Information processing with photonic hardware neural networks
Irene Estébanez completed a double BSc. in Mathematics and Physics at the University of Oviedo in 2017, followed by an MSc. in Physics of Complex Systems, specializing in Photonics, at the University of the Balearic Islands in 2018. Following her master's degree, she pursued a PhD at the same institution focusing on neuromorphic computing. Since 2023, Irene has been a photonic integrated circuit designer at VLC Photonics, where she applies her expertise to design advanced concepts in photonic circuits.
This thesis presents numerical and experimental investigations that validate the use of photonic systems as information processors. The first part of the thesis presents the experimental setup used for information processing. The second part of the thesis takes advantage of the master-slave configuration present in our TDRC to generate faster system responses. The response bandwidth is increased by strong optical injection of the drive laser into the reservoir one. This bandwidth enhancement is proven to speed up the photonic TDRC computation without sacrificing performance. Efficient data recovery in fiber transmission systems is demonstrated in the third part of the thesis. Photonic processing schemes are compared to digital ones. Alternative photonic processing architecture is presented in the last part of the thesis, where wavelength division multiplexing is used instead of the time-multiplexing technique in the TDRC approach. An experimental setup mimicking a tapped delay neural network is implemented experimentally and tested against digital-to-analog conversion and header recognition tasks.
Thesis advisors: Ingo Fischer, Apostolos Argyris
Jury members: Kathy Lüdge, Javier Porte Parera , Nikos Pleros
Presential in the IFISC's seminar room and virtual via zoom.
https://us06web.zoom.us/j/98286706234?pwd=bm1JUFVYcTJkaVl1VU55L0FiWDRIUT09
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