Frequency‐multiplexed optical reservoir computing using a microcomb
Jonathan Cuevas, Yue Hu, Baoqi Shi, Junqiu Liu, Kaoru Minoshima, Naoya Kuse · Nanophotonics · 2025
Abstract Optical reservoir computing (ORC) promises fast, energy‐efficient temporal inference by harnessing the rich transient dynamics of photonic systems. Yet most ORC demonstrations still depend on fiber delay lines or camera‐based spatial multiplexing, which caps the clock rate at a few tens of MSa/s and complicates monolithic integration. Here we introduce a frequency‐multiplexed ORC whose nodes are the individual modes of a dissipative Kerr‐soliton microcomb generated in a high‐ Q Si 3 N 4 microresonator. The input signal is encoded as a rapid detuning modulation of the pump laser, so the intracavity dynamics of the microcomb provide both the high‐dimensional nonlinear mapping and tens of nanoseconds of memory, while output weighting is realized optically with standard microring arrays. Numerical modeling with 60 comb modes provides a normalized mean‐square error (NMSE) of 0.015 on the Santa Fe chaotic time‐series task at 50 MSa/s and more than a tenfold reduction in symbol‐error rate for nonlinear equalization (NLEQ) at 100 MSa/s. A proof‐of‐concept experiment using 37 measured modes also confirms the concept on the Santa Fe chaotic time‐series and NLEQ benchmarks. Because both the microcomb and weighting network are fabricated by a complementary metal‐oxide semiconductor (CMOS)‐compatible process, the architecture offers a clear path toward compact, energy‐efficient photonic processors operating at greater than 1 GSa/s, directly addressing the scalability and speed challenges of nanophotonic ORC.