Optoelectronic Reservoir Computing with an On-Chip True-Time-Delay Element

Compact delay elements remain a central challenge in photonic neuromorphic processors. Here, we demonstrate an optoelectronic delayed-feedback reservoir computer that incorporates a foundry-fabricated silicon nitride (Si${}_3$N${}_4$) true-time-delay circuit within its feedback loop. Eight cascaded Archimedean spirals provide a \SI{1.76}{\metre} on-chip optical path and a calculated passive group delay of \SI{11.63}{\nano\second}. At a feedback gain of $G=0.0223$, the system classifies sinusoidal and square waveforms without error (word error rate, WER,$=$,0 across all cross-validation folds), predicts the Mackey–Glass chaotic series with a best-fold normalized mean-square error (NMSE) of $0.0082$, and performs nine-class Japanese Vowels speaker classification with WER,$=$,0.0898. We also introduce a subcarrier phase-encoding method that maps the calculated $0.232\pi$ spiral-to-reference phase contrast onto the measured reservoir states through deliberate aliasing, achieving NMSE,$=$,0.0767 and WER,$=$,0 without increasing the insertion-loss-limited feedback gain. These results show that on-chip propagation delay in Si${}_3$N${}_4$ can operate as a functional component of an optoelectronic reservoir computer and motivate lower-loss, more-integrated implementations.