Microcomb-driven photonic chip for solving partial differential equations

被引:0
作者
Yuan, Hongyi [1 ,2 ]
Du, Zhuochen [3 ,4 ]
Qi, Huixin [3 ,4 ]
Si, Guoxiang [1 ,2 ]
Lu, Cuicui [1 ,2 ]
Yang, Yan [5 ]
Wang, Ze [3 ,4 ]
Ni, Bo [3 ,4 ,6 ]
Wang, Yufei [3 ,4 ]
Yang, Qi-Fan [3 ,4 ,6 ,7 ]
Hu, Xiaoyong [3 ,4 ,6 ,7 ,8 ]
Gong, Qihuang [3 ,4 ,6 ,7 ,8 ]
机构
[1] Beijing Inst Technol, Ctr Interdisciplinary Sci Opt Quantum, Sch Phys, Beijing, Peoples R China
[2] Minist Educ, Beijing Key Lab Nanophoton & Ultrafine Optoelect S, Key Lab Adv Optoelect Quantum Architecture & Measu, NEMS Integrat, Beijing, Peoples R China
[3] Peking Univ, Beijing Acad Quantum Informat Sci, Nano Optoelect Frontier Ctr Minist Educ, Collaborat Innovat Ctr Quantum Matter,State Key La, Beijing, Peoples R China
[4] Dept Phys, Beijing, Peoples R China
[5] Chinese Acad Sci, Inst Microelect, Beijing, Peoples R China
[6] Peking Univ, Yangtze Delta Inst Optoelect, Nantong, Peoples R China
[7] Shanxi Univ, Collaborat Innovat Ctr Extreme Opt, Taiyuan, Peoples R China
[8] Hefei Natl Lab, Hefei, Peoples R China
来源
ADVANCED PHOTONICS | 2025年 / 7卷 / 01期
基金
中国国家自然科学基金;
关键词
photonic computing; silicon photonics; partial differential equations; INVERSE DESIGN; SUPERCOMPUTER;
D O I
10.1117/1.AP.7.1.016007
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
With the development of the big data era, the need for computation power is dramatically growing, especially for solving partial differential equations (PDEs), because PDEs are often used to describe complex systems and phenomena in both science and engineering. However, it is still a great challenge for on-chip photonic solving of time-evolving PDEs because of the difficulties in big coefficient matrix photonic computing, high accuracy, and error accumulation. We overcome these challenges by realizing a microcomb-driven photonic chip and introducing time-division multiplexing and matrix partition techniques into PDE photonic solving, which can solve PDEs with a large coefficient matrix on a photonic chip with a limited size. Time-evolving PDEs, including the heat equation with the first order of time derivative, the wave equation with the second order of time derivative, and the nonlinear Burgers equation, are solved with an accuracy of up to 97%. Furthermore, the parallel solving of the Poisson equation and Laplace's equation is demonstrated experimentally on a single chip, with an accuracy of 95.9% and 95.8%, respectively. We offer a powerful photonic platform for solving PDEs, which takes a step forward in the application of photonic chips in mathematical problems and will promote the development of on-chip photonic computing.
引用
收藏
页数:12
相关论文
共 71 条
  • [1] Evans L. C., Partial Differential Equations, (2022)
  • [2] Morton K. W., Mayers D. F., Numerical Solution of Partial Differential Equations: An Introduction, (2005)
  • [3] Michalakes J., HPC for weather forecasting, Parallel Algorithms in Computational Science and Engineering, pp. 297-323, (2020)
  • [4] Muller E. H., Scheichl R., Massively parallel solvers for elliptic partial differential equations in numerical weather and climate prediction, Q. J. R. Meteorol. Soc, 140, 685, pp. 2608-2624, (2014)
  • [5] Bethke C. M., Et al., Supercomputer analysis of sedimentary basins, Science, 239, 4837, pp. 261-267, (1988)
  • [6] Moin P., Kim J., Tackling turbulence with supercomputers, Sci. Am, 276, 1, pp. 62-68, (1997)
  • [7] Gutierrez-Milla A., Et al., New high performance computing software for multiphysics simulations of fusion reactors, Fusion Eng. Des, 136, pp. 639-644, (2018)
  • [8] Dean E., Glowinski R., Li C. H., Supercomputer solutions of partial differential equation problems in computational fluid dynamics and in control, Comput. Phys. Commun, 53, 1-3, pp. 401-439, (1989)
  • [9] Yang X.-J., Et al., The TianHe-1A supercomputer: its hardware and software, J. Comput. Sci. Technol, 26, 3, pp. 344-351, (2011)
  • [10] Adiga N. R., Et al., An overview of the BlueGene/L supercomputer, SC'02: Proc. 2002 ACM/IEEE Conf. Supercomput, pp. 60-60, (2002)