Curvilinear Optical Proximity Correction via Cardinal Spline

This paper presents a novel curvilinear optical proximity correction (OPC) framework. The proposed approach involves representing mask patterns with control points, which are interconnected through cardinal splines. Mask optimization is achieved by iteratively adjusting these control points, guided...

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Bibliographic Details
Published in:2025 62nd ACM/IEEE Design Automation Conference (DAC) pp. 1 - 7
Main Authors: Zheng, Su, Liang, Xiaoxiao, Yu, Ziyang, Ma, Yuzhe, Yu, Bei, Wong, Martin
Format: Conference Proceeding
Language:English
Published: IEEE 22.06.2025
Subjects:
Adaptive optics
Design automation
Fitting
Layout
Lithography
Optical interconnections
Optimization
Scalability
Splines (mathematics)
Testing
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Summary:This paper presents a novel curvilinear optical proximity correction (OPC) framework. The proposed approach involves representing mask patterns with control points, which are interconnected through cardinal splines. Mask optimization is achieved by iteratively adjusting these control points, guided by lithography simulation. To ensure compliance with mask rule checking (MRC) criteria, we develop comprehensive methods for checking width, space, area, and curvature. Additionally, to match the performance of inverse lithography techniques (ILT), we design algorithms to fit ILT results and resolve MRC violations. Extensive experiments demonstrate the effectiveness of our methodology, highlighting its potential as a viable OPC/ILT alternative.
DOI:10.1109/DAC63849.2025.11133367