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

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 (<0.2dB) MKR, exhibits exceptional low-error and high-accuracy performance in processing complex temporal tasks. This work eliminates the need for external feedback loops in optical computing, offering a standalone, cost-effective, and ultra-low-loss memory unit solution for neuromorphic photonic edge nodes.<p></p>