubMed Central  Google Scholar 

Chen, C. et al. Ultra-broadband all-optical nonlinear activation function enabled by MoTe₂/optical waveguide integrated devices. Nat. Commun. 15, 9047 (2024).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Yan, T. et al. A complete photonic integrated neuron for nonlinear all-optical computing. Nat. Comput. Sci. 5, 1202–1213 (2025).

Article  PubMed  Google Scholar 

Wu, B. et al. Scaling up for end-to-end on-chip photonic neural network inference. Light Sci. Appl. 14, 328 (2025).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Xia, F. et al. Nonlinear optical encoding enabled by recurrent linear scattering. Nat. Photon. 18, 1067–1075 (2024).

Article  CAS  Google Scholar 

Li, Y., Li, J. & Ozcan, A. Nonlinear encoding in diffractive information processing using linear optical materials. Light Sci. Appl. 13, 173 (2024).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Shi, W., Cao, J., Zhang, Q., Li, Y. & Xu, L. Edge computing: vision and challenges. IEEE Internet Things J. 3, 637–646 (2016).

Article  Google Scholar 

Zhang, S. et al. Photonic edge intelligence chip for multi-modal sensing, inference and learning. Nat. Commun. 16, 10136 (2025).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Huang, Z. et al. Pre-sensor computing with compact multilayer optical neural network. Sci. Adv. 10, eado8516 (2024).

Article  PubMed  PubMed Central  Google Scholar 

Sludds, A. et al. Delocalized photonic deep learning on the internet’s edge. Science 378, 270–276 (2022).

Article  CAS  PubMed  Google Scholar 

Gan, Z., Cao, Y., Evans, R. A. & Gu, M. Three-dimensional deep sub-diffraction optical beam lithography with 9-nm feature size. Nat. Commun. 4, 2061 (2013).

Article  PubMed  Google Scholar 

Goi, E. et al. Nanoprinted high-neuron-density optical linear perceptrons performing near-infrared inference on a CMOS chip. Light Sci. Appl. 10, 40 (2021).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Yu, H. et al. All-optical image transportation through a multimode fibre using a miniaturized diffractive neural network on the distal facet. Nat. Photon. 19, 486–493 (2025).

Article  CAS  Google Scholar 

Choi, M. et al. Transferable polychromatic optical encoder for neural networks. Nat. Commun. 16, 5623 (2025).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wei, K. et al. Spatially varying nanophotonic neural networks. Sci. Adv. 10, eadp0391 (2024).

Article  PubMed  PubMed Central  Google Scholar 

Yan, T. et al. Nanowatt all-optical 3D perception for mobile robotics. Sci. Adv. 10, eadn2031 (2024).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Dong, Y., Bai, Y., Zhang, Q., Luan, H. & Gu, M. High-throughput optical neuromorphic graphic processing at millions of images per second. eLight 5, 29 (2025).

Article  Google Scholar 

Gu, M., Dong, Y., Yu, H., Luan, H. & Zhang, Q. Perspective on 3D vertically-integrated photonic neural networks based on VCSEL arrays. Nanophotonics 12, 827–832 (2023).

Article  PubMed  PubMed Central  Google Scholar 

Liao, K. et al. Hetero-integrated perovskite/Si₃N₄ on-chip photonic system. Nat. Photon. 19, 358–368 (2025).

Article  CAS  Google Scholar 

Bie, Y.-Q. et al. A MoTe₂-based light-emitting diode and photodetector for silicon photonic integrated circuits. Nat. Nanotechnol. 12, 1124–1129 (2017).

Article  CAS  PubMed  Google Scholar 

Qian, F. et al. Multi-quantum-well nanowire heterostructures for wavelength-controlled lasers. Nat. Mater. 7, 701–706 (2008).

Article  CAS  PubMed  Google Scholar 

Qi, L., Li, P., Zhang, X., Wong, K. M. & Lau, K. M. Monolithic full-color active-matrix micro-LED micro-display using InGaN/AlGaInP heterogeneous integration. Light Sci. Appl. 12, 258 (2023).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Pan, G. et al. Harnessing the capabilities of VCSELs: unlocking the potential for advanced integrated photonic devices and systems. Light Sci. Appl. 13, 229 (2024).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Chen, Z. et al. Deep learning with coherent VCSEL neural networks. Nat. Photon. 17, 723–730 (2023).

Article  CAS  Google Scholar 

Flöry, N. et al. Waveguide-integrated van der Waals heterostructure photodetector at telecom wavelengths with high speed and high responsivity. Nat. Nanotechnol. 15, 118–124 (2020).

Article  PubMed  PubMed Central  Google Scholar 

Kim, B. et al. Ultrahigh-gain colloidal quantum dot infrared avalanche photodetectors. Nat. Nanotechnol. 20, 237–245 (2025).

