Advanced search
2 files | 1.08 MB Add to list

Toward neuro-inspired computing using a small network of micro-ring resonators on an integrated photonic chip

Author
Organization
Project
Abstract
We present in this work numerical simulations of the performance of an on-chip photonic reservoir computer using nonlinear microring resonator as neurons. We present dynamical properties of the nonlinear node and the reservoir computer, and we analyse the performance of the reservoir on a typical nonlinear Boolean task : the delayed XOR task. We study the performance for various designs (number of nodes, and length of the synapses in the reservoir), and with respect to the properties of the optical injection of the data (optical detuning and power). From this work, we find that such a reservoir has state-of-the art level of performance on this particular task - that is a bit error rate of 2.5 10(-4) - at 20 Gb/s, with very good power efficiency (total injected power lower than 1.0 mW).
Keywords
Neuromorphic Computing, Reservoir Computing, Integrated Photonics, Microring Resonators, SELF-PULSATION, BISTABILITY

Downloads

  • (...).pdf
    • full text (Published version)
    • |
    • UGent only
    • |
    • PDF
    • |
    • 543.73 KB
  • pub 2228a.pdf
    • full text (Accepted manuscript)
    • |
    • open access
    • |
    • PDF
    • |
    • 538.20 KB

Citation

Please use this url to cite or link to this publication:

MLA
Denis-le Coarer, Florian, et al. “Toward Neuro-Inspired Computing Using a Small Network of Micro-Ring Resonators on an Integrated Photonic Chip.” NEURO-INSPIRED PHOTONIC COMPUTING, edited by Marc Sciamanna and Peter Bienstman, vol. 10689, SPIE, 2018, pp. 1–9, doi:10.1117/12.2306780.
APA
Denis-le Coarer, F., Freiberger, M., Dambre, J., Bienstman, P., Rontani, D., Katumba, A., & Sciamanna, M. (2018). Toward neuro-inspired computing using a small network of micro-ring resonators on an integrated photonic chip. In M. Sciamanna & P. Bienstman (Eds.), NEURO-INSPIRED PHOTONIC COMPUTING (Vol. 10689, pp. 1–9). https://doi.org/10.1117/12.2306780
Chicago author-date
Denis-le Coarer, Florian, Matthias Freiberger, Joni Dambre, Peter Bienstman, Damien Rontani, Andrew Katumba, and Marc Sciamanna. 2018. “Toward Neuro-Inspired Computing Using a Small Network of Micro-Ring Resonators on an Integrated Photonic Chip.” In NEURO-INSPIRED PHOTONIC COMPUTING, edited by Marc Sciamanna and Peter Bienstman, 10689:1–9. SPIE. https://doi.org/10.1117/12.2306780.
Chicago author-date (all authors)
Denis-le Coarer, Florian, Matthias Freiberger, Joni Dambre, Peter Bienstman, Damien Rontani, Andrew Katumba, and Marc Sciamanna. 2018. “Toward Neuro-Inspired Computing Using a Small Network of Micro-Ring Resonators on an Integrated Photonic Chip.” In NEURO-INSPIRED PHOTONIC COMPUTING, ed by. Marc Sciamanna and Peter Bienstman, 10689:1–9. SPIE. doi:10.1117/12.2306780.
Vancouver
1.
Denis-le Coarer F, Freiberger M, Dambre J, Bienstman P, Rontani D, Katumba A, et al. Toward neuro-inspired computing using a small network of micro-ring resonators on an integrated photonic chip. In: Sciamanna M, Bienstman P, editors. NEURO-INSPIRED PHOTONIC COMPUTING. SPIE; 2018. p. 1–9.
IEEE
[1]
F. Denis-le Coarer et al., “Toward neuro-inspired computing using a small network of micro-ring resonators on an integrated photonic chip,” in NEURO-INSPIRED PHOTONIC COMPUTING, Strassbourg, France, 2018, vol. 10689, pp. 1–9.
@inproceedings{8578433,
  abstract     = {{We present in this work numerical simulations of the performance of an on-chip photonic reservoir computer using nonlinear microring resonator as neurons. We present dynamical properties of the nonlinear node and the reservoir computer, and we analyse the performance of the reservoir on a typical nonlinear Boolean task : the delayed XOR task. We study the performance for various designs (number of nodes, and length of the synapses in the reservoir), and with respect to the properties of the optical injection of the data (optical detuning and power). From this work, we find that such a reservoir has state-of-the art level of performance on this particular task - that is a bit error rate of 2.5 10(-4) - at 20 Gb/s, with very good power efficiency (total injected power lower than 1.0 mW).}},
  articleno    = {{UNSP 1068908}},
  author       = {{Denis-le Coarer, Florian and Freiberger, Matthias and Dambre, Joni and Bienstman, Peter and Rontani, Damien and Katumba, Andrew and Sciamanna, Marc}},
  booktitle    = {{NEURO-INSPIRED PHOTONIC COMPUTING}},
  editor       = {{Sciamanna, Marc and Bienstman, Peter}},
  isbn         = {{9781510619050}},
  issn         = {{0277-786X}},
  keywords     = {{Neuromorphic Computing,Reservoir Computing,Integrated Photonics,Microring Resonators,SELF-PULSATION,BISTABILITY}},
  language     = {{eng}},
  location     = {{Strassbourg, France}},
  pages        = {{UNSP 1068908:1--UNSP 1068908:9}},
  publisher    = {{SPIE}},
  title        = {{Toward neuro-inspired computing using a small network of micro-ring resonators on an integrated photonic chip}},
  url          = {{http://doi.org/10.1117/12.2306780}},
  volume       = {{10689}},
  year         = {{2018}},
}

Altmetric
View in Altmetric
Web of Science
Times cited: