3 citations · 7 across the 5 of their papers we have counts for
5 papers
Inverse-designed Photonic Computing Core for Parallel Matrix-vector Multiplication
Kaiyuan Wang, Yunlong Li, Tiange Wu +3
On-chip optical neural networks (ONNs) have recently emerged as an attractive hardware accelerator for deep learning applications, characterized by high computing density, low late…
Fully Tunable On-Chip Meta-Generator for Multidimensional Poincaré Sphere mapping
Jing Luan, Tiange Wu, Shuang Zheng +7
The angular momentum of light can be elegantly mapped onto high-order Poincare spheres, providing a powerful framework for describing structured light beams. Such beams have shown…
Non-volatile Reconfigurable Digital Optical Diffractive Neural Network Based on Phase Change Material
Chu Wu, Jingyu Zhao, Qiaomu Hu +2
Optical diffractive neural networks have triggered extensive research with their low power consumption and high speed in image processing. In this work, we propose a reconfigurable…
High-speed and single-mode FP laser based on parity-time symmetry
Sikang Yang, Jing Luan, Yu Han +5
The ability to manipulate cavity resonant modes is of critical importance in laser physics and applications. By exploiting the parity time (PT) symmetry, we propose and experimenta…
Digitized Adjoint Method for Inverse Design of Digital Nanophotonic Devices
Xinshu Ren, Weijie Chang, Longhui Lu +3
We present a digitized adjoint method for realizing efficient inverse design of "digital" subwavelength nanophotonic devices. We design a single-mode 3-dB power divider and a dual-…