Synchronization and reservoir computing in coupled semiconductor laser networks
Semiconductor laser networks provide a versatile platform for exploring nonlinear dynamics and photonic information processing. In this talk, I will present an experimental study of an all-to-all fiber-coupled network of four semiconductor lasers with optical feedback. First, I will show how frequency detuning influences the synchronization properties of the network. By detuning one laser relative to the remaining nodes, I investigate the evolution of synchronization as a function of frequency mismatch. The experiments reveal chaotic synchronization of sub-nanosecond signals, with pairwise cross-correlations that can reach 0.9 under suitable detuning conditions. Cross-correlation functions expose signatures of the heterogeneous feedback and coupling delays, while RF spectral analysis demonstrates that synchronization is strongly linked to the spectral overlap between the detuned laser and the rest of the network. In the second part of the talk, I will show how the same system can be used as a photonic reservoir computer. The architecture combines physically coupled laser nodes with time-multiplexed virtual nodes embedded in a shared feedback loop. Using a chaotic time-series prediction benchmark task, I evaluate the computational capabilities of the network and compare its performance with equivalent reservoir computing configurations based on independent single-laser systems.
This Annual PhD student seminar will be broadcasted in the following zoom link: https://us06web.zoom.us/j/89466064429?pwd=po9p99eAEYVPaNI8xIIGoOIz0hOqaF.1
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