Effects of cavity nonlinearities and linear losses on silicon microring-based reservoir computing
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2023
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| _version_ | 1866907791623454720 |
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| author | Castro, Bernard J. Giron Peucheret, Christophe Zibar, Darko Da Ros, Francesco |
| author_facet | Castro, Bernard J. Giron Peucheret, Christophe Zibar, Darko Da Ros, Francesco |
| contents | Microring resonators (MRRs) are promising devices for time-delay photonic reservoir computing, but the impact of the different physical effects taking place in the MRRs on the reservoir computing performance is yet to be fully understood. We numerically analyze the impact of linear losses as well as thermo-optic and free-carrier effects relaxation times on the prediction error of the time-series task NARMA-10. We demonstrate the existence of three regions, defined by the input power and the frequency detuning between the optical source and the microring resonance, that reveal the cavity transition from linear to nonlinear regimes. One of these regions offers very low error in time-series prediction under relatively low input power and number of nodes while the other regions either lack nonlinearity or become unstable. This study provides insight into the design of the MRR and the optimization of its physical properties for improving the prediction performance of time-delay reservoir computing. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2310_09433 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Effects of cavity nonlinearities and linear losses on silicon microring-based reservoir computing Castro, Bernard J. Giron Peucheret, Christophe Zibar, Darko Da Ros, Francesco Optics Emerging Technologies Machine Learning Neural and Evolutionary Computing Microring resonators (MRRs) are promising devices for time-delay photonic reservoir computing, but the impact of the different physical effects taking place in the MRRs on the reservoir computing performance is yet to be fully understood. We numerically analyze the impact of linear losses as well as thermo-optic and free-carrier effects relaxation times on the prediction error of the time-series task NARMA-10. We demonstrate the existence of three regions, defined by the input power and the frequency detuning between the optical source and the microring resonance, that reveal the cavity transition from linear to nonlinear regimes. One of these regions offers very low error in time-series prediction under relatively low input power and number of nodes while the other regions either lack nonlinearity or become unstable. This study provides insight into the design of the MRR and the optimization of its physical properties for improving the prediction performance of time-delay reservoir computing. |
| title | Effects of cavity nonlinearities and linear losses on silicon microring-based reservoir computing |
| topic | Optics Emerging Technologies Machine Learning Neural and Evolutionary Computing |
| url | https://arxiv.org/abs/2310.09433 |