Article  CAS  PubMed  Google Scholar 

Liu, W. et al. Graphene charge-injection photodetectors. Nat. Electron. 5, 281–288 (2022).

Article  CAS  Google Scholar 

Wang, F. et al. Multidimensional detection enabled by twisted black arsenic–phosphorus homojunctions. Nat. Nanotechnol. 19, 455–462 (2024).

Article  PubMed  Google Scholar 

Koepfli, S. M. et al. Controlling photothermoelectric directional photocurrents in graphene with over 400-GHz bandwidth. Nat. Commun. 15, 7351 (2024).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Jiao, S. et al. All-optical logic gate computing for high-speed parallel information processing. Opto-Electron. Sci. 1, 220010 (2022).

Article  Google Scholar 

Inagaki, T. et al. A coherent Ising machine for 2000-node optimization problems. Science 354, 603–606 (2016).

Article  CAS  PubMed  Google Scholar 

Estakhri, N. M., Edwards, B. & Engheta, N. Inverse-designed metastructures that solve equations. Science 363, 1333–1338 (2019).

Article  Google Scholar 

Zhang, W. et al. Photonic logic tensor computing beyond Tbit/s per core. Optica 12, 1252–1260 (2025).

Article  CAS  Google Scholar 

Huang, Y., Shi, M., Yu, A. & Xia, L. Design of multifunctional all-optical logic gates based on photonic crystal waveguides. Appl. Opt. 62, 774–781 (2023).

Article  CAS  PubMed  Google Scholar 

Cheng, Z. et al. Device-level photonic memories and logic applications using phase-change materials. Adv. Mater. 30, 1802435 (2018).

Article  Google Scholar 

Okawachi, Y. et al. Demonstration of chip-based coupled degenerate optical parametric oscillators for realizing a nanophotonic spin-glass. Nat. Commun. 11, 4119 (2020).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wu, B. et al. A monolithically integrated optical Ising machine. Nat. Commun. 16, 4296 (2025).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Honjo, T. et al. 100,000-spin coherent Ising machine. Sci. Adv. 7, eabh0952 (2021).

Article  PubMed  PubMed Central  Google Scholar 

Pierangeli, D., Marcucci, G. & Conti, C. Large-scale photonic Ising machine by spatial light modulation. Phys. Rev. Lett. 122, 213902 (2019).

Article  CAS  PubMed  Google Scholar 

Fang, Y., Huang, J. & Ruan, Z. Experimental observation of phase transitions in spatial photonic Ising machine. Phys. Rev. Lett. 127, 043902 (2021).

Article  CAS  PubMed  Google Scholar 

Goodman, J. W. Introduction to Fourier Optics 3rd edn (Roberts & Co., 2005).

Silva, A. et al. Performing mathematical operations with metamaterials. Science 343, 160–163 (2014).

Article  CAS  PubMed  Google Scholar 

Zhou, C., Wang, Y. & Huang, L. All-optical analog differential operation and information processing empowered by meta-devices. Nanophotonics 14, 1021–1044 (2025).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Cordaro, A. et al. Solving integral equations in free space with inverse-designed ultrathin optical metagratings. Nat. Nanotechnol. 18, 365–372 (2023).

Article  CAS  PubMed  Google Scholar 

Tan, S. et al. All-optical computation system for solving differential equations based on optical intensity differentiator. Opt. Express 21, 7008–7013 (2013).

Article  PubMed  Google Scholar 

Tan, S. et al. High-order all-optical differential equation solver based on microring resonators. Opt. Lett. 38, 3735–3738 (2013).

Article  PubMed  Google Scholar 

Tang, Y. et al. Optical neural engine for solving scientific partial differential equations. Nat. Commun. 16, 4603 (2025).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Yuan, H. et al. Microcomb-driven photonic chip for solving partial differential equations. Adv. Photon. 7, 016007 (2025).

Article  CAS  Google Scholar 

Dong, P. et al. Low loss shallow-ridge silicon waveguides. Opt. Express 18, 14474–14479 (2010).

Article  CAS  PubMed  Google Scholar 

Lee, H., Chen, T., Li, J., Painter, O. & Vahala, K. J. Ultra-low-loss optical delay line on a silicon chip. Nat. Commun. 3, 867 (2012).

