Review articles
B.J. Shastri et al. “Photonics for artificial intelligence and neuromorphic computing,” Nat. Photon. 15, 102 (2021).
Q. Zhang et al. “Artificial neural networks enabled by nanophotonics” Light Sci. Appl. 8, 42 (2019).
T. Ferreira de Lima et al. “Machine learning with neuromorphic photonics,” J. Lightwave Technol. 37, 1515 (2019).
Selected research papers
D. Rosenbluth et al. “A high performance photonic pulse processing device,” Opt. Express 17, 22767 (2009).
M.A. Nahmias et al. “An integrated analog O/E/O link for multi-channel laser neurons,” Appl. Phys. Lett. 108, 151106 (2016).
A.N. Tait et al. “Microring weight banks,” IEEE J. Sel. Top. Quantum Electron. 22, 312 (2016).
Y. Shen et al. “Deep learning with coherent nanophotonic circuits,” Nat. Photon. 11, 441 (2017).
Z. Cheng et al. “On-chip photonic synapse,” Sci. Adv. 3, e1700160 (2017).
Y. Romanyshyn et al. “Energy model of neuron activation,” Neural Comput. 29, 502–518 (2017).
A.N. Tait et al. “Neuromorphic photonic networks using silicon photonic weight banks,” Sci. Rep. 7, 7430 (2017).
R. Amin et al. “ITO-based electro-absorption modulator for photonic neural activation function,” APL Mater. 7, 081112 (2019).
J. Feldmann et al. “All-optical spiking neurosynaptic networks with self-learning capabilities,” Nature 569, 208 (2019).
A.N. Tait et al. “Silicon photonic modulator neuron,” Phys. Rev. Appl. 11, 064043 (2019).
C. Huang et al. “Demonstration of photonic neural network for fiber nonlinearity compensation in long-haul transmission systems,” in 2020 Optical Fiber Communications Conference and Exhibition (OFC), Th4C.6, March 2020.
B. Shi et al. “Deep neural network through an InP SOA-based photonic integrated cross-connect,” IEEE J. Sel. Top. Quantum Electron. 26, 7701111 (2020).
I.A.D. Williamson et al. “Reprogrammable electro-optic nonlinear activation functions for optical neural networks,” IEEE J. Sel. Top. Quantum Electron. 26, 7700412 (2020).