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Photonics Research
Vol. 11, Issue 12, 2033 (2023)

Spiking information processing in a single photonic spiking neuron chip with double integrated electronic dendrites

Yahui Zhang^1,2, Shuiying Xiang^1,2,*, Xingxing Guo¹, Yanan Han¹..., Yuechun Shi³, Xiangfei Chen⁴, Genquan Han² and Yue Hao²|Show fewer author(s)

Author Affiliations

¹State Key Laboratory of Integrated Service Networks, Xidian University, Xi’an 710071, China

²State Key Discipline Laboratory of Wide Bandgap Semiconductor Technology, Xidian University, Xi’an 710071, China

³Yongjiang Laboratory, Ningbo 315202, China

⁴Key Laboratory of Intelligent Optical Sensing and Manipulation, Ministry of Education, National Laboratory of Solid State Microstructures, College of Engineering and Applied Sciences, Institute of Optical Communication Engineering, Nanjing University, Nanjing 210023, China

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DOI: 10.1364/PRJ.499767 Cite this Article Set citation alerts

Yahui Zhang, Shuiying Xiang, Xingxing Guo, Yanan Han, Yuechun Shi, Xiangfei Chen, Genquan Han, Yue Hao, "Spiking information processing in a single photonic spiking neuron chip with double integrated electronic dendrites," Photonics Res. 11, 2033 (2023) Copy Citation Text

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References

[1] K. Roy, A. Jaiswal, P. Panda. Towards spike-based machine intelligence with neuromorphic computing. Nature, 575, 607-617(2019).

[2] W. Maass. Networks of spiking neurons: the third generation of neural network models. Neural Netw., 10, 1659-1671(1997).

[3] J. Hao, X. D. Wang, Y. Dan, M. M. Poo, X. H. Zhang. An arithmetic rule for spatial summation of excitatory and inhibitory inputs in pyramidal neurons. Proc. Natl. Acad. Sci. USA, 106, 21906-21911(2009).

[4] A. Payeur, B. Jean-Claude, N. Richard. Classes of dendritic information processing. Curr. Opin. Neurobiol., 58, 78-85(2019).

[5] A. Gidon, T. A. Zolnik, P. Fidzinski, F. Bolduan, A. Papoutsi, P. Poirazi, M. Holtkamp, I. Vida, M. E. Larkum. Dendritic action potentials and computation in human layer 2/3 cortical neurons. Science, 367, 83-87(2020).

[6] H. T. Peng, G. Angelatos, T. F. de Lima, M. A. Nahmias, A. N. Tait, S. Abbaslou, B. J. Shastri, P. R. Prucnal. Temporal information processing with an integrated laser neuron. IEEE J. Sel. Top. Quantum Electron., 26, 5100209(2020).

[7] S. Xu, J. Wang, H. Shu, Z. Zhang, S. Yi, B. Bai, X. Wang, J. Liu, W. Zou. Optical coherent dot-product chip for sophisticated deep learning regression. Light Sci. Appl., 10, 221(2021).

[8] Y. Tian, Y. Zhao, S. Liu, Q. Li, W. Wang, J. Feng, J. Guo. Scalable and compact photonic neural chip with low learning-capability-loss. Nanophotonics, 11, 329-344(2022).

[9] S. Xiang, Y. Shi, X. Guo, Y. Zhang, H. Wang, D. Zheng, Z. Song, Y. Han, S. Gao, S. Zhao, B. Gu, H. Wang, X. Zhu, L. Hou, X. Chen, W. Zheng, X. Ma, Y. Hao. Hardware-algorithm collaborative computing with photonic spiking neuron chip based on integrated Fabry-Pérot laser with saturable absorber. Optica, 10, 162-171(2022).

[10] P. R. Prucnal, B. J. Shastri, T. F. de Lima, M. A. Nahmias, A. N. Tait. Recent progress in semiconductor excitable lasers for photonic spike processing. Adv. Opt. Photon., 8, 228-299(2016).

[11] Y. Shen, N. C. Harris, S. Skirlo, M. Prabhu, T. Baehr-Jones, M. Hochberg, X. Sun, S. Zhao, H. Larochelle, D. Englund, M. Soljačić. Deep learning with coherent nanophotonic circuits. Nat. Photonics, 11, 441-446(2017).

[12] X. Lin, Y. Rivenson, N. T. Yardimci, M. Veli, Y. Luo, M. Jarrahi, A. Ozcan. All-optical machine learning using diffractive deep neural networks. Science, 361, 1004-1008(2018).

