Thèse - Axel Dolcemascolo

14/12/2018 Sophia

Laser à semi-conducteur pour modéliser et contrôler des cellules et des réseaux excitables

Excitable systems are everywhere in Nature, and among them the neuron, which responds to an external stimulus with an all-or-none type of response, is often regarded as the most typical example. This excitability behavior is clearly established as to be one of the underlying operating mechanisms of the nervous system and its analysis in model systems (being them mathematical of physical) can, from one hand, shed some light on the dynamics of neural networks, and from the other, open novel ways for a neuro-mimetic treatment of information.
In this presentation I will present a summarized version of the work realized during my PhD program, where we have considered systems based on semiconductor lasers for modelling excitable systems or coupled neuromorphic networks.
I will firstly briefly describe the context of this work from the point of view of excitable cells, and I will outline the applications potential of this work, namely the possibility of using “neuromimetic” photonic systems as a way to treat information.
Later I will describe the excitable character of a laser with coherent injection. I will detail our results, firstly experimental and subsequently numerical, on the response of this “neuromimetic” system to perturbations repeated in time. Whereas the simplified mathematical model envisions an integrator behavior in response to repeated perturbations, I will show that the system often acts as a resonator, thus imparting the remarkable property of being able to emit a single pulse only if it receives two perturbations that are separated by a specific time interval.
Finally, we will expand our case study to a network of 451 coupled semiconductor lasers in a slow-fast chaotic regime. We will rely on a previous study documenting that a single such element can present a neuromimetic dynamics (in particular, the emission of chaotic pulses originating from a canard phenomenon). Surprisingly for a system having such a large number of degrees of freedom, we observe a dynamics which seems low dimensional chaotic. We will examine the impact of statistical properties of the selected population on the dynamics, and we will link our experimental and numerical observations to the existence of a slow manifold for the mean field and towards whom the dynamics converges thanks to the slow-fact nature of the system.

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