Photonic Reservoir Computing Based on Laser Dynamics with External Feedback

  • Seiji Takeda
  • Daiju Nakano
  • Toshiyuki Yamane
  • Gouhei Tanaka
  • Ryosho Nakane
  • Akira Hirose
  • Shigeru Nakagawa
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9947)


Reservoir computing is a novel paradigm of neural network, offering advantages in low learning cost and ease of implementation as hardware. In this paper we propose a concept of reservoir computing consisting of a semiconductor laser subject to external feedback by a mirror, where input signal is supplied as modulation pattern of mirror reflectivity. In that system, non-linear interaction between optical field and electrons are enhanced in complex manner under substantial external feedback, leading to achieve highly nonlinear projection of input electric signal to output optical field intensity. It is exhibited that the system can most efficiently classify waveforms of sequential input data when operating around laser oscillation’s effective threshold.


Reservoir computing Recurrent neural network Sequential data processing Laser Silicon photonics Energy efficiency 


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Seiji Takeda
    • 1
  • Daiju Nakano
    • 1
  • Toshiyuki Yamane
    • 1
  • Gouhei Tanaka
    • 2
  • Ryosho Nakane
    • 2
  • Akira Hirose
    • 2
  • Shigeru Nakagawa
    • 1
  1. 1.IBM Research – TokyoKawasakiJapan
  2. 2.Graduate School of EngineeringThe University of TokyoTokyoJapan

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