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DAC2025顶会

Curvilinear Optical Proximity Correction via Cardinal Spline

Su Zheng, Xiaoxiao Liang, Ziyang Yu, Yuzhe Ma, Bei Yu, Martin D. F. Wong

2025年份
5被引次数

摘要

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.

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