Optical neuromorphic computing based on chaotic frequency combs in nonlinear microresonators
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866929690024869888 |
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| author | Shishavan, Negar Shaabani Manuylovich, Egor Kamalian-Kopae, Morteza Perego, Auro M. |
| author_facet | Shishavan, Negar Shaabani Manuylovich, Egor Kamalian-Kopae, Morteza Perego, Auro M. |
| contents | In this work we present a novel implementation of delay line free reservoir computing based on state-of-the-art photonic technologies, which exploits chaotic optical frequency comb formation in optical microresonator as the nonlinear reservoir. Our solution leverages the high resonator Q-factor both for memory and for enhancing high dimensional nonlinear mapping of input symbols. We numerically demonstrate the accurate prediction of about one thousand symbols in chaotic time series without the need of dedicated optimisation for specific tasks. Our results will enable design of optical neuromorphic computing architectures combining on-chip integrability, low footprint, high speed and low power consumption. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_17113 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Optical neuromorphic computing based on chaotic frequency combs in nonlinear microresonators Shishavan, Negar Shaabani Manuylovich, Egor Kamalian-Kopae, Morteza Perego, Auro M. Optics In this work we present a novel implementation of delay line free reservoir computing based on state-of-the-art photonic technologies, which exploits chaotic optical frequency comb formation in optical microresonator as the nonlinear reservoir. Our solution leverages the high resonator Q-factor both for memory and for enhancing high dimensional nonlinear mapping of input symbols. We numerically demonstrate the accurate prediction of about one thousand symbols in chaotic time series without the need of dedicated optimisation for specific tasks. Our results will enable design of optical neuromorphic computing architectures combining on-chip integrability, low footprint, high speed and low power consumption. |
| title | Optical neuromorphic computing based on chaotic frequency combs in nonlinear microresonators |
| topic | Optics |
| url | https://arxiv.org/abs/2501.17113 |