Hidden‐Layer Expansion of Photonic Extreme Learning Machine via Coupled‐Core Multi‐Core Fibres

Fibre‐optic propagation could be harnessed to realize a photonic extreme learning machine (ELM) that accelerates classification tasks. Leveraging fibre non‐linearity and dispersion during propagation is beneficial to realize high‐accuracy photonic ELMs with expanding the hidden layer size. We present a scalable strategy to enlarge the ELM hidden layer size via spatial diversity enhancement by coupled‐core multi‐core fibres (CC‐MCFs). Beyond the spatial parallelism of CC‐MCFs, we transform inter‐core crosstalk (IC‐XT) and stochastic spatial‐mode dispersion (SMD) into computational resources rather than impairments in communications. Temporally‐coded sequences propagation over CC‐MCFs is rigorously emulated via solving coupled nonlinear Schrodinger equations (CNSEs). Through investigating the MNIST handwritten‐digit dataset as a benchmark, we demonstrate that deliberately harnessed IC‐XT and SMD coefficients could boost ELM classification accuracy by 5.72% and 7.20% over SMFs, respectively. Requirements on system SNR and launched optical power are also discussed. We believe the results establish CC‐MCF‐enabled space‐division multiplexing as a promising route toward ultra‐high‐accuracy, hardware‐accelerated photonic ELMs.