activity
20242026
collaborators

6 papers

physics.optics2026

Programmable electro-optic frequency comb empowers integrated parallel convolution processing

Jinze He, Junzhe Qiang, Yiying Dong +11

Integrated photonic convolution processors make optical neural networks (ONNs) a transformative solution for artificial intelligence applications such as machine vision. To enhance…

quant-ph2026

Quantum photonic frequency processor on thin-film lithium niobate

Ran Yang, Wei Zhou, Dong-Jie Guo +11

The rapid development of photonic quantum information processing necessitates precise and programmable control over optical frequency, a capability critical not only for achieving…

physics.optics2026

Precise and Robust Domain Engineering Based on Faraday Cage Effect for Thin-film Lithium Niobate Photonics

Yanqun Wang, Furong Zhong, Lin Liu +4

Thin-film lithium niobate (TFLN) waveguides are promising for efficient second-harmonic generation (SHG) owing to their strong optical confinement and large second-order nonlineari…

physics.optics2025

On-chip real-time detection of optical frequency variations with ultrahigh resolution using the sine-cosine encoder approach

X. Steve Yao, Yulong Yang, Xiaosong Ma +6

Real-time measurement of optical frequency variations (OFVs) is crucial for various applications including laser frequency control, optical computing, and optical sensing. Traditio…

cs.ET2025

Roadmap on Neuromorphic Photonics

Daniel Brunner, Bhavin J. Shastri, Mohammed A. Al Qadasi +147

This roadmap consolidates recent advances while exploring emerging applications, reflecting the remarkable diversity of hardware platforms, neuromorphic concepts, and implementatio…

physics.optics2024

120 GOPS Photonic Tensor Core in Thin-film Lithium Niobate for Inference and in-situ Training

Zhongjin Lin, Bhavin J. Shastri, Shangxuan Yu +27

Photonics offers a transformative approach to artificial intelligence (AI) and neuromorphic computing by enabling low-latency, high-speed, and energy-efficient computations. Howeve…