Photonic Reservoir Computing Based on Laser Dynamics with External Feedback

• Published in: Neural Information Processing Vol. 9947; pp. 222 - 230
• Main Authors: Takeda, Seiji, Nakano, Daiju, Yamane, Toshiyuki, Tanaka, Gouhei, Nakane, Ryosho, Hirose, Akira, Nakagawa, Shigeru
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2016; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Energy efficiency; Laser; Recurrent neural network; Reservoir computing; Sequential data processing; Silicon photonics
• ISBN: 3319466860; 9783319466866
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-46687-3_24

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.