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2025-12-13
Matrix Square Root Based Differentiable Rcwa Implementation for High-Performance Parallel Computing
By
Progress In Electromagnetics Research C, Vol. 163, 60-72, 2026
Abstract
Rigorous Coupled-Wave Analysis (RCWA) is a semi-analytical method, used to determine the optical response of nanostructures, such as meta-materials. Recently, the ability to combine RCWA with automatic differentiation for optical response optimization has been demonstrated. We seek to build upon this use by attempting to address RCWA's poor performance on parallel computer architecture, stemming from the presence of an eigendecomposition. We do this by outlining an alteration of RCWA, which replaces the eigendecomposition with a matrix square root and matrix exponential evaluation. Furthermore, we demonstrate that these matrix functions can be evaluated using algorithms which are both differentiable and readily evaluated in parallel. Finally, we show that replacing the eigendecomposition with these matrix functions resolves the bottleneck and paves the way for higher-accuracy parameter retrieval using RCWA approaching real-time performance, without compromising stability.
Citation
Frank Van der Ceelen, Yifeng Shao, and Wim M. J. Coene, "Matrix Square Root Based Differentiable Rcwa Implementation for High-Performance Parallel Computing," Progress In Electromagnetics Research C, Vol. 163, 60-72, 2026.
doi:10.2528/PIERC25091202
References

1. Li, Lifeng, "Fourier modal method," Gratings: Theory and Numeric Applications, Second Revisited Edition, 13.1-13.40, E. Popov, ed., Aix Marseille Université, CNRS, Centrale Marseille, Institut Fresnel, 2014.

2. Li, Lifeng, "4. Mathematical reflections on the fourier modal method in grating theory," Mathematical Modeling in Optical Science, 111-139, Frontiers in Applied Mathematics, SIAM, 2001.

3. Moharam, M. G., Drew A. Pommet, Eric B. Grann, and T. K. Gaylord, "Stable implementation of the rigorous coupled-wave analysis for surface-relief gratings: Enhanced transmittance matrix approach," Journal of the Optical Society of America A, Vol. 12, No. 5, 1077-1086, 1995.
doi:10.1364/josaa.12.001077

4. Semenikhin, I., M. Zanuccoli, M. Benzi, V. Vyurkov, E. Sangiorgi, and C. Fiegna, "Computational efficient RCWA method for simulation of thin film solar cells," Optical and Quantum Electronics, Vol. 44, No. 3, 149-154, 2012.
doi:10.1007/s11082-012-9560-5

5. Colburn, Shane and Arka Majumdar, "Inverse design and flexible parameterization of meta-optics using algorithmic differentiation," Communications Physics, Vol. 4, No. 1, 65, 2021.
doi:10.1038/s42005-021-00568-6

6. Sherwin, Stuart, Isvar Cordova, Ryan Miyakawa, Laura Waller, Andrew Neureuther, and Patrick Naulleau, "Quantitative phase retrieval for EUV photomasks," Extreme Ultraviolet (EUV) Lithography XI, Vol. 11323, 281-290, 2020.
doi:10.1117/12.2552967

7. Den Boef, Arie J., "Optical wafer metrology sensors for process-robust CD and overlay control in semiconductor device manufacturing," Surface Topography: Metrology and Properties, Vol. 4, No. 2, 023001, 2016.
doi:10.1088/2051-672x/4/2/023001

8. Amari, Shun-ichi, "Backpropagation and stochastic gradient descent method," Neurocomputing, Vol. 5, No. 4-5, 185-196, 1993.
doi:10.1016/0925-2312(93)90006-o

9. Krizhevsky, Alex, Ilya Sutskever, and Geoffrey E. Hinton, "ImageNet classification with deep convolutional neural networks," Communications of the ACM, Vol. 60, No. 6, 84-90, 2017.
doi:10.1145/3065386

10. Evanschitzky, P., T. V. Nguyen, C. Schwemmer, and A. Erdmann, "Highly parallelized RCWA with optimized eigenvalue problem for efficient simulation of curvilinear mask structures," 40th European Mask and Lithography Conference (EMLC 2025), Vol. 13787, 108-116, Dresden, Germany, 2025.
doi:10.1117/12.3062253

11. Wei, Xvlong and Shuqiang Chen, "Parallel computing for application in rigorous coupled-wave analysis," 2012 Fifth International Symposium on Computational Intelligence and Design, Vol. 2, 186-189, Hangzhou, China, 2012.
doi:10.1109/iscid.2012.198

12. Tong, Jing and Shuqiang Chen, "Computation improvement for the rigorous coupled-wave analysis with GPU," 2012 Fourth International Conference on Computational and Information Sciences, 123-126, Chongqing, China, 2012.
doi:10.1109/iccis.2012.110

13. Giles, Mike, "An extended collection of matrix derivative results for forward and reverse mode algorithmic differentiation," Report No. 08/01, Oxford University Computing Laboratory, Oxford, England, 2008.

