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Photonic reservoir computing with a silica microsphere cavity

Junwei Xu, Tong Zhao, Pengfa Chang, C.-L. Wang, Anbang Wang

2023Optics Letters17 citationsDOI

Abstract

We experimentally demonstrate a photonic reservoir computing (RC) system using a passive silica microsphere cavity. The microsphere cavity exhibits a consistent nonlinear response to the non-return-to-zero signal and the multiple-level signal due to strong interference between numerous whispering gallery modes in the "over-coupling" state. Benefiting from the fact that the long photon lifetime inside the microsphere cavity provides a memory of past inputs, this photonic reservoir does not require a delayed feedback loop. We evaluate the generalization property of the RC system and obtain a correlation coefficient of 0.923. In addition, we obtain a NMSE of 0.06 for the Santa-Fe chaotic time series prediction task and a SER of 0.02 at a SNR of 12 dB for the nonlinear channel equalization task. Moreover, a microsphere cavity with a higher quality factor can provide a larger memory capacity. The application of the silica microsphere cavity as a small-volume passive device in a reservoir furnishes a new avenue for achieving a low-consumption and integrated RC system.

Topics & Concepts

Reservoir computingPhotonicsPhotonic crystalOpticsWhispering-gallery waveMaterials scienceInterference (communication)MicrosphereResonatorSIGNAL (programming language)Nonlinear systemChannel (broadcasting)OptoelectronicsPhysicsComputer scienceTelecommunicationsEngineeringMachine learningProgramming languageQuantum mechanicsRecurrent neural networkArtificial neural networkChemical engineeringNeural Networks and Reservoir ComputingPhotonic and Optical DevicesOptical Network Technologies
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