[13] G. Wetzstein, A. Ozcan, S. Gigan, S. Fan, D. Englund, M. Soljačić, C. Denz, D. A. B. Miller, D. Psaltis. Inference in artificial intelligence with deep optics and photonics. Nature, 588, 39-47(2020).

[14] W. Zou, B. Ma, S. Xu, X. Zou, X. Wang. Towards an intelligent photonic system. Sci. China Inf. Sci., 63, 160401(2020).

[15] B. J. Shastri, A. N. Tait, T. F. de Lima, W. H. P. Pernice, H. Bhaskaran, C. D. Wright, P. R. Prucnal. Photonics for artificial intelligence and neuromorphic computing. Nat. Photonics, 15, 102-114(2021).

[16] S. Xiang, Y. Han, Z. Song, X. Guo, Y. Zhang, Z. Ren, S. Wang, Y. Ma, W. Zou, B. Ma. A review: photonics devices, architectures, and algorithms for optical neural computing. J. Semicond., 42, 023105(2021).

[17] X. Guo, J. Xiang, Y. Zhang, Y. Su. Integrated neuromorphic photonics: synapses, neurons, and neural networks. Adv. Photon. Res., 2, 2000212(2021).

[18] J. Feldmann, N. Youngblood, M. Karpov, H. Gehring, X. Li, M. Stappers, M. Le Gallo, X. Fu, A. Lukashchuk, A. S. Raja, J. Liu, C. D. Wright, A. Sebastian, T. J. Kippenberg, W. H. P. Pernice, H. Bhaskaran. Parallel convolutional processing using an integrated photonic tensor core. Nature, 589, 52-58(2021).

[19] T. K. Zhou, X. Lin, J. Wu, Y. Chen, H. Xie, Y. Li, J. Fan, H. Wu, L. Fang, Q. Dai. Large-scale neuromorphic optoelectronic computing with a reconfigurable diffractive processing unit. Nat. Photonics, 15, 367-373(2021).

[20] H. Zhou, J. Dong, J. Cheng, W. Dong, C. Huang, Y. Shen, Q. Zhang, M. Gu, C. Qian, H. Chen, Z. Ruan, X. Zhang. Photonic matrix multiplication lights up photonic accelerator and beyond. Light Sci. Appl., 11, 30(2022).

[21] C. Huang, V. J. Sorger, M. Miscuglio, M. Al-Qadasi, A. Mukherjee, L. Lampe, M. Nichols, A. N. Tait, T. F. de Lima, B. A. Marquez, J. Wang, L. Chrostowski, M. P. Fok, D. Brunner, S. Fan, S. Shekhar, P. R. Prucnal, B. J. Shastri. Prospects and applications of photonic neural networks. Adv. Phys. X, 7, 1981155(2022).

[22] A. Zhao, N. Jiang, J. Peng, S. Liu, Y. Zhang, K. Qiu. Parallel generation of low-correlation wideband complex chaotic signals using CW laser and external-cavity laser with self-phase-modulated injection. Opto-Electron. Adv., 5, 200026(2022).

[23] J. Feldmann, N. Youngblood, C. D. Wright, H. Bhaskaran, W. H. P. Pernice. All-optical spiking neurosynaptic networks with self-learning capabilities. Nature, 569, 208-214(2019).

[24] Z. Song, S. Xiang, Z. Ren, S. Wang, A. Wen, Y. Hao. Photonic spiking neural network based on excitable VCSELs-SA for sound azimuth detection. Opt. Express, 28, 1561-1573(2020).

[25] T. Inagaki, K. Inaba, T. Leleu, T. Honjo, T. Ikuta, K. Enbutsu, T. Umeki, R. Kasahara, K. Aihara, H. Takesue. Collective and synchronous dynamics of photonic spiking neurons. Nat. Commun., 12, 2325(2021).

[26] S. Xiang, Z. Ren, Z. Song, Y. Zhang, X. Guo, G. Han, Y. Hao. Computing primitive of fully-VCSELs-based all-optical spiking neural network for supervised learning and pattern classification. IEEE Trans. Neural Netw. Learn. Syst., 32, 2494-2505(2021).

[27] T. Chen, P. Zhou, Y. Huang, Y. Zeng, S. Xiang, N. Li. Boolean logic gates implemented by a single photonic neuron based on a semiconductor Fano laser. Opt. Contin., 1, 1859-1866(2022).

[28] T. Makinwa, K. Inaba, T. Inagaki, Y. Yamada, T. Leleu, T. Honjo, T. Ikuta, K. Enbutsu, T. Umeki, R. Kasahara, K. Aihara, H. Takesue. Experimental observation of chimera states in spiking neural networks based on degenerate optical parametric oscillators. Commun. Phys., 6, 121(2023).

[29] W. Coomans, L. Gelens, S. Beri, J. Danckaert, G. Van der Sande. Solitary and coupled semiconductor ring lasers as optical spiking neurons. Phys. Rev. E, 84, 036209(2011).

[30] A. Hurtado, K. Schires, I. D. Henning, M. J. Adams. Investigation of vertical cavity surface emitting laser dynamics for neuromorphic photonic systems. Appl. Phys. Lett., 100, 103703(2012).

[31] F. Selmi, R. Braive, G. Beaudoin, I. Sagnes, R. Kuszelewicz, S. Barbay. Relative refractory period in an excitable semiconductor laser. Phys. Rev. Lett., 112, 183902(2014).

[32] B. J. Shastri, M. A. Nahmias, A. N. Tait, A. W. Rodriguez, B. Wu, P. R. Prucnal. Spiking processing with a graphene excitable laser. Sci. Rep., 6, 19126(2016).

[33] T. Deng, J. Robertson, A. Hurtado. Controlled propagation of spiking dynamics in vertical-cavity surface-emitting lasers: towards neuromorphic photonic networks. IEEE J. Sel. Top. Quantum Electron., 23, 1800408(2017).

[34] I. Chakraborty, G. Saha, G. Sengupta, K. Roy. Toward fast neural computing using all-photonic phase change spiking neurons. Sci. Rep., 8, 12980(2018).

[35] J. Robertson, T. Ackemann, L. F. Lester, A. Hurtado. Externally-triggered activation and inhibition of optical pulsating regimes in quantum-dot mode-locked lasers. Sci. Rep., 8, 12515(2018).

[36] T. Deng, J. Robertson, Z. Wu, G. Xia, X. Lin, X. Tang, Z. Wang, A. Hurtado. Stable propagation of inhibited spiking dynamics in vertical-cavity surface-emitting lasers for neuromorphic photonic networks. IEEE Access, 6, 67951-67958(2018).

[37] P. Y. Ma, B. J. Shastri, T. F. de Lima, C. Huang, A. N. Tait, M. A. Nahmias, H.-T. Peng, P. R. Prucnal. Simultaneous excitatory and inhibitory dynamics in an excitable laser. Opt. Lett., 43, 3802-3805(2018).

[38] Y. Zhang, S. Xiang, X. Guo, A. Wen, Y. Hao. All-optical inhibitory dynamics in photonic neuron based on polarization mode competition in a VCSEL with an embedded saturable absorber. Opt. Lett., 44, 1548-1551(2019).

[39] J. Robertson, E. Wade, Y. Kopp, Y. Bueno, A. Hurtado. Toward neuromorphic photonic networks of ultrafast spiking laser neurons. IEEE J. Sel. Top. Quantum Electron., 26, 7700715(2020).

[40] V. A. Pammi, K. Alfaro-Bittner, M. G. Clerc, S. Barbay. Photonic computing with single and coupled spiking micropillar lasers. IEEE J. Sel. Top. Quantum Electron., 26, 1500307(2020).

[41] A. Jha, C. Huang, H.-T. Peng, B. Shastri, P. R. Prucnal. Photonic spiking neural networks and graphene-on-silicon spiking neurons. J. Lightwave Technol., 40, 2901-2914(2022).

[42] J. Xiang, Y. Zhang, Y. Zhao, X. Guo, Y. Su. All-optical silicon microring spiking neuron. Photon. Res., 10, 939-946(2022).

[43] Y. Han, S. Xiang, T. Zhang, Y. Zhang, X. Guo, Y. Shi, Y. Hao. Conversion of a single-layer ANN to photonic SNN for pattern recognition. Sci. China Inf. Sci.(2023).

[44] F. Ponulak, A. Kasiński. Supervised learning in spiking neural networks with ReSuMe: sequence learning, classification, and spike shifting. Neural Comput., 22, 467-510(2010).

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Yahui Zhang, Shuiying Xiang, Xingxing Guo, Yanan Han, Yuechun Shi, Xiangfei Chen, Genquan Han, Yue Hao, "Spiking information processing in a single photonic spiking neuron chip with double integrated electronic dendrites," Photonics Res. 11, 2033 (2023)

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