14. Li, Jie, Lihua Shi, Yao Ma, Yuzhou Ran, Yicheng Liu, and Jianbao Wang, "Efficient and stable implementation of RCWA for ultrathin multilayer gratings: T-matrix approach without solving eigenvalues," IEEE Antennas and Wireless Propagation Letters, Vol. 20, No. 1, 83-87, 2021.
doi:10.1109/lawp.2020.3041299

15. Xu, Jingxiao and Martin D. B. Charlton, "Highly efficient rigorous coupled-wave analysis implementation without eigensystem calculation," IEEE Access, Vol. 12, 127966-127975, 2024.
doi:10.1109/access.2024.3456798

16. Li, Jie, Jian-Bao Wang, Zheng Sun, Li-Hua Shi, Yao Ma, Qi Zhang, Shang-Chen Fu, Yi-Cheng Liu, and Yu-Zhou Ran, "Efficient rigorous coupled-wave analysis without solving eigenvalues for analyzing one-dimensional ultrathin periodic structures," IEEE Access, Vol. 8, 198131-198138, 2020.
doi:10.1109/access.2020.3034760

17. Rumpf, Raymond C., "Improved formulation of scattering matrices for semi-analytical methods that is consistent with convention," Progress In Electromagnetics Research B, Vol. 35, 241-261, 2011.
doi:10.2528/pierb11083107

18. Gustafson, John L., "Reevaluating Amdahl's law," Communications of the ACM, Vol. 31, No. 5, 532-533, 1988.
doi:10.1145/42411.42415

19. Barkeshli, Kasra and Sina Khorasani, "Periodic structures," Advanced Electromagnetics and Scattering Theory, 329-335, K. Barkeshli and S. Khorasani, eds., Springer, 2015.
doi:10.1007/978-3-319-11547-4

20. Higham, Nicholas J., Functions of Matrices: Theory and Computation, SIAM, 2008.

21. Li, Jie, Lihua Shi, Yao Ma, Zheng Sun, Qi Zhang, Shangchen Fu, Yicheng Liu, Yuzhou Ran, and Jianbao Wang, "Efficient implementation of rigorous coupled-wave analysis for analyzing binary gratings," IEEE Antennas and Wireless Propagation Letters, Vol. 19, No. 12, 2132-2135, 2020.
doi:10.1109/lawp.2020.3024640

22. Li, Jie, Lihua Shi, Dedong Ji, Eng Leong Tan, Qi Lei, Yao Ma, Yuzhou Ran, Yicheng Liu, and Jianbao Wang, "Efficient implementation of fourier modal method for 2-D periodic structures," IEEE Microwave and Wireless Components Letters, Vol. 32, No. 5, 375-378, 2022.
doi:10.1109/lmwc.2021.3139360

23. Kenney, C. S. and A. J. Laub, "A hyperbolic tangent identity and the geometry of Padé sign function iterations," Numerical Algorithms, Vol. 7, No. 2, 111-128, 1994.
doi:10.1007/bf02140677

24. Kenney, C. S. and A. J. Laub, "The matrix sign function," IEEE Transactions on Automatic Control, Vol. 40, No. 8, 1330-1348, 1995.
doi:10.1109/9.402226

25. Kenney, Charles and Alan J. Laub, "Rational iterative methods for the matrix sign function," SIAM Journal on Matrix Analysis and Applications, Vol. 12, No. 2, 273-291, 1991.
doi:10.1137/0612020

26. Denman, Eugene D. and Alex N. Beavers Jr., "The matrix sign function and computations in systems," Applied Mathematics and Computation, Vol. 2, No. 1, 63-94, 1976.
doi:10.1016/0096-3003(76)90020-5

27. Moler, Cleve and Charles Van Loan, "Nineteen dubious ways to compute the exponential of a matrix," SIAM Review, Vol. 20, No. 4, 801-836, 1978.
doi:10.1137/1020098

28. Moler, Cleve and Charles Van Loan, "Nineteen dubious ways to compute the exponential of a matrix, twenty-five years later," SIAM Review, Vol. 45, No. 1, 3-49, 2003.
doi:10.1137/s00361445024180

