(Peer-Reviewed) Massively parallel and programmable photonic differential equation solver
Jiahao Wang 汪嘉豪 ¹ ², Wen Chen 陈闻 ³, Zhou Zhou 周舟 ⁴, Dongyu Hu 胡冬煜 ¹ ⁵, Zile Li 李子乐 ¹ ², Peng Chen 陈鹏 ³, Yan-qing Lu 陆延青 ³, Shuang Zhang 张霜 ⁶, Cheng-Wei Qiu 仇成伟 ⁴, Shaohua Yu 余少华 ⁷, Guoxing Zheng 郑国兴 ¹ ² ⁵
¹ Electronic Information School, Wuhan University, Wuhan 430072, China
中国 武汉 武汉大学电子信息学院
² Peng Cheng Laboratory, Shenzhen 518055, China
中国 深圳 鹏城实验室
³ National Laboratory of Solid State Microstructures, and College of Engineering and Applied Sciences, Nanjing University, Nanjing 210093, China
中国 南京 南京大学现代工程与应用科学学院 固体微结构物理国家重点实验室
⁴ NUS Graduate School and Department of Electrical and Computer Engineering, National University of Singapore, Singapore 119077, Singapore
⁵ Wuhan Institute of Quantum Technology, Wuhan 430206, China
中国 武汉 武汉量子技术研究院
⁶ Department of Physics, University of Hong Kong, Hong Kong 999077, China
中国 香港 香港大学物理系
⁷ Chinese Academy of Engineering, Beijing 100088, China
中国 北京 中国工程院
Opto-Electronic Advances
, 2026-05-15
Abstract
Calculus equations are fundamental mathematical tools, whose numerical solution is crucial. Existing solvers with optical analog computing struggle to simultaneously integrate programmability and parallel processing, thus constraining computational speed and density. Herein, we propose a reconfigurable all-optical platform capable of solving variable-coefficient first-order ordinary differential equations in parallel.
We utilize the electrically tunable liquid crystals (LCs) as computing kernels to address these equations. The solver's applicability to canonical scientific problems, such as heat conduction and resistor-capacitor circuit dynamics, is further showcased with simultaneous solving of 158 equations with only one single forward propagation of light. Experimental results confirm the efficacy of the platform in solving equations in an ultra-fast, reconfigurable, broadband, and parallel manner.
A 4096-element 3D-integrated Si-SiN optical phased array for high-power coherent LiDAR
Han Wang, Weimin Xie, Xin Yan, Jiaqi Li, Youxi Lu, Ping Jiang, Feng Li, Kai Jin, Xu Yang, Jiali Jiang, Keran Deng, Weishuai Chen, Jing Luo, Li Jin, Junbo Feng, Kai Wei
Opto-Electronic Technology
2026-03-20
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Nan Chi, Zhilan Lu, Fujie Li, Haoyu Zhang, Yunkai Wang, Xinyi Liu, Zhiwu Chen, Zhe Feng, Zhuoran Hu, Zhixue He, Ziwei Li, Chao Shen, Junwen Zhang
Opto-Electronic Technology
2026-03-20
Holotomography-driven learning unlocks in-silico staining of single cells in flow cytometry by avoiding fluorescence co-registration
Daniele Pirone, Giusy Giugliano, Michela Schiavo, Annalaura Montella, Martina Mugnano, Vincenza Cerbone, Maddalena Raia, Giulia Scalia Ivana Kurelac, Diego Luis Medina, Lisa Miccio Mario Capasso, Achille Iolascon, Pasquale Memmolo, Pietro Ferraro
Opto-Electronic Science
2026-02-25
