[1] Semiconductor industry association. International technology roadmap for semiconductors Washington,[R]. DC: SIA(2015).
[2] Mack C. Fundamental principles of optical lithography[M]. Chichester, UK: John Wiley & Sons, Ltd(2007).
[3] Rosenbluth A E, Bukofsky S J, Hibbs M S et al. Optimum mask and source patterns to print a given shape[J]. Proceedings of SPIE, 4346, 486-502(2001).
[4] Staals F, Andryzhyieuskaya A, Bakker H et al. Advanced wavefront engineering for improved imaging and overlay applications on a 1.35 NA immersion scanner[J]. Proceedings of SPIE, 7973, 79731G(2011).
[5] Fühner T, Evanschitzky P, Erdmann A. Mutual source, mask and projector pupil optimization[J]. Proceedings of SPIE, 8326, 83260I(2012).
[7] Fühner T[D]. Artificial evolution for the optimization of lithographic process conditions Germany: Friedrich-Alexander-Universität Erlangen-Nü, rnberg, 2013.
[8] Pomplun J, Zschiedrich L, Burger S et al. Reduced basis method for source mask optimization[J]. Proceedings of SPIE, 7823, 78230E(2010).
[9] Chang J H C, Chen C C P, Melvin L S. Abbe-PCA-SMO: microlithography source and mask optimization based on Abbe-PCA[J]. Proceedings of SPIE, 7640, 764026(2010).
[10] Mülders T, Domnenko V, Küchler B et al. Simultaneous source-mask optimization: a numerical combining method[J]. Proceedings of SPIE, 7823, 78233X(2010).
[11] Deng Y F, Zou Y, Yoshimoto K et al. Considerations in source-mask optimization for logic applications[J]. Proceedings of SPIE, 7640, 76401J(2010).
[12] Pang L Y, Xiao G M, Tolani V et al. Considering MEEF in inverse lithography technology (ILT) and source mask optimization (SMO)[J]. Proceedings of SPIE, 7122, 71221W(2008).
[13] Yu J C, Yu P C, Chao H Y. Source optimization incorporating margin image average with conjugate gradient method[J]. Proceedings of SPIE, 8326, 83261W(2012).
[14] Fuehner T, Erdmann A, Schnattinger T. Genetic algorithms for geometry optimization in lithographic imaging systems[J]. Proceedings of SPIE, 5558, 29-40(2004).
[16] Li J, Liu S Y, Lam E Y. Efficient source and mask optimization with augmented Lagrangian methods in optical lithography[J]. Optics Express, 21, 8076-8090(2013).
[17] Finders J. The impact of Mask 3D and Resist 3D effects in optical lithography[J]. Proceedings of SPIE, 9052, 905205(2014).
[18] Samy A N, Seltmann R, Kahlenberg F et al. Role of 3D photo-resist simulation for advanced technology nodes[J]. Proceedings of SPIE, 8683, 86831E(2013).
[19] Zuniga C, Deng Y F. Resist toploss and profile modeling for optical proximity correction applications[J]. Nanolithography, MEMS, and MOEMS, 13, 043010(2014).
[20] Fan Y F. Wu C E R, Ren Q, et al. Improving 3D resist profile compact modeling by exploiting 3D resist physical mechanisms[J]. Proceedings of SPIE, 9052, 90520X(2014).
[21] Wu C E R, Chang J, Song H et al. AF printability check with a full-chip 3D resist profile model[J]. Proceedings of SPIE, 8880, 88802D(2013).
[22] Cao Y. New trends in computational lithography-data, algorithm and applications[R]. China: IWAPS(2018).
[23] Poonawala A, Milanfar P. Mask design for optical microlithography: an inverse imaging problem[J]. IEEE Transactions on Image Processing, 16, 774-788(2007).
[24] Li S K, Wang X Z, Bu Y. Robust pixel-based source and mask optimization for inverse lithography[J]. Optics & Laser Technology, 45, 285-293(2013).
[26] Shen Y J, Jia N N, Wong N et al. Robust level-set-based inverse lithography[J]. Optics Express, 19, 5511-5521(2011).
[27] Pati Y C, Ghazanfarian A A, Pease R F. Exploiting structure in fast aerial image computation for integrated circuit patterns[J]. IEEE Transactions on Semiconductor Manufacturing, 10, 62-74(1997).
[29] Zhang J Q, Sanderson A C. JADE: self-adaptive differential evolution with fast and reliable convergence performance. [C]//2007 IEEE Congress on Evolutionary Computation, September 25-28, 2007, Singapore. New York: IEEE, 2251-2258(2007).
[30] Liu P, Zhang Z F, Lan S et al. A full-chip 3D computational lithography framework[J]. Proceedings of SPIE, 8326, 83260A(2012).