Physics-informed neural networks (PINNs) have significant potential for modeling and parameter design in engineering field. While most existing PINNs research focuses on fluid mechanics and ...

We report a novel hybrid InP-Si photonic integration scheme with 3D-nanoprinted couplers, achieving 2.1 dB die-to-die coupling loss over a 100 nm wavelength range.