Integrated lithium niobate photonic computing circuit based on efficient and high-speed electro-optic conversion
Abstract
Here we show a photonic computing accelerator utilizing a system-level thin-film lithium niobate circuit which overcomes this limitation. Leveraging the strong electro-optic (Pockels) effect and the scalability of this platform, we demonstrate photonic computation at speeds up to 1.36 TOPS while consuming 0.057 pJ/OP. Our system features more than 100 thin-film lithium niobate high-performance components working synergistically, surpassing state-of-the-art systems on this platform. We further demonstrate binary-classification, handwritten-digit classification, and image classification with remarkable accuracy, showcasing our system's capability of executing real algorithms. Finally, we investigate the opportunities offered by combining our system with a hybrid-integrated distributed feedback laser source and a heterogeneous-integrated modified uni-traveling carrier photodiode. Our results illustrate the promise of thin-film lithium niobate as a computational platform, addressing current bottlenecks in both electronic and photonic computation. Its unique properties of high-performance electro-optic weight encoding and conversion, wafer-scale scalability, and compatibility with integrated lasers and detectors, position thin-film lithium niobate photonics as a valuable complement to silicon photonics, with extensions to applications in ultrafast and power-efficient signal processing and ranging.
Cite
@article{arxiv.2411.02734,
title = {Integrated lithium niobate photonic computing circuit based on efficient and high-speed electro-optic conversion},
author = {Yaowen Hu and Yunxiang Song and Xinrui Zhu and Xiangwen Guo and Shengyuan Lu and Qihang Zhang and Lingyan He and C. A. A. Franken and Keith Powell and Hana Warner and Daniel Assumpcao and Dylan Renaud and Ying Wang and Letícia Magalhães and Victoria Rosborough and Amirhassan Shams-Ansari and Xudong Li and Rebecca Cheng and Kevin Luke and Kiyoul Yang and George Barbastathis and Mian Zhang and Di Zhu and Leif Johansson and Andreas Beling and Neil Sinclair and Marko Loncar},
journal= {arXiv preprint arXiv:2411.02734},
year = {2024}
}