Electrically programmable phase-change photonic memory for optical neural networks with nanoseconds in situ training capability

Maoliang Wei; Junying Li; Zequn Chen; Bo Tang; Zhiqi Jia; Peng Zhang; Kunhao Lei; Kai Xu; Jianghong Wu; Chuyu Zhong; Hui Ma; Yuting Ye; Jialing Jian; Chunlei Sun; Ruonan Liu; Ying Sun; Wei. E. I. Sha; Xiaoyong Hu; Jianyi Yang; Lan Li; Hongtao Lin

doi:10.1117/1.AP.5.4.046004

[1] C. Zhang, P. Patras, H. Haddadi. Deep learning in mobile and wireless networking: a survey. IEEE Commun. Surv. Tutor., 21, 2224-2287(2019).

[2] L. Chen et al. Deep neural network based vehicle and pedestrian detection for autonomous driving: a survey. IEEE Trans. Intell. Transp. Syst., 22, 3234-3246(2021).

[3] J. Chai et al. Deep learning in computer vision: a critical review of emerging techniques and application scenarios. Mach. Learn. Appl., 6, 100134(2021).

[4] P. Xu, Z. Zhou. Silicon-based optoelectronics for general-purpose matrix computation: a review. Adv. Photonics, 4, 044001(2022).

[5] H. Zhou et al. Photonic matrix multiplication lights up photonic accelerator and beyond. Light Sci. Appl., 11, 30(2022).

[6] B. J. Shastri et al. Photonics for artificial intelligence and neuromorphic computing. Nat. Photonics, 15, 102-114(2021).

[7] C. Li et al. The challenges of modern computing and new opportunities for optics. PhotoniX, 2, 20(2021).

[8] J. Liu et al. Research progress in optical neural networks: theory, applications and developments. PhotoniX, 2, 5(2021).

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

[10] T. J. Seok et al. Large-scale broadband digital silicon photonic switches with vertical adiabatic couplers. Optica, 3, 64-70(2016).

[11] W. Bogaerts et al. Programmable photonic circuits. Nature, 586, 207-216(2020).

[12] S. Y. Siew et al. Review of silicon photonics technology and platform development. J. Lightwave Technol., 39, 4374-4389(2021).

[13] H. Shu et al. Microcomb-driven silicon photonic systems. Nature, 605, 457-463(2022).

[14] S. Bandyopadhyay et al. Single chip photonic deep neural network with accelerated training(2022).

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

[16] H. Zhang et al. An optical neural chip for implementing complex-valued neural network. Nat. Commun., 12, 457(2021).

[17] J. Y. S. Tan et al. Monadic Pavlovian associative learning in a backpropagation-free photonic network. Optica, 9, 792-802(2022).

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

[19] F. Ashtiani, A. J. Geers, F. Aflatouni. An on-chip photonic deep neural network for image classification. Nature, 606, 501-506(2022).

[20] Y. Shen et al. Deep learning with coherent nanophotonic circuits. Nat. Photonics, 11, 441-446(2017).

[21] Z. G. Cheng et al. On-chip photonic synapse. Sci. Adv., 3, e1700160(2017).

[22] P. Edinger et al. Silicon photonic microelectromechanical phase shifters for scalable programmable photonics. Opt. Lett., 46, 5671-5674(2021).

[23] D. Pérez, I. Gasulla, J. Capmany. Programmable multifunctional integrated nanophotonics. Nanophotonics, 7, 1351-1371(2018).

[24] K. Shportko et al. Resonant bonding in crystalline phase-change materials. Nat. Mater., 7, 653-658(2008).

[25] A.-K. U. Michel et al. Using low-loss phase-change materials for mid-infrared antenna resonance tuning. Nano Lett., 13, 3470-3475(2013).

[26] L. Mao et al. Reversible switching of electromagnetically induced transparency in phase change metasurfaces. Adv. Photonics, 2, 056004(2020).

[27] M. Wuttig, N. Yamada. Phase-change materials for rewriteable data storage. Nat. Mater., 6, 824-832(2007).

[28] J.-F. Song et al. Integrated photonics with programmable non-volatile memory. Sci. Rep., 6, 22616(2016).

[29] J. Geler-Kremer et al. A ferroelectric multilevel non-volatile photonic phase shifter. Nat. Photonics, 16, 491-497(2022).

[30] S. Abe, K. Hane. A silicon microring resonator with a nanolatch mechanism. Microsyst. Technol., 21, 2019-2024(2015).

