Photonic neural network chips have been widely studied because of their low power consumption, high speed and large bandwidth. Using amplitude and phase to encode, photonic chips can accelerate complex-valued neural network computations. In this article, a photonic complex-valued neural network (PCNN) chip is designed. The scale of the single-core PCNN chip is limited because of optical losses, and the multicore architecture of the chip is used to improve computing capability. Further, for improving the performance of the PCNN, we propose the transformation layer, which can be implemented by the designed photonic chip to transform real-valued encoding to complex-valued encoding, which has richer information. Compared with real-valued input, the transformation layer can effectively improve the classification accuracy from 93.14% to 97.51% of a 64-dimensional input on the MNIST test set. Finally, we analyze the multicore computation of the PCNN. Compared with the single-core architecture, the multicore architecture can improve the classification accuracy by implementing larger neural networks and has better phase noise robustness. The proposed architecture and algorithms are beneficial to promote the accelerated computing of photonic chips for complex-valued neural networks and are promising for use in many applications, such as image recognition and signal processing.

High-mesa semi-insulating buried heterostructure (SIBH) lasers with InP: Fe have great potential in high-speed and high-power scenarios, but the leakage current problem under high current injections has always limited their application. In order to solve the issue of low output power and low efficiency for high-mesa SIBH lasers, the mechanism of leakage current generation in InP-based semi-insulating (SI) layers at high injection levels was analyzed through numerical simulation. The deterioration of the device performance is due to the hole current-induced electron leakage current, which results from the reduction of the potential barrier and Fe-Zn interdiffusion. Thus, lasers with wide bandgap layers of InAlAs and ZnCdSe were employed for current blocking, the power and wall-plug efficiency of which were improved by more than 36% and 5%, respectively. For the first time, a SIBH laser based on lattice-matched ZnCdSe barrier layers is proposed, which shows good output performance and high reliability. The introduction of the wide bandgap layer in the SIBH structure establishes potential barriers to confine both carrier leakages at high injection levels, which realizes the high-power and high-efficiency operation of the laser.