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1.发明申请Method and Apparatus for Measuring a Structure on a Substrate, Models for Error Correction, Computer Program Products for Implementing such Methods and Apparatus 有权用于测量基板上的结构的方法和装置，用于误差校正的模型，用于实现这种方法和装置的计算机程序产品公开(公告)号：US20160313653A1
公开(公告)日：2016-10-27
申请号：US15101511
申请日：2014-11-05
Applicant: ASML Netherlands B.V.
Inventor： Martijn Peter Mink , Janne Maria Brok , Irwan Dani Setija
CPC classification number: G03F7/70633 , G01B11/272 , G01B2210/56 , G03F7/705 , G03F7/70625
Abstract: A reconstruction process includes measuring structures formed on a substrate by a lithographic process, determining a reconstruction model for generating modeled patterns, computing and minimizing a multi-variable cost function including model errors. Errors induced by nuisance parameters are modeled based on statistical description of the nuisance parameters' behavior, described by probability density functions. From the statistical description model errors are calculated expressed in terms of average model errors and weighing matrices. These are used to modify the cost function so as to reduce the influence of the nuisance parameters in the reconstruction, without increasing the complexity of the reconstruction model. The nuisance parameters may be parameters of the modeled structure, and/or parameters of an inspection apparatus used in the reconstruction.
Abstract translation: 重建过程包括通过光刻处理测量在衬底上形成的结构，确定用于生成建模图案的重建模型，计算并最小化包括模型误差的多变量成本函数。 基于概率密度函数描述的扰乱参数行为的统计描述，对由扰乱参数引起的误差进行建模。 从统计描述模型计算出的误差是用平均模型误差和称重矩阵表示的。 这些用于修改成本函数，以减少重建中扰动参数的影响，而不会增加重建模型的复杂性。 妨扰参数可以是建模结构的参数，和/或重建中使用的检查装置的参数。
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公开(公告)号：US09772562B2
公开(公告)日：2017-09-26
申请号：US15101511
申请日：2014-11-05
Applicant: ASML Netherlands B.V.
Inventor： Martijn Peter Mink , Janne Maria Brok , Irwan Dani Setija
CPC classification number: G03F7/70633 , G01B11/272 , G01B2210/56 , G03F7/705 , G03F7/70625
Abstract: A reconstruction process includes measuring structures formed on a substrate by a lithographic process, determining a reconstruction model for generating modeled patterns, computing and minimizing a multi-variable cost function including model errors. Errors induced by nuisance parameters are modeled based on statistical description of the nuisance parameters' behavior, described by probability density functions. From the statistical description model errors are calculated expressed in terms of average model errors and weighing matrices. These are used to modify the cost function so as to reduce the influence of the nuisance parameters in the reconstruction, without increasing the complexity of the reconstruction model. The nuisance parameters may be parameters of the modeled structure, and/or parameters of an inspection apparatus used in the reconstruction.
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