[31] J. Zheng et al. Nonvolatile electrically reconfigurable integrated photonic switch enabled by a silicon PIN diode heater. Adv. Mater., 32, 2001218(2020).

[32] C. Ríos et al. In-memory computing on a photonic platform. Sci. Adv., 5, eaau5759(2019).

[33] D. Wu et al. Resonant multilevel optical switching with phase change material GST. Nanophotonics, 11, 3437-3446(2022).

[34] N. Farmakidis et al. Electronically reconfigurable photonic switches incorporating plasmonic structures and phase change materials. Adv. Sci., 9, 2200383(2022).

[35] C. Wu et al. Low-loss integrated photonic switch using subwavelength patterned phase change material. ACS Photonics, 6, 87-92(2019).

[36] H. Zhang et al. Miniature multilevel optical memristive switch using phase change material. ACS Photonics, 6, 2205-2212(2019).

[37] Y. Zhang et al. Broadband transparent optical phase change materials for high-performance nonvolatile photonics. Nat. Commun., 10, 4279(2019).

[38] Z. Fang et al. Non-volatile reconfigurable integrated photonics enabled by broadband low-loss phase change material. Adv. Opt. Mater., 9, 2002049(2021).

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

[40] C. Ríos et al. Ultra-compact nonvolatile phase shifter based on electrically reprogrammable transparent phase change materials. PhotoniX, 3, 26(2022).

[41] J. Feldmann et al. All-optical spiking neurosynaptic networks with self-learning capabilities. Nature, 569, 208-214(2019).

[42] X. Ma et al. Photonic tensor core with photonic compute-in-memory, 1-3(2022).

[43] T. W. Hughes et al. Training of photonic neural networks through in situ backpropagation and gradient measurement. Optica, 5, 864-871(2018).

[44] H. Zhou et al. All-in-one silicon photonic polarization processor. Nanophotonics, 8, 2257-2267(2019).

[45] H. Zhou et al. Chip-scale optical matrix computation for PageRank algorithm. IEEE J. Sel. Top. Quantum Electron., 26, 8300910(2020).

[46] S. M. Buckley et al. Photonic online learning: a perspective. Nanophotonics, 12, 833-845(2023).

[47] S. Xu, J. Wang, W. Zou. Optical convolutional neural network with WDM-based optical patching and microring weighting banks. IEEE Photonics Technol. Lett., 33, 89-92(2021).

[48] F. Brückerhoff-Plückelmann et al. Broadband photonic tensor core with integrated ultra-low crosstalk wavelength multiplexers. Nanophotonics, 11, 4063-4072(2022).

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

[50] R. Soref. Mid-infrared photonics in silicon and germanium. Nat. Photonics, 4, 495-497(2010).

[51] M. Nedeljkovic, R. Soref, G. Z. Mashanovich. Free-carrier electrorefraction and electroabsorption modulation predictions for silicon over the 1–14 μm infrared wavelength range. IEEE Photonics J., 3, 1171-1180(2011). https://doi.org/10.1109/JPHOT.2011.2171930

[52] K. Lei et al. Magnetron-sputtered and thermal-evaporated low-loss Sb-Se phase-change films in non-volatile integrated photonics. Opt. Mater. Express, 12, 2815-2823(2022).

[53] Y. Zhang et al. Myths and truths about optical phase change materials: a perspective. Appl. Phys. Lett., 118, 210501(2021).

[54] H. Ballan, M. Declercq. High Voltage Devices and Circuits in Standard CMOS Technologies, 268-269(2013).

[55] C. Zhong et al. Fast thermo-optical modulators with doped-silicon heaters operating at 2 μm. Opt. Express, 29, 23508-23516(2021). https://doi.org/10.1364/OE.430756

[56] M. Wei et al. TDFA-band silicon optical variable attenuator. Prog. Electromagn. Res., 174, 33-42(2022).

[57] S. Liu et al. Thermo-optic phase shifters based on silicon-on-insulator platform: state-of-the-art and a review. Front. Optoelectron., 15, 9(2022).

[58] J. R. Erickson et al. Designing fast and efficient electrically driven phase change photonics using foundry compatible waveguide-integrated microheaters. Opt. Express, 30, 13673-13689(2022).

[59] H. Ma et al. Passive devices at 2 μm wavelength on 200 mm CMOS-compatible silicon photonics platform [Invited]. Chin. Opt. Lett., 19, 071301(2021). https://doi.org/10.3788/COL202119.071301