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    DYNAMIC REMOVAL OF CORRELATION OF HIGHLY CORRELATED PARAMETERS FOR OPTICAL METROLOGY
    1.
    发明申请
    DYNAMIC REMOVAL OF CORRELATION OF HIGHLY CORRELATED PARAMETERS FOR OPTICAL METROLOGY 审中-公开
    用于光学计量学的高相关参数的相关动态移除

    公开(公告)号：US20140358488A1

    公开(公告)日：2014-12-04

    申请号：US14293221

    申请日：2014-06-02

    申请人： Lie-Quan Lee ,  Leonid Poslavsky ,  Stilian Ivanov Pandev

    发明人： Lie-Quan Lee ,  Leonid Poslavsky ,  Stilian Ivanov Pandev

    IPC分类号： G01N21/25

    CPC分类号： G03F7/70616 ,  G01N21/255 ,  G03F1/44 ,  G03F7/70483 ,  G03F7/70516 ,  G03F7/70625

    摘要： Dynamic removal of correlation of highly-correlated parameters for optical metrology is described. An embodiment of a method includes determining a model of a structure, the model including a set of parameters; performing optical metrology measurement of the structure, including collecting spectra data on a hardware element; during the measurement of the structure, dynamically removing correlation of two or more parameters of the set of parameters, an iteration of the dynamic removal of correlation including: generating a Jacobian matrix of the set of parameters, applying a singular value decomposition of the Jacobian matrix, selecting a subset of the set of parameters, and computing a direction of the parameter search based on the subset of parameters. If the model does not converge, performing one or more additional iterations of the dynamic removal of correlation until the model converges; and if the model does converge, reporting the results of the measurement.

    摘要翻译： 描述了用于光学测量的高度相关参数的相关性的动态去除。 方法的实施例包括确定结构的模型，所述模型包括一组参数; 执行结构的光学测量测量，包括在硬件元件上收集光谱数据; 在结构测量期间，动态地去除该组参数中的两个或多个参数的相关性，相关动态去除的迭代包括：生成该组参数的雅可比矩阵，应用雅可比矩阵的奇异值分解 ，选择参数集合的子集，以及基于参数子集计算参数搜索的方向。 如果模型不收敛，则执行动态去除相关性的一个或多个附加迭代，直到模型收敛; 如果模型收敛，报告测量结果。

    Automatic wavelength or angle pruning for optical metrology
    2.
    发明授权
    Automatic wavelength or angle pruning for optical metrology 有权

    公开(公告)号：US11175589B2

    公开(公告)日：2021-11-16

    申请号：US14293625

    申请日：2014-06-02

    申请人： Lie-Quan Lee ,  Leonid Poslavsky

    发明人： Lie-Quan Lee ,  Leonid Poslavsky

    IPC分类号： G01N21/17 ,  G03F7/20 ,  G01N23/20 ,  G06Q50/04 ,  G06F11/30 ,  G01D21/00 ,  G05B99/00 ,  G06F17/40

    摘要： Automatic wavelength or angle pruning for optical metrology is described. An embodiment of a method for automatic wavelength or angle pruning for optical metrology includes determining a model of a structure including a plurality of parameters; designing and computing a dataset of wavelength-dependent or angle-dependent data for the model; storing the dataset in a computer memory; performing with a processor an analysis of the dataset for the model including applying an outlier detection technology on the dataset, and identifying any data outliers, each data outlier being a wavelength or angle; and, if any data outliers are identified in the analysis of the dataset of the model, removing the wavelengths or angles corresponding to the data outliers from the dataset to generate a modified dataset, and storing the modified dataset in the computer memory.

    AUTOMATIC SELECTION OF SAMPLE VALUES FOR OPTICAL METROLOGY
    4.
    发明申请
    AUTOMATIC SELECTION OF SAMPLE VALUES FOR OPTICAL METROLOGY 审中-公开
    自动选择光学方程的样本值

    公开(公告)号：US20150142395A1

    公开(公告)日：2015-05-21

    申请号：US14542546

    申请日：2014-11-15

    申请人： Meng Cao ,  Leonid Poslavsky ,  Inkyo Kim ,  Lie-Quan Lee

    发明人： Meng Cao ,  Leonid Poslavsky ,  Inkyo Kim ,  Lie-Quan Lee

    IPC分类号： G06F17/50

    CPC分类号： G03F7/70625 ,  G01B11/02 ,  G01B11/0625 ,  G01B11/0641 ,  G01B2210/56 ,  G01N21/211 ,  G01N2021/213

    摘要： Embodiments include automatic selection of sample values for optical metrology. An embodiment of a method includes providing a library parameter space for modeling of a diffracting structure using an optical metrology system; automatically determining by a processing unit a reduced sampling set from the library parameter space, wherein the reduced space is based on one or both of the following recommending a sampling shape based on an expected sample space usage, or recommending a sampling filter based on correlation between two or more parameters of the library parameter space; and generating a library for the optical metrology system using the reduced sampling set.

    摘要翻译： 实施例包括自动选择用于光学测量的样本值。 一种方法的实施例包括使用光学测量系统提供用于对衍射结构进行建模的库参数空间; 由处理单元自动确定来自库参数空间的减少的采样集合，其中减少的空间基于以下中的一个或两个基于预期采样空间使用推荐采样形状，或者基于相关性推荐采样滤波器 库参数空间的两个或多个参数; 并使用减少的采样集生成用于光学测量系统的库。

    LIBRARY GENERATION WITH DERIVATIVES IN OPTICAL METROLOGY
    6.
    发明申请
    LIBRARY GENERATION WITH DERIVATIVES IN OPTICAL METROLOGY 审中-公开
    在光学计量学中具有衍生物的图书馆生成

    公开(公