Information Processing Using Transient Dynamics of Semiconductor Lasers Subject to Delayed Feedback

Hicke, Konstantin; Escalona-Morán, M.; Brunner, Daniel; Soriano, Miguel C.; Fischer, Ingo; Mirasso, Claudio R.

doi:10.1109/jstqe.2013.2241738

Cited by 101 publications

(49 citation statements)

References 21 publications

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“…Here we take into account the two polarization modes of the laser and include a third equation for the complex TM electric field. This two-mode model has successfully been used in the case of a delayed optical feedback [25][26][27][28][29] and we recently showed that different models proposed in the literature reduce to the same dimensionless equations [30]. In the case of TE optical injection, the dimensionless rate equations are given by The evolution of 02 passively depends on N and its equation is not shown.…”

Section: Te Injectionmentioning

confidence: 99%

Analytical stability boundaries of an injected two-polarization semiconductor laser

2015

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The classical problem of a semiconductor laser subject to polarized injection is revisited. From the laser rate equations for the transverse electric (TE) and transverse magnetic (TM) modes, we first determine the steady states. We then investigate their linear stability properties and derive analytical expressions for the steady, saddle-node, and Hopf bifurcation points. We highlight conditions for bistability between pure- and mixed-mode steady states for the laser subject to either TE or TM injection. To our knowledge, the first case has not been documented yet. An important parameter is the ratio of the polarization gain coefficients and we explore its effect on the stability and bifurcation diagrams.

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Section: Te Injectionmentioning

confidence: 99%

Analytical stability boundaries of an injected two-polarization semiconductor laser

2015

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“…A similar system was also employed to demonstrate highspeed optical vector and matrix operations [69]. Numerical simulations of this kind of system suggest that the information processing capabilities can still be improved by either increasing the injection strength [70] or by changing the input mask [71].…”

Section: All Optical Delay-based Reservoir Computingmentioning

confidence: 99%

Advances in photonic reservoir computing

2017

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Abstract:We review a novel paradigm that has emerged in analogue neuromorphic optical computing. The goal is to implement a reservoir computer in optics, where information is encoded in the intensity and phase of the optical field. Reservoir computing is a bio-inspired approach especially suited for processing time-dependent information. The reservoir's complex and high-dimensional transient response to the input signal is capable of universal computation. The reservoir does not need to be trained, which makes it very well suited for optics. As such, much of the promise of photonic reservoirs lies in their minimal hardware requirements, a tremendous advantage over other hardware-intensive neural network models. We review the two main approaches to optical reservoir computing: networks implemented with multiple discrete optical nodes and the continuous system of a single nonlinear device coupled to delayed feedback.

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“…In those implementations, the nonlinear response of the reservoir is provided by passive nonlinearity such as saturable absorption of a semiconductor mirror [9][10][11] or by active devices such as optoelectronic modulators [5,8], optical amplifiers [3], or semiconductor lasers [7]. These experiments have been supported by numerical simulations [8,[12][13][14][15]. Numerical simulations also have shown that the different modes of multimode lasers subject to optical delayed feedback can be used independently to process independent tasks in parallel [16].…”

mentioning

confidence: 99%

“…(ii) In the usual procedure of RC, the injection times of the input data (i.e., the inverse of the processing speeds) are close or correspond to the time delay. In addition, in previous experiments, long time delays (time delays much larger than the system's characteristic time) have been used [4][5][6][7][8][9][10][11][12][13][14]16]. We explore here whether time delays less than or comparable to the laser relaxation time can also be suitable for RC systems.…”

mentioning

confidence: 99%

“…The optimal values of these weights are those for which the summation of all the different node responses always approaches the associated target as closely as possible. They can typically be determined with an offline training procedure using digital computers [5][6][7][8][11][12][13][14] or an online training procedure using a field-programmable gate array [17]. In our case, the training is done offline.…”

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Prediction performance of reservoir computing systems based on a diode-pumped erbium-doped microchip laser subject to optical feedback

et al. 2017

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Reservoir computing (RC) systems are computational tools for information processing that can be fully implemented in optics. Here, we experimentally and numerically show that an optically pumped laser subject to optical delayed feedback can yield similar results to those obtained for electrically pumped lasers. Unlike with previous implementations, the input data are injected at a time interval that is much larger than the time-delay feedback. These data are directly coupled to the feedback light beam. Our results illustrate possible new avenues for RC implementations for prediction tasks. Reservoir computing (RC) is a brain-inspired concept for information processing that has been recently demonstrated to be efficient for solving practical time-dependent tasks [1,2]. RC systems operate by ensuring nonlinear mapping between the input and the output, thereby allowing a variety of information processing through training. To perform well, an RC system typically requires high dimensionality and nonlinearity. Traditionally, high dimensionality is obtained by randomly interconnecting a large number of neurons, while the needed nonlinearity can be implemented through sigmoidal activation functions. For example, with an ensemble of 16 interconnected semiconductor optical amplifiers, state-of-the-art performance has been achieved [3].Alternatively, state-of-the-art performance also has been obtained by relying on a single dynamical nonlinear node subject to delayed feedback [4]. This configuration (typically referred to as the delay-based RC) has the advantage of being easy to train and to implement experimentally. It has led to several implementations, even at high processing speeds, using stand-alone commercial telecommunication components [5][6][7][8]. The main differences between these experiments are the type of nonlinearity used and how the input matches with the period of the delay line. In those implementations, the nonlinear response of the reservoir is provided by passive nonlinearity such as saturable absorption of a semiconductor mirror [9][10][11] or by active devices such as optoelectronic modulators [5,8], optical amplifiers [3], or semiconductor lasers [7]. These experiments have been supported by numerical simulations [8,[12][13][14][15]. Numerical simulations also have shown that the different modes of multimode lasers subject to optical delayed feedback can be used independently to process independent tasks in parallel [16]. In all cases, the readout layer is trained (using some form of regression) from the state vectors of the reservoir in response to the training data.Until now, only one experiment has been dedicated to RC systems, in which the processing was done from the response provided by a laser subject to optical delayed feedback [7]. The laser used in this experiment was an electrically pumped singlelongitudinal-mode laser, and the input data were either electrically injected by modulating the pump current or optically injected into the reservoir through optical injection using another laser....

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Information Processing Using Transient Dynamics of Semiconductor Lasers Subject to Delayed Feedback

Cited by 101 publications

References 21 publications

Analytical stability boundaries of an injected two-polarization semiconductor laser

Analytical stability boundaries of an injected two-polarization semiconductor laser

Advances in photonic reservoir computing

Prediction performance of reservoir computing systems based on a diode-pumped erbium-doped microchip laser subject to optical feedback

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