Transmitting ultra-high symbol rate optical signals remains a challenge due to their high sensitivity to fluctuations
of GVD and higher orders of dispersion in the transmission link. Being able to cancel the impairments
due to those fluctuations is a key requirement to make transmission of ultrashort optical pulses practical. We
demonstrate an automatic compensation scheme able to keep an Optical Time Division Multiplexed (OTDM)
signal stable at a bandwidth of up to 1.28 Tbaud in spite of external perturbations. Our approach is based on
monitoring the signal with a photonic-chip-based all-optical RF-spectrum analyzer. The measurement of a
single parameter extracted from the RF-spectrum is used to drive a multidimensional optimization algorithm.
We apply the method to the real time simultaneous compensation for 2nd, 3rd and 4th order dispersion using
an LCOS spectral pulse shaper (SPS) as a tunable dispersion compensator.
KEYWORDS: Neural networks, Photonics, Data processing, Optoelectronics, Analog electronics, Complex systems, Current controlled current source, Neodymium, Dynamical systems, Optical signal processing
At the boundaries between photonics and dynamic systems theory, we combine recent advances in neural networks with opto-electronic nonlinearities to demonstrate a new way to perform optical information processing.
The concept of reservoir computing arose recently as a powerful solution to the issue of training recurrent neural networks. Indeed, it is comparable to, or even outperforms, other state of the art solutions for tasks such as speech recognition or time series prediction. As it is based on a static topology, it allows making the most of very simple physical architectures having complex nonlinear dynamics. The method is inherently robust to noise and does not require explicit programming operations. It is therefore particularly well adapted for analog realizations. Among the various implementations of the concept that have been proposed, we focus on the field of optics.
Our experimental reservoir computer is based on opto-electronic technology, and can be viewed as an intermediate step towards an all optical device. Our fiber optics system is based on a nonlinear feedback loop operating at the threshold of chaos. In its present preliminary stage it is already capable of complicated tasks like modeling nonlinear systems with memory.
Our aim is to demonstrate that such an analog reservoir can have performances comparable to state of the art digital implementations of Neural Networks. Furthermore, our system can in principle be operated at very high frequencies thanks to the high speed of photonic devices. Thus one could envisage targeting applications such as online information processing in broadband telecommunications.
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