Massively parallel and programmable photonic differential equation solver
大规模并行可编程光子微分方程求解器
大規模並列かつプログラマブルな光子微分方程式ソルバー
대규모 병렬 및 프로그래밍 가능한 광학 미분 방정식 해결기
Resolver de ecuaciones diferenciales fotónicas masivamente paralelas y programables
Solveur d'équations différentielles photoniques massivement parallèles et programmables
Массивно параллельный и программируемый решатель фотонных дифференциальных уравнений
Jiahao Wang ¹ ², Wen Chen ³, Zhou Zhou ⁴, Dongyu Hu ¹ 5, Zile Li ¹ ², Peng Chen ³, Yan-qing Lu ³, Shuang Zhang ⁶, Cheng-Wei Qiu ⁴, Shaohua Yu ⁷, Guoxing Zheng 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 武汉量子技术研究所
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
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.
