Variational Level-set Formulation for Lithographic Source and Mask Optimization

This paper addresses the contributing factors in lithographic source and mask optimization, namely, the accuracy of the image formation model and the efficiency of the inverse imaging calculations in the optimization framework. A variational level-set formulation is established to incorporate a dist...

Full description

Bibliographic Details
Main Author: Yijiang Shen
Format: Article
Language:English
Published: JommPublish 2018-12-01
Series:Journal of Microelectronic Manufacturing
Subjects:
Online Access:http://www.jommpublish.org/p/19/
id doaj-99083d0d327c45ee8928f4c31a1809a9
record_format Article
spelling doaj-99083d0d327c45ee8928f4c31a1809a92020-11-25T01:48:01ZengJommPublishJournal of Microelectronic Manufacturing2578-37692578-37692018-12-011210.33079/jomm.18010203Variational Level-set Formulation for Lithographic Source and Mask OptimizationYijiang Shen0School of Automation, , Guangdong University of TechnologyThis paper addresses the contributing factors in lithographic source and mask optimization, namely, the accuracy of the image formation model and the efficiency of the inverse imaging calculations in the optimization framework. A variational level-set formulation is established to incorporate a distance regularization term and an external energy. The former maintains a signed-distance profile and the latter minimizes the sum of the mismatches between the printed image and the desired one over all locations. Hence the need of reinitialization is eliminated in a principle way securing a stable level-set evolution and accurate computation with a simpler and more efficient numerical implementation. We employ a vector imaging model together with a stratified media model to describe the vector nature of electromagnetic fields propagating in the coupling image formation. Several strategies including computing the convolution operation with Fast Fourier Transform, the electric-field caching technique and the conjugate gradient method are discussed to ease the computation load and improve convergence.http://www.jommpublish.org/p/19/computaional lithographyvariational level setsource and mask optimizationcoupling image
collection DOAJ
language English
format Article
sources DOAJ
author Yijiang Shen
spellingShingle Yijiang Shen
Variational Level-set Formulation for Lithographic Source and Mask Optimization
Journal of Microelectronic Manufacturing
computaional lithography
variational level set
source and mask optimization
coupling image
author_facet Yijiang Shen
author_sort Yijiang Shen
title Variational Level-set Formulation for Lithographic Source and Mask Optimization
title_short Variational Level-set Formulation for Lithographic Source and Mask Optimization
title_full Variational Level-set Formulation for Lithographic Source and Mask Optimization
title_fullStr Variational Level-set Formulation for Lithographic Source and Mask Optimization
title_full_unstemmed Variational Level-set Formulation for Lithographic Source and Mask Optimization
title_sort variational level-set formulation for lithographic source and mask optimization
publisher JommPublish
series Journal of Microelectronic Manufacturing
issn 2578-3769
2578-3769
publishDate 2018-12-01
description This paper addresses the contributing factors in lithographic source and mask optimization, namely, the accuracy of the image formation model and the efficiency of the inverse imaging calculations in the optimization framework. A variational level-set formulation is established to incorporate a distance regularization term and an external energy. The former maintains a signed-distance profile and the latter minimizes the sum of the mismatches between the printed image and the desired one over all locations. Hence the need of reinitialization is eliminated in a principle way securing a stable level-set evolution and accurate computation with a simpler and more efficient numerical implementation. We employ a vector imaging model together with a stratified media model to describe the vector nature of electromagnetic fields propagating in the coupling image formation. Several strategies including computing the convolution operation with Fast Fourier Transform, the electric-field caching technique and the conjugate gradient method are discussed to ease the computation load and improve convergence.
topic computaional lithography
variational level set
source and mask optimization
coupling image
url http://www.jommpublish.org/p/19/
work_keys_str_mv AT yijiangshen variationallevelsetformulationforlithographicsourceandmaskoptimization
_version_ 1725013425466114048