29. Higham, Nicholas J., "The scaling and squaring method for the matrix exponential revisited," SIAM Journal on Matrix Analysis and Applications, Vol. 26, No. 4, 1179-1193, 2005.
doi:10.1137/04061101x

30. Higham, Nicholas J., "Newton’s method for the matrix square root," Mathematics of Computation, Vol. 46, No. 174, 537-549, 1986.
doi:10.1090/s0025-5718-1986-0829624-5

31. Schott, James R., Matrix Analysis for Statistics, John Wiley & Sons, 2016.
doi:10.2307/2965451

32. Lin, Tsung-Yu and Subhransu Maji, "Improved bilinear pooling with CNNs," ArXiv Preprint ArXiv:1707.06772, 2017.
doi:10.48550/arXiv.1707.06772

33. Al-Mohy, Awad H. and Nicholas J. Higham, "Improved inverse scaling and squaring algorithms for the matrix logarithm," SIAM Journal on Scientific Computing, Vol. 34, No. 4, C153-C169, 2012.
doi:10.1137/110852553

34. Higham, Nicholas J., D. Steven Mackey, Niloufer Mackey, and Françoise Tisseur, "Functions preserving matrix groups and iterations for the matrix square root," SIAM Journal on Matrix Analysis and Applications, Vol. 26, No. 3, 849-877, 2005.
doi:10.1137/s0895479804442218

35. Higham, Nicholas J. and Pythagoras Papadimitriou, "A parallel algorithm for computing the polar decomposition," Parallel Computing, Vol. 20, No. 8, 1161-1173, 1994.
doi:10.1016/0167-8191(94)90073-6

36. Nakatsukasa, Yuji and Nicholas J. Higham, "Stable and efficient spectral divide and conquer algorithms for the symmetric eigenvalue decomposition and the SVD," SIAM Journal on Scientific Computing, Vol. 35, No. 3, A1325-A1349, 2013.
doi:10.1137/120876605

37. Hochbruck, Marlis and Christian Lubich, "On Krylov subspace approximations to the matrix exponential operator," SIAM Journal on Numerical Analysis, Vol. 34, No. 5, 1911-1925, 1997.
doi:10.1137/s0036142995280572

38. Sidje, Roger B. and William J. Stewart, "A numerical study of large sparse matrix exponentials arising in Markov chains," Computational Statistics & Data Analysis, Vol. 29, No. 3, 345-368, 1999.
doi:10.1016/s0167-9473(98)00062-0

39. Hench, John J. and Zdeněk Strakoš, "The RCWA method --- A case study with open questions and perspectives of algebraic computations," Electronic Transactions on Numerical Analysis, Vol. 31, 331-357, 2008.

40. Al-Mohy, Awad H. and Nicholas J. Higham, "A new scaling and squaring algorithm for the matrix exponential," SIAM Journal on Matrix Analysis and Applications, Vol. 31, No. 3, 970-989, 2010.
doi:10.1137/09074721x

41. Li, Lifeng, "Use of Fourier series in the analysis of discontinuous periodic structures," Journal of the Optical Society of America A, Vol. 13, No. 9, 1870-1876, 1996.
doi:10.1364/josaa.13.001870

42. Markidis, Stefano, Steven Wei Der Chien, Erwin Laure, Ivy Bo Peng, and Jeffrey S. Vetter, "Nvidia tensor core programmability, performance & precision," 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 522-531, Vancouver, BC, Canada, 2018.
doi:10.1109/ipdpsw.2018.00091

43. Kingma, Diederik P. and Jimmy Ba, "Adam: A method for stochastic optimization," ArXiv Preprint ArXiv:1412.6980, 2014.
doi:10.48550/arXiv.1412.6980

44. Zhu, Ziwei and Changxi Zheng, "Differentiable scattering matrix for optimization of photonic structures," Optics Express, Vol. 28, No. 25, 37773-37787, 2020.
doi:10.1364/oe.409261

45. Redheffer, Raymond, "Difference and functional equations in transmission line theory," Modern Mathematics for the Engineer Second, Vol. 30, No. 3, 282-337, 1959.
doi:10.1107/S056774087400330X

46. Deadman, Edvin, Nicholas J. Higham, and Rui Ralha, "Blocked Schur algorithms for computing the matrix square root," International Workshop on Applied Parallel Computing, 171-182, Springer, Berlin, Heidelberg, 2012.
doi:10.1007/978-3-642-36803-5_12