Optimization of lithography source illumination arrays using diffraction subspaces

Optics Express
Xu MaLu Zhang

Abstract

An efficient and robust lithography illumination optimization (ILO) approach is developed based on subspace compressive sensing (CS) and an lp-norm reconstruction algorithm. Instead of optimizing the source pattern over all its degrees of freedom, the proposed method only optimizes the source pixels in a subspace. The subspace includes the source pixels inducing interference between different diffraction orders of the mask pattern. The ILO is then formulated as an lp-norm (0 < p < 1) inverse reconstruction problem under the sparse representation of the source pattern. The subspace CS method benefits from having a significantly smaller number of optimization variables, thus effectively improving the computation speed. In addition, an lp-norm reconstruction algorithm is used, which is more robust than l1-norm reconstruction algorithms. Based on the simulations at 45nm and 14nm technology nodes, the proposed methods prove to improve the computational efficiency, robustness and imaging performance of current ILO methods based on adaptive CS.

References

Jul 4, 2012·Journal of the Optical Society of America. A, Optics, Image Science, and Vision·Xu MaLisong Dong
Oct 6, 2012·Optics Express·Jia LiEdmund Y Lam
Mar 5, 2013·Journal of the Optical Society of America. A, Optics, Image Science, and Vision·Xu MaGonzalo R Arce
May 15, 2013·Applied Optics·Xu MaGonzalo R Arce
Jul 1, 2014·Optics Express·Zhiyang SongGonzalo R Arce

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