Photonic nonlinear transient computing with multiple-delay wavelength dynamics

Romain Martinenghi (1) , Sergei Rybalko (1) , Maxime Jacquot (1) , Yanne Kouomou Chembo (1) , Laurent Larger (1)

1 FEMTO-ST - Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174)

We report on the experimental demonstration of a hybrid optoelectronic neuromorphic computer based on a complex nonlinear wavelength dynamics including multiple delayed feedbacks with randomly defined weights. This neuromorphic approach is based on a new paradigm of a brain-inspired computational unit, intrinsically differing from Turing machines. This recent paradigm consists in expanding the input information to be processed into a higher dimensional phase space, through the nonlinear transient response of a complex dynamics excited by the input information. The computed output is then extracted via a linear separation of the transient trajectory in the complex phase space. The hyperplane separation is derived from a learning phase consisting of the resolution of a regression problem. The processing capability originates from the nonlinear transient, resulting in nonlinear transient computing. The computational performance is successfully evaluated on a standard benchmark test, namely, a spoken digit recognition task.

Domaines: Optique / photonique; Optique [physics.optics]

Romain Martinenghi, Sergei Rybalko, Maxime Jacquot, Yanne Kouomou Chembo, Laurent Larger. Photonic nonlinear transient computing with multiple-delay wavelength dynamics. Physical Review Letters, 2012, 108, pp.244101. ⟨10.1103/PhysRevLett.108.244101⟩. ⟨hal-00932456⟩