Advertisement

Controllable spiking dynamics in cascaded VCSEL-SA photonic neurons

  • Zhenxue Zhang
  • Zhengmao Wu
  • Dan Lu
  • Guangqiong Xia
  • Tao DengEmail author
Original paper
  • 53 Downloads

Abstract

We propose a photonic neural system composed of three cascaded vertical-cavity surface-emitting lasers with an embedded saturable absorbers (VCSEL-SAs) and numerically investigate the encoding, propagation and storage characteristics of the spiking patterns in this system. The results show that, with suitable perturbation strength, the first VCSEL-SA (VCSEL-SA1) can convert the stimulus into spike response. Increasing both the perturbation strength and the bias current of active region is beneficial to improve the conversion rate. Moreover, the spiking patterns generated by VCSEL-SA1 can be stably propagated into another two VCSEL-SAs (VCSEL-SA2 and VCSEL-SA3) with a certain delay through adjusting the coupling weight. Additionally, after introducing a feedback into VCSEL-SA1, the fired spiking patterns can be successfully stored in this proposed system. The obtained results can offer great potential for future, brain-inspired ultrafast neuromorphic computing system.

Keywords

Vertical-cavity surface-emitting lasers with an embedded saturable absorber (VCSEL-SA) Controllable spiking dynamics Conversion rate Stable propagation Storage characteristics 

