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Journal of the Optical Society of America B

Journal of the Optical Society of America B

| OPTICAL PHYSICS

  • Editor: Grover Swartzlander
  • Vol. 30, Iss. 11 — Nov. 1, 2013
  • pp: 3048–3055

Micro ring resonators as building blocks for an all-optical high-speed reservoir-computing bit-pattern-recognition system

Charis Mesaritakis, Vassilis Papataxiarhis, and Dimitris Syvridis  »View Author Affiliations


JOSA B, Vol. 30, Issue 11, pp. 3048-3055 (2013)
http://dx.doi.org/10.1364/JOSAB.30.003048


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Abstract

In this paper, an alternative approach for an integrated photonic reservoir computer is presented. The fundamental building block of the reservoir is based on the nonlinear response of a ring resonator, where effects such as two-photon absorption and nonlinear refractive index variation were taken into consideration. In order to investigate the validity of this scheme, the response of a single add/drop micro ring was simulated through a traveling wave numerical model, and the parameters that affect the nonlinearity of the response were identified. Based on these results, a 5×5 matrix of randomly interconnected resonators was utilized in order to classify different high-bit-rate digital patterns. Simulations confirmed that the proposed system could offer a classification error of 0.5% for bit rates up to 160 Gbps and for 8-bit-length digital words.

© 2013 Optical Society of America

OCIS Codes
(170.0110) Medical optics and biotechnology : Imaging systems
(170.3010) Medical optics and biotechnology : Image reconstruction techniques
(170.3660) Medical optics and biotechnology : Light propagation in tissues

ToC Category:
Nonlinear Optics

History
Original Manuscript: July 17, 2013
Revised Manuscript: October 2, 2013
Manuscript Accepted: October 2, 2013
Published: October 31, 2013

Citation
Charis Mesaritakis, Vassilis Papataxiarhis, and Dimitris Syvridis, "Micro ring resonators as building blocks for an all-optical high-speed reservoir-computing bit-pattern-recognition system," J. Opt. Soc. Am. B 30, 3048-3055 (2013)
http://www.opticsinfobase.org/josab/abstract.cfm?URI=josab-30-11-3048


