Level-set-based inverse lithography for mask synthesis using the conjugate gradient and an optimal time step
Inverse mask synthesis is achieved by minimizing a cost function on the difference between the output and desired patterns. Such a minimization problem can be solved by a level-set method where the boundary of the pattern is iteratively evolved. However, this evolution is time-consuming in practice...
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Published in | Journal of Vacuum Science & Technology B: Microelectronics and Nanometer Structures Vol. 31; no. 4 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
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01.07.2013
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Abstract | Inverse mask synthesis is achieved by minimizing a cost function on the difference between the output and desired patterns. Such a minimization problem can be solved by a level-set method where the boundary of the pattern is iteratively evolved. However, this evolution is time-consuming in practice and usually converges to a local minimum. The velocity of the boundary evolution and the size of the evolution step, also known as the descent direction and the step size in optimization theory, have a dramatic influence on the convergence properties. This paper focuses on developing a more efficient algorithm with faster convergence and improved performance such as smaller pattern error, lower mean edge placement error, wider defocus band, and higher normalized image log slope. These improvements are accomplished by employing the conjugate gradient of the cost function as the evolution velocity, and by introducing an optimal time step for each iteration of the boundary evolution. The latter is obtained from an extended Euler time range by using a line search method. The authors present simulations demonstrating the efficacy of these two improvements. |
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AbstractList | Inverse mask synthesis is achieved by minimizing a cost function on the difference between the output and desired patterns. Such a minimization problem can be solved by a level-set method where the boundary of the pattern is iteratively evolved. However, this evolution is time-consuming in practice and usually converges to a local minimum. The velocity of the boundary evolution and the size of the evolution step, also known as the descent direction and the step size in optimization theory, have a dramatic influence on the convergence properties. This paper focuses on developing a more efficient algorithm with faster convergence and improved performance such as smaller pattern error, lower mean edge placement error, wider defocus band, and higher normalized image log slope. These improvements are accomplished by employing the conjugate gradient of the cost function as the evolution velocity, and by introducing an optimal time step for each iteration of the boundary evolution. The latter is obtained from an extended Euler time range by using a line search method. The authors present simulations demonstrating the efficacy of these two improvements. |
Author | Liu, Shiyuan Xia, Qi Lv, Wen Lam, Edmund Y. Wu, Xiaofei Shen, Yijiang |
Author_xml | – sequence: 1 givenname: Wen surname: Lv fullname: Lv, Wen organization: Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China – sequence: 2 givenname: Shiyuan surname: Liu fullname: Liu, Shiyuan email: shyliu@mail.hust.edu.cn organization: State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China – sequence: 3 givenname: Qi surname: Xia fullname: Xia, Qi organization: State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China – sequence: 4 givenname: Xiaofei surname: Wu fullname: Wu, Xiaofei organization: Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong – sequence: 5 givenname: Yijiang surname: Shen fullname: Shen, Yijiang organization: Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong – sequence: 6 givenname: Edmund Y. surname: Lam fullname: Lam, Edmund Y. organization: Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong |
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Keywords | Optical Mask Silicon Chip Photoresist |
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Snippet | Inverse mask synthesis is achieved by minimizing a cost function on the difference between the output and desired patterns. Such a minimization problem can be... |
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Title | Level-set-based inverse lithography for mask synthesis using the conjugate gradient and an optimal time step |
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