Notes

Acknowledgements

This work was supported by National Natural Science Foundation of China (NSFC) (61775184, 61875167); Natural Science Foundation of Chongqing City (CSTC 2019jcyj-msxm X0136).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. 1.
    Nahmias, M.A., Shastri, B.J., Tait, A.N., Lima, T.F.D., Prucnal, P.R.: Neuromorphic photonics. Opt. Photon. News 29, 34–41 (2018)CrossRefGoogle Scholar
  2. 2.
    Feldmann, J., Youngblood, N., Wright, C.D., Bhaskaran, H., Pernice, W.H.P.: All-optical spiking neurosynaptic networks with self-learning capabilities. Nature 569, 208–214 (2019)CrossRefGoogle Scholar
  3. 3.
    Lima, T.F.D., Shastri, B.J., Tait, A.N., Nahmias, M.A., Prucnal, P.R.: Progress in neuromorphic photonics. Nanophoton. 6, 577–599 (2017)Google Scholar
  4. 4.
    Arena, P., Calí, M., Patané, L., Portera, A., Spinosa, A.G.: A CNN-based neuromorphic model for classification and decision control. Nonlinear Dyn. 95, 1999–2017 (2019)CrossRefGoogle Scholar
  5. 5.
    Shen, Y., Harris, N.C., Skirlo, S., Prabhu, M., Baehr-Jones, T., Hochberg, M., Sun, X., Zhao, S.J., Larochelle, H., Englund, D., Soljačić, M.: Deep learning with coherent nanophotonic circuits. Nat. Photon. 11, 441–446 (2017)CrossRefGoogle Scholar
  6. 6.
    Lin, X., Rivenson, Y., Yardimci, N.T., Veli, M., Luo, Y., Jarrahi, M., Ozcan, A.: All-optical machine learning using diffractive deep neural networks. Science 361, 1004–1008 (2018)MathSciNetzbMATHCrossRefGoogle Scholar
  7. 7.
    Jia, B., Wu, Y.C., He, D., Guo, B.H.: Dynamics of transitions from anti-phase to multiple in-phase synchronizations in inhibitory coupled bursting neurons. Nonlinear Dyn. 93, 1599–1618 (2018)CrossRefGoogle Scholar
  8. 8.
    Betley, N.J., Xu, S.J., Cao, Z.F.H., Gong, R., Magnus, C.J., Yu, Y., Sternson, S.M.: Neurons for hunger and thirst transmit a negative-valence teaching signal. Nature 521, 180–185 (2015)CrossRefGoogle Scholar
  9. 9.
    Guo, F., Yu, W., Jung, H.J., Abruzzi, K.C., Luo, W.F., Griffith, L.C., Rosbash, M.: Circadian neuron feedback controls the Drosophila sleep-activity profile. Nature 536, 292–297 (2016)CrossRefGoogle Scholar
  10. 10.
    Kuhara, A., Okumura, M., Kimata, T., Tanizawa, Y., Takano, R., Kimura, K.D., Inada, H., Matsumoto, K., Mori, I.: Temperature sensing by an olfactory neuron in a circuit controlling behavior of C. elegans. Science 320, 803-807 (2008)CrossRefGoogle Scholar
  11. 11.
    Hsu, J.: IBM’s new brain. IEEE Spectr. 51, 17–19 (2014)CrossRefGoogle Scholar
  12. 12.
    Lim, H., Ahn, H.W., Kornijcuk, V., Kim, G., Seok, J.Y., Kim, I., Hwang, C.S., Jeong, D.S.: Relaxation oscillator-realized artificial electronic neurons, their responses, and noise. Nanoscale 8, 9629–9640 (2016)CrossRefGoogle Scholar
  13. 13.
    Deng, T., Robertson, J., Wu, Z.M., Xia, G.Q., Lin, X.D., Tang, X., Wang, Z.J., Hurtado, A.: Stable propagation of inhibited spiking dynamics in vertical-cavity surface-emitting lasers for neuromorphic photonic networks. IEEE Access 6, 67951–67958 (2018)CrossRefGoogle Scholar
  14. 14.
    Xiang, S.Y., Wen, A.J., Pan, W.: Emulation of spiking response and spiking frequency property in VCSEL-based photonic neuron. IEEE Photon. J. 8, 1504109 (2016)CrossRefGoogle Scholar
  15. 15.
    Xiang, S.Y., Zhang, H., Guo, X.X., Hao, Y.: Cascadable neuron-like spiking dynamics in coupled VCSELs subject to orthogonally polarized optical pulse injection. IEEE J. Sel. Top. Quantum Electron. 23, 1700207 (2017)CrossRefGoogle Scholar
  16. 16.
    Hurtado, A., Javaloyes, J.: Controllable spiking patterns in long-wavelength vertical cavity surface emitting lasers for neuromorphic photonics systems. Appl. Phys. Lett. 107, 241103 (2015)CrossRefGoogle Scholar
  17. 17.
    Robertson, J., Deng, T., Javaloyes, J., Hurtado, A.: Controlled inhibition of spiking dynamics in VCSELs for neuromorphic photonics: theory and experiments. Opt. Lett. 42, 1560–1563 (2017)CrossRefGoogle Scholar