Article  PubMed  Google Scholar 

Liu, J. et al. High-yield, wafer-scale fabrication of ultralow-loss, dispersion-engineered silicon nitride photonic circuits. Nat. Commun. 12, 2236 (2021).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Lomonte, E. et al. Single-photon detection and cryogenic reconfigurability in lithium niobate nanophotonic circuits. Nat. Commun. 12, 6847 (2021).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Li, Z. et al. High density lithium niobate photonic integrated circuits. Nat. Commun. 14, 4856 (2023).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zhou, W. et al. In-memory photonic dot-product engine with electrically programmable weight banks. Nat. Commun. 14, 2887 (2023).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zhou, T., Wu, W., Zhang, J., Yu, S. & Fang, L. Ultrafast dynamic machine vision with spatiotemporal photonic computing. Sci. Adv. 9, eadg4391 (2023).

Article  PubMed  PubMed Central  Google Scholar 

Ashtiani, F. Programmable photonic latch memory. Opt. Express 33, 3501–3510 (2025).

Article  CAS  PubMed  Google Scholar 

Alexoudi, T., Kanellos, G. T. & Pleros, N. Optical RAM and integrated optical memories: a survey. Light Sci. Appl. 9, 91 (2020).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Feldmann, J. et al. Calculating with light using a chip-scale all-optical abacus. Nat. Commun. 8, 1256 (2017).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wuttig, M., Bhaskaran, H. & Taubner, T. Phase-change materials for non-volatile photonic applications. Nat. Photon. 11, 465–476 (2017).

Article  CAS  Google Scholar 

Chen, R. et al. Non-volatile electrically programmable integrated photonics with a 5-bit operation. Nat. Commun. 14, 3465 (2023).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Chen, R. et al. Opportunities and challenges for large-scale phase-change material integrated electro-photonics. ACS Photon. 9, 3181–3195 (2022).

Article  CAS  Google Scholar 

Chen, S., Li, Y., Wang, Y., Chen, H. & Ozcan, A. Optical generative models. Nature 644, 903–911 (2025).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Siew, S. Y. et al. Review of silicon photonics technology and platform development. J. Light. Technol. 39, 4374–4389 (2021).

Article  CAS  Google Scholar 

Nezami, M. S. et al. Packaging and interconnect considerations in neuromorphic photonic accelerators. IEEE J. Sel. Top. Quantum Electron. 29, 1–11 (2023).

Article  Google Scholar 

Popoff, S. M. et al. A practical guide to digital micro-mirror devices (DMDs) for wavefront shaping. J. Phys. Photon. 8, 023002 (2026).

Article  Google Scholar 

Pivnenko, M., Li, K. & Chu, D. Sub-millisecond switching of multi-level liquid crystal on silicon spatial light modulators for increased information bandwidth. Opt. Express 29, 24614–24628 (2021).

Article  CAS  PubMed  Google Scholar 

Luo, S., Wang, Y., Tong, X. & Wang, Z. Graphene-based optical modulators. Nanoscale Res. Lett. 10, 199 (2015).

Article  PubMed  PubMed Central  Google Scholar 

Pérez-López, D. & Torrijos-Morán, L. Large-scale photonic processors and their applications. Npj Nanophoton 2, 32 (2025).

Article  Google Scholar 

Giannopoulos, I., Mochi, I., Vockenhuber, M., Ekinci, Y. & Kazazis, D. Extreme ultraviolet lithography reaches 5 nm resolution. Nanoscale 16, 15533–15543 (2024).

Article  CAS  PubMed  Google Scholar 

Sreenivasan, S. V. Nanoimprint lithography steppers for volume fabrication of leading-edge semiconductor integrated circuits. Microsyst. Nanoeng. 3, 17075 (2017).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Jia, L. et al. Fabrication technologies for the on-chip integration of 2D materials. Small Methods 6, 2101435 (2022).

Article  Google Scholar 

Adya, U. et al. Post-processing of phase change material in a zero-change commercial silicon photonic process. Opt. Express 32, 27552–27562 (2024).

Article  CAS  PubMed  Google Scholar 

Yang, A. et al. Qwen2 Technical Report. Preprint at https://arxiv.org/abs/2407.10671 (2024).

Dosovitskiy, A. et al. An image is worth 16 × 16 words: transformers for image recognition at scale. In Proc. International Conference on Learning Representations https://go.nature.com/4y4eiTL (ICLR, 2021).

De Marinis, L., Liboiron-Ladouceur, O. & Andriolli, N. Characterization and ENOB analysis of a reconfigurable linear optical processor. In Proc. OSA Advanced Photonics Congress (AP) 2020 (eds Caspani, L., Tauke-Pedretti, A., Leo, F. & Yang, B.) https://doi.org/10.1364/PSC.2020.PsW1F.4 (Optica Publishing Group, 2020).

Lightmatter. Envise. https://lightmatter.co/blog/a-new-kind-of-computer/ (2025).

Neurophos. White paper Neurophos. https://11549dc2-0dc9-4363-9a47-d257d2a497cc.filesusr.com/ugd/79aa3c_85cd1a5477d44f4fa0e423c03ad0746c.pdf?index=true (2025).

Lightstandard. Product. https://www.lightstandard.co/gsxw/93.html (2026).

Lightelligence. PACE2. https://lightelligence.ai/index.php/product/PACE2.html (2026).

Neurophos. TULKAS. https://www.neurophos.com/product (2026).

Lightelligence. Lightelligence. https://www.lightelligence.ai/ (2026).

Chen, L. et al. End-to-end autonomous driving: challenges and frontiers. IEEE Trans. Pattern Anal. Mach. Intell. 46, 10164–10183 (2024).

Article  PubMed  Google Scholar 

Liu, H., Guo, D. & Cangelosi, A. Embodied intelligence: a synergy of morphology, action, perception and learning. ACM Comput. Surv. 57, 186 (2025).

Article  Google Scholar 

Bartolozzi, C., Indiveri, G. & Donati, E. Embodied neuromorphic intelligence. Nat. Commun. 13, 1024 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Perez, E. F. et al. High-performance Kerr microresonator optical parametric oscillator on a silicon chip. Nat. Commun. 14, 242 (2023).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Li, Z. et al. A sub-wavelength Si LED integrated in a CMOS platform. Nat. Commun. 14, 882 (2023).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Hu, Y. et al. Artificial intelligence in nanophotonics: from design to optical computing. Chin. Phys. Lett. 42, 080802 (2025).

Article  Google Scholar 

Molesky, S. et al. Inverse design in nanophotonics. Nat. Photon. 12, 659–670 (2018).

Article  CAS  Google Scholar 

Ma, W. et al. Deep learning for the design of photonic structures. Nat. Photon. 15, 77–90 (2021).

Article  CAS  Google Scholar 

Reinhart, W. F. & Statt, A. Large language models design sequence-defined macromolecules via evolutionary optimization. NPJ Comput. Mater. 10, 262 (2024).

Article  CAS  Google Scholar 

Momeni, A. et al. Training of physical neural networks. Nature 645, 53–61 (2025). A review paper on training strategies for physical neural networks, including backpropagation-based and backpropagation-free approaches.

Article  CAS  PubMed  Google Scholar 

Bai, B. et al. Microcomb-based integrated photonic processing unit. Nat. Commun. 14, 66 (2023).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Chen, H. et al. Diffractive deep neural networks: theories, optimization and applications. Appl. Phys. Rev. 11, 021332 (2024).

Article  CAS  Google Scholar 

Churaev, M. et al. A heterogeneously integrated lithium niobate-on-silicon nitride photonic platform. Nat. Commun. 14, 3499 (2023).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Mackin, C. et al. Optimised weight programming for analogue memory-based deep neural networks. Nat. Commun. 13, 3765 (2022).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Xu, X. et al. Scaling for edge inference of deep neural networks. Nat. Electron. 1, 216–222 (2018).

Article  Google Scholar 

Wang, Z., Wan, T., Ma, S. & Chai, Y. Multidimensional vision sensors for information processing. Nat. Nanotechnol. 19, 919–930 (2024).

Article  CAS  PubMed  Google Scholar 

Pérez-López, D., López, A., DasMahapatra, P. & Capmany, J. Multipurpose self-configuration of programmable photonic circuits. Nat. Commun. 11, 6359 (2020).

Article  PubMed  PubMed Central  Google Scholar 

Lin, H.-C., Wang, Z. & Hsu, C. W. Fast multi-source nanophotonic simulations using augmented partial factorization. Nat. Comput. Sci. 2, 815–822 (2022).

Article  PubMed  PubMed Central  Google Scholar 

NVIDIA Corporation. NVIDIA DGX B300. https://www.nvidia.com/en-us/data-center/hgx/ (2026).

NVIDIA Corporation. NVIDIA GeForce RTX 5090. https://images.nvidia.com/aem-dam/Solutions/geforce/blackwell/nvidia-rtx-blackwell-gpu-architecture.pdf (2026).

NVIDIA Corporation. NVIDIA Jetson Xavier. https://info.nvidia.com/rs/156-OFN-742/images/Jetson_AGX_Xavier_New_Era_Autonomous_Machines.pdf (2026).

Lightmatter. l200. https://lightmatter.co/products/l200/ (2026).

Lightmatter. Passage-M1000-EVK. https://lightmatter.co/products/passage-m1000-evk/ (2026).

Lightelligence. PACE. https://lightelligence.ai/index.php/product/pace-photonic-arithmetic-computing-engine-ai.html (2026).

LightOn. LightOn. https://hc33.hotchips.org/assets/program/posters/HotChips_LigthOn_Aug2021.pdf (2021).