Faculty Mentor

Andres Aragoneses

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Lasers are stable devices with a broad spectrum of applications. They can be perturbed to induce complex dynamics in their output intensity. One interesting regime in semiconductor lasers is that the output intensity of the laser emits a sequence of non-regular optical spikes. This behavior resembles that of neurons. We use a semiconductor laser with optical feedback from two mirrors to characterize the behavior of the laser's power output. The data is then analyzed by transforming the intensity time series into a sequence of patterns or words. By doing this we want to explore how the laser changes its preferred words as the pump current is increased and characterize the effect of each one of both feedbacks. This can help us better understand the response of networks of neurons under two external inputs.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.