  18. 18.
    Li, Q., Wang, Z., Cui, C., Li, R.Q., Li, Y., Liu, B., Wu, C.Q.: Simulation the spiking response of VCSEL-based optical spiking neuron. Opt. Commun. 18, 327–332 (2018)CrossRefGoogle Scholar
  19. 19.
    Van Vaerenbergh, T., Alexander, K., Dambre, J., Bienstman, P.: Excitation transfer between optically injected microdisk lasers. Opt. Express 21, 28922–28932 (2013)CrossRefGoogle Scholar
  20. 20.
    Alexander, K., Van Vaerenbergh, T., Fiers, M., Mechet, P., Dambre, J., Bienstman, P.: Excitability in optically injected microdisk lasers with phase controlled excitatory and inhibitory response. Opt. Express 21, 26182–26191 (2013)CrossRefGoogle Scholar
  21. 21.
    Shastri, B.J., Nahmias, M.A., Tait, A.N., Rodriguez, A.W., Wu, B., Prucnal, P.R.: Spike processing with a graphene excitable laser. Sci. Rep. 6, 19126 (2016)CrossRefGoogle Scholar
  22. 22.
    Shastri, B.J., Nahmias, M.A., Tait, A.N., Prucnal, P.R.: Simulations of a graphene excitable laser for spike processing. Opt. Quantum Electron. 46, 1353–1358 (2014)CrossRefGoogle Scholar
  23. 23.
    Romeira, B., Javaloyes, J., Ironside, C.N., Figueiredo, J.M.L., Balle, S., Piro, O.: Excitability and optical pulse generation in semiconductor lasers driven by resonant tunneling diode photo-detectors. Opt. Express 21, 20931–20940 (2013)CrossRefGoogle Scholar
  24. 24.
    Kelleher, B., Goulding, D., Hegarty, S.P., Huyet, G., Cong, D.Y., Martinez, A., Lemaître, A., Ramdane, A., Fischer, M., Gerschütz, F., Koeth, J.: Excitable phase slips in an injection-locked single-mode quantum-dot laser. Opt. Lett. 34, 440–442 (2009)CrossRefGoogle Scholar
  25. 25.
    Olejniczak, L., Panajotov, K., Thienpont, H., Sciamanna, M.: Self-pulsations and excitability in optically injected quantum-dot lasers: impact of the excited states and spontaneous emission noise. Phys. Rev. A 82, 023807 (2010)CrossRefGoogle Scholar
  26. 26.
    Perego, A.M., Lamberti, M.: Collective excitability, synchronization, and array-enhanced coherence resonance in a population of lasers with a saturable absorber. Phys. Rev. A 94, 033839 (2016)CrossRefGoogle Scholar
  27. 27.
    Zhang, Y.H., Xiang, S.Y., Guo, X.X., Wen, A.J., Hao, Y.: Polarization-resolved and polarization-multiplexed spike encoding properties in photonic neuron based on VCSEL-SA. Sci. Rep. 8, 1–9 (2018)CrossRefGoogle Scholar
  28. 28.
    Mesaritakis, C., Kapsalis, A., Bogris, A., Syvridis, D.: Artificial neuron based on integrated semiconductor quantum dot mode-locked lasers. Sci. Rep. 6, 39317 (2016)CrossRefGoogle Scholar
  29. 29.
    Tait, A.N., Nahmias, M.A., Shastri, B.J., Prucnal, P.R.: Broadcast and weight: An integrated network for scalable photonic spike processing. IEEE J. Lightw. Technol. 32, 4029–4041 (2014)CrossRefGoogle Scholar
  30. 30.
    Barbay, S., Kuszelewicz, R., Yacomotti, A.: Excitability in a semiconductor laser with saturable absorber. Opt. Lett. 36, 4476–4478 (2011)CrossRefGoogle Scholar
  31. 31.
    Koyama, F.: Recent advances of VCSEL photonics. IEEE J. Lightwave Technol. 24, 4502–4513 (2006)CrossRefGoogle Scholar
  32. 32.
    Zhong, D.Z., Ji, Y.Q., Luo, W.: Controllable optoelectric composite logic gates based on the polarization switching in an optically injected VCSEL. Opt. Express 23, 29823–29833 (2015)CrossRefGoogle Scholar
  33. 33.
    Jayaprasath, E., Wu, Z.M., Sivaprakasam, S., Xia, G.Q.: Observation of additional delayed-time in chaos synchronization of uni-directionally coupled VCSELs. Chaos 28, 123103 (2018)MathSciNetCrossRefGoogle Scholar
  34. 34.
    Deng, T., Xia, G.Q., Wu, Z.M.: Broadband chaos synchronization and communication based on mutually coupled VCSELs subject to a bandwidth-enhanced chaotic signal injection. Nonlinear Dyn. 76, 399–407 (2014)CrossRefGoogle Scholar
  35. 35.
    Zhang, Y.H., Xiang, S.Y., Gong, J.K., Guo, X.X., Wen, A.J., Hao, Y.: Spike encoding and storage properties in mutually coupled vertical-cavity surface-emitting lasers subject to optical pulse injection. Appl. Opt. 57, 1731–1737 (2018)CrossRefGoogle Scholar
  36. 36.
    Bruno, G., Julien, J., Giovanna, T., Stéphane, B.: Topological solitons as addressable phase bits in a driven laser. Nat. Commun. 6, 5915 (2015)CrossRefGoogle Scholar
  37. 37.
    Deng, T., Robertson, J., Hurtado, A.: Controlled propagation of spiking dynamics in vertical-cavity surface-emitting lasers: towards neuromorphic photonic network. IEEE J. Sel. Top. Quantum Electron. 23, 1800408 (2017)Google Scholar
  38. 38.
    Prucnal, P.R., Shastri, B.J., Lima, T.F., Nahmias, M.A., Tait, A.N.: Recent progress in semiconductor excitable lasers for photonic spike processing. Adv. Opt. Photon. 8, 228–299 (2016)CrossRefGoogle Scholar
  39. 39.
    Nahmias, M.A., Tait, A.N., Shastri, B.J., Lima, T.F., Prucnal, P.R.: Excitable laser processing network node in hybrid silicon: analysis and simulation. Opt. Express 23, 26800–26813 (2015)CrossRefGoogle Scholar
  40. 40.
    Nugent, D.G.H., Plumb, R.G.S., Fisher, M.A., Davies, D.A.O.: Self-pulsation in vertical-cavity surface-emitting lasers. Electron. Lett. 31, 43–44 (1995)CrossRefGoogle Scholar
  41. 41.
    Shchukin, V.A., Ledentsov, N.N., Qureshi, Z., Ingham, J.D., Penty, R.V., White, I.H., Nadtochy, A.M., Maximov, M.V., Blokhin, S.A., Karachinsky, L.Ya., Novikov, I.I.: Digital data transmission using electro-optically modulated vertical-cavity surface-emitting laser with saturable absorber. Appl. Phys. Lett. 104, 051125 (2014)CrossRefGoogle Scholar
  42. 42.
    Hoogland, S., Dhanjal, S., Tropper, A.C., Roberts, J.S., Haring, R., Paschotta, R., Morier-Genoud, F., Keller, U.: Passively mode-locked diode-pumped surface-emitting semiconductor laser. IEEE Photon. Technol. Lett. 12, 1135–1137 (2000)CrossRefGoogle Scholar
  43. 43.
    Nahmias, M.A., Shastri, B.J., Tait, A.N., Prucnal, P.R.: A leaky integrate-and-fire laser neuron for ultrafast cognitive computing. IEEE J. Sel. Top. Quantum Electron. 19, 1800212 (2013)CrossRefGoogle Scholar
  44. 44.
    Shastri, B.J., Nahmias, M.A., Tait, A.N., Wu, B., Prucnal, P.R.: SIMPEL: Circuit model for photonic spike processing laser neurons. Opt. Express 23, 8029–8044 (2015)CrossRefGoogle Scholar
  45. 45.
    Ma, P.Y., Shastri, B.J., Lima, F.T.D., Tait, A.N., Nahmias, M.A., Prucnal, P.R.: All-optical digital-to-spike conversion using a graphene excitable laser. Opt. Express 25, 33504–33513 (2017)CrossRefGoogle Scholar
  46. 46.
    Selmi, F., Braive, R., Beaudoin, G., Sagnes, I., Kuszelesicz, R., Barbay, S.: Relative refractory period in an excitable semiconductor laser. Phys. Rev. Lett. 112, 183902 (2014)CrossRefGoogle Scholar
  47. 47.
    Garbin, B., Dolcemascolo, A., Prati, F., Javaloyes, J., Tissoni, G., Barland, S.: Refractory period of an excitable semiconductor laser with optical injection. Phys. Rev. E 95, 012214 (2017)CrossRefGoogle Scholar
  48. 48.
    Selmi, F., Braive, R., Beaudoin, G., Sagnes, I., Kuszelewicz, R., Barbay, S.: Neuromimetic dynamics in a micropillar laser with saturable absorber. 2015 European Conference on Lasers and Electro-Optics-European Quantum Electronics Conference. Paper EF_8_1 (2015)Google Scholar
  49. 49.
    Kistler, W.M.: Stable propagation of activity pulses in populations of spiking neurons. Neural Comput. 14, 987–997 (2002)zbMATHCrossRefGoogle Scholar
  50. 50.
    Prucnal, P.R., Shastri, B.J.: Neuromorphic Photonics. CRC Press, Boca Raton (2017)CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.School of Physical Science and TechnologySouthwest UniversityChongqingChina
  2. 2.Key Laboratory of Semiconductor Materials Science, Institute of SemiconductorsChinese Academy of ScienceBeijingChina

Personalised recommendations