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References

  1. K. Hornik, M. Stinchcombe, and H. White, “Multilayer feed-forward networks are universal approximators,” Neural Netw. 2, 359–366 (1989). [CrossRef]
  2. D. Psaltis, D. Brady, and K. Wagner, “Adaptive optical networks using photorefractive crystals,” Appl. Opt. 27, 1752–1759 (1988). [CrossRef]
  3. A. Hurtado, K. Schires, I. D. Henning, and M. J. Adams, “Investigation of vertical cavity surface emitting laser dynamics for neuromorphic photonic systems,” AIP Appl. Phys. Lett. 100, 103703 (2012).
  4. K. Kravtsov, M. P. Fok, D. Rosenbluth, and P. R. Prucnal, “Ultrafast all-optical implementation of a leaky integrate-and-fire neuron,” Opt. Express 19, 2133–2147 (2011). [CrossRef]
  5. B. Javidi, J. Li, and Q. Tang, “Optical implementation of neural networks for face recognition by the use of nonlinear joint transform correlators,” Appl. Opt. 34, 3950–3962 (1995). [CrossRef]
  6. M. Hill, E. Edward, E. Frietman, H. de Waardt, H. J. S. Dorren, and G. Khoe, “All fiber-optic neural network using coupled SOA based ring lasers,” IEEE Trans. Neural Netw. 13, 1504–1513 (2002).
  7. S. A. Marhon, C. J. F. Cameron, and S. C. Kremer, “Recurrent neural networks” in Handbook on Neural Information Processing (Springer, 2013), Vol. 49, pp. 29–65.
  8. J. Kilian and H. Siegelmann, “The dynamic universality of sigmoidal neural networks,” Inform. Comput. 128, 48–56 (1996).
  9. B. A. Pearlmutter, “Gradient calculations for dynamic recurrent neural networks: a survey,” IEEE Trans. Neural Netw. 6, 1212–1228 (1995).
  10. H. Jaeger and H. Haas, “Harnessing nonlinearity: predicting chaotic systems and saving energy in wireless communication,” Science 304, 78–80 (2004). [CrossRef]
  11. W. Maass, T. Natschlager, and H. Markram, “Real-time computing without stable states: a new framework for neural computation based on perturbations,” Neural Comput. 14, 2531–2560 (2002). [CrossRef]
  12. E. A. Antonelo, B. Schrauwen, and D. Stroobandt, “Event detection and localization for small mobile robots using reservoir computing,” Neural Netw. 21, 862–871 (2008). [CrossRef]
  13. P. Joshi and W. Maass, “Movement generation and control with generic neural microcircuits,” in Proceedings of BIO-AUDIT (Springer, 2004), pp. 16–31.
  14. B. Schrauwen, M. D’Haene, D. Verstraeten, and J. V. Campenhout, “Compact hardware liquid state machines on FPGA for real-time speech recognition,” Neural Netw. 21, 511–523 (2008). [CrossRef]
  15. B. Schrauwen, J. Defour, D. Verstraeten, and J. V. Campenhout, “The introduction of time-scales in reservoir computing, applied to isolated digits recognition,” Artificial Neural Networks—ICANN (Springer, 2007), Vol. 4668, pp. 471–479.
  16. P. Buteneers, B. Schrauwen, D. Verstraeten, and D. Stroobandt, “Real-time epileptic seizure detection on intra-cranial rat data using reservoir computing,” Advances in Neuro-Information Processing (Springer, 2013), Vol. 5506, pp. 56–63.
  17. K. Vandoorne, W. Dierckx, B. Schrauwen, D. Verstraeten, R. Baets, P. Bienstman, and J. V. Campenhout, “Towards optical signal processing using photonic reservoir computing,” Opt. Express 16, 11182–11192 (2008). [CrossRef]
  18. M. Fiers, T. V. Vaerenbergh, K. Caluwaerts, D. V. Ginste, B. Schrauwen, J. Dambre, and P. Bienstman, “Time-domain and frequency-domain modeling of nonlinear optical components at the circuit-level using a node-based approach,” J. Opt. Soc. Am. B 29, 896–900 (2012). [CrossRef]
  19. L. Larger, M. C. Soriano, D. Brunner, L. Appeltant, J. M. Gutierrez, L. Pesquera, C. R. Mirasso, and I. Fischer, “Photonic information processing beyond Turing: an optoelectronic implementation of reservoir computing” Opt. Express 20, 3241–3249 (2012). [CrossRef]
  20. L. Appeltant, M. C. Soriano, G. V. der Sande, J. Danckaert, S. Massar, J. Dambre, B. Schrauwen, C. R. Mirasso, and I. Fischer, “Information processing using a single dynamical node as complex system,” Nat. Commun. 2, 468 (2011). [CrossRef]
  21. M. C. Soriano, S. Ortín, D. Brunner, L. Larger, C. R. Mirasso, I. Fischer, and L. Pesquera, “Optoelectronic reservoir computing: tackling noise-induced performance degradation” Opt. Express 21, 12–20 (2013). [CrossRef]
  22. B. E. Little, S. T. Chu, H. A. Haus, J. Foresi, and J. P. Laine, “Microring resonator channel dropping filters,” J. Lightwave Technol. 15, 998–1005 (1997). [CrossRef]
  23. H. Simos, C. Mesaritakis, D. Alexandropoulos, and D. Syvridis, “Intraband cross talk properties of add–drop filters based on active microring resonators,” IEEE Photon. Technol. Lett. 19, 1649–1651 (2007). [CrossRef]
  24. H. Yi, D. S. Citrin, and Z. Zhou, “Coupling-induced high-sensitivity silicon microring intensity-based sensor,” J. Opt. Soc. Am. B 28, 1611–1615 (2011). [CrossRef]
  25. A. Pasquazi, M. Peccianti, B. E. Little, S. T. Chu, D. J. Moss, and R. Morandotti, “Stable, dual mode, high repetition rate mode-locked laser based on a microring resonator,” Opt. Express 20, 27355–27363 (2012). [CrossRef]
  26. T. V. Vaerenbergh, M. Fiers, K. Vandoorne, B. Schneider, J. Dambre, and P. Bienstman, “Towards a photonic spiking neuron: excitability in a silicon-on-insulator microring,” International Symposium on Nonlinear Theory and its Applications, Palma, Mallorca, 2012, pp. 767–770.
  27. S. Mikroulis, H. Simos, E. Roditi, and D. Syvridis, “Ultrafast all-optical AND logic operation based on FWM in a passive InGaAsP-InP microring resonator,” IEEE Photon. Technol. Lett. 17, 1878–1880 (2005).
  28. A. Yariv, “Critical coupling and its control in optical waveguide-ring resonator systems,” IEEE Photon. Technol. Lett. 14, 483–485 (2002). [CrossRef]
  29. J. Niehusmann, A. Vörckel, P. H. Bolivar, T. Wahlbrink, W. Henschel, and H. Kurz, “Ultrahigh-quality-factor silicon-on-insulator microring resonator,” Opt. Lett. 29, 2861–2863 (2004). [CrossRef]
  30. C. W. Tee, K. A. Williams, R. V. Penty, and I. H. White, “Fabrication-tolerant active-passive integration scheme for vertically coupled microring resonator,” IEEE J. Sel. Top. Quantum Electron. 12, 108–116 (2006).
  31. J. Yao, D. Leuenberger, M.-C. M. Lee, and M. C. Wu, “Silicon microtoroidal resonators with integrated MEMS tunable coupler,” IEEE J. Sel. Top. Quantum Electron. 13, 202–208 (2007).

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