Characterizing the deterministic nature of individual power dropouts in semiconductor lasers subject to delayed feedback

Hicke, Konstantin; Porté, Xavier; Fischer, Ingo

doi:10.1103/physreve.88.052904

Cited by 10 publications

(9 citation statements)

References 30 publications

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“…In the LFF regime the laser intensity drops out irregularly (see Fig.1), in an apparently random manner, each dropout (the laser "spike") being followed by a gradual, step-like recovery [15][16][17][18][19][20][21][22][23]. To study entrainment, external forcing can be implemented via a direct modulation of the laser pump current [24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Effects of periodic forcing on the temporally correlated spikes of a semiconductor laser with feedback

Sorrentino¹,

Quintero-Quiroz²,

Aragoneses³

et al. 2015

Opt. Express

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Optical excitable devices that mimic neuronal behavior can be building-blocks of novel, brain-inspired information processing systems. A relevant issue is to understand how such systems represent, via correlated spikes, the information of a weak external input. Semiconductor lasers with optical feedback operating in the low frequency fluctuations regime have been shown to display optical spikes with intrinsic temporal correlations similar to those of biological neurons. Here we investigate how the spiking laser output represents a weak periodic input that is implemented via direct modulation of the laser pump current. We focus on understanding the influence of the modulation frequency. Experimental sequences of inter-spike-intervals (ISIs) are recorded and analyzed by using the ordinal symbolic methodology that identifies and characterizes serial correlations in datasets. The change in the statistics of the various symbols with the modulation frequency is empirically shown to be related to specific changes in the ISI distribution, which arise due to different phase-locking regimes. A good qualitative agreement is also found between simulations of the Lang and Kobayashi model and observations. This methodology is an efficient way to detect subtle changes in noisy correlated ISI sequences and may be applied to investigate other optical excitable devices.

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Section: Introductionmentioning

confidence: 99%

Effects of periodic forcing on the temporally correlated spikes of a semiconductor laser with feedback

Sorrentino¹,

Quintero-Quiroz²,

Aragoneses³

et al. 2015

Opt. Express

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“…The LFFs and CC regimes have been known for decades and their dynamical origin and statistical properties have been intensively studied202122232425262728293031323334353637383940414243444546474849505152535455565758. However, to the best of our knowledge, the transition points from noisy emission to LFFs, and from LFFs to CC, occurring as the pump current increases, have not yet been quantified.…”

mentioning

confidence: 99%

Quantitative identification of dynamical transitions in a semiconductor laser with optical feedback

Quintero-Quiroz

Tiana-Alsina

Romà

et al. 2016

Sci Rep

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Identifying transitions to complex dynamical regimes is a fundamental open problem with many practical applications. Semi- conductor lasers with optical feedback are excellent testbeds for studying such transitions, as they can generate a rich variety of output signals. Here we apply three analysis tools to quantify various aspects of the dynamical transitions that occur as the laser pump current increases. These tools allow to quantitatively detect the onset of two different regimes, low-frequency fluctuations and coherence collapse, and can be used for identifying the operating conditions that result in specific dynamical properties of the laser output. These tools can also be valuable for analyzing regime transitions in other complex systems.

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“…A successful approach for studying such systems is by focusing on an event-level description of their dynamics, considering, for example, intervals between events. Examples of this approach include neuronal inter-spike intervals, heart beat-to-beat intervals, earthquake waiting times, intervals between peak communication activity in social networks, etc 5678910…”

mentioning

confidence: 99%

Unveiling the complex organization of recurrent patterns in spiking dynamical systems

Aragoneses

Perrone

Sorrentino

et al. 2014

Sci Rep

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Complex systems displaying recurrent spike patterns are ubiquitous in nature. Understanding the organization of these patterns is a challenging task. Here we study experimentally the spiking output of a semiconductor laser with feedback. By using symbolic analysis we unveil a nontrivial organization of patterns, revealing serial spike correlations. The probabilities of the patterns display a well-defined, hierarchical and clustered structure that can be understood in terms of a delayed model. Most importantly, we identify a minimal model, a modified circle map, which displays the same symbolic organization. The validity of this minimal model is confirmed by analyzing the output of the forced laser. Since the circle map describes many dynamical systems, including neurons and cardiac cells, our results suggest that similar correlations and hierarchies of patterns can be found in other systems. Our findings also pave the way for optical neurons that could provide a controllable set up to mimic neuronal activity.

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Characterizing the deterministic nature of individual power dropouts in semiconductor lasers subject to delayed feedback

Cited by 10 publications

References 30 publications

Effects of periodic forcing on the temporally correlated spikes of a semiconductor laser with feedback

Effects of periodic forcing on the temporally correlated spikes of a semiconductor laser with feedback

Quantitative identification of dynamical transitions in a semiconductor laser with optical feedback

Unveiling the complex organization of recurrent patterns in spiking dynamical systems

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