Ultra-low-loss microfiber-knot resonator photonic processor for cost-effective feedback-free reservoir computing

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Authors: Jianxiang Wen, Yang Fulong, Suhua Wang, Mingyi Gao, Tingyun Wang, Yanhua Luo, Fufei Pang, Nian Fang
Cited by: 1

Abstract

High-performance photonic computing fundamentally demands physical memory units that both low-loss and cost-effective. In this work, four sets of microfiber-knot resonators (MKRs) were fabricated using a three-electrode tapering technique, featuring an insertion loss below 0.2dB and quality factors (Q-factors) ranging from 104 to 105. The devices are subsequently packaged with polydimethylsiloxane (PDMS), maintaining a total loss less than 1.0 dB. Utilizing these packaged MKRs, a feedback-free photonic reservoir computing (FF-PRC) system is constructed. Experimental results demonstrate with the increasing Q-factor increasing, the normalized mean square errors (NMSEs) for the Mackey-Glass and Santa Fe time-series prediction tasks dropped from 0.390 and 0.420 to 0.022 and 0.034, respectively, while the system achieves a classification accuracy of 97.5% on the MNIST dataset. The proposed FF-PRC system, enabled by ultra-low-loss (

Fields of Study & Subjects

Neural Networks and Reservoir Computing Photonic and Optical Devices Optical Network Technologies

Publication details

Publisher
Optica Publishing Group
Publication date
28 March 2026
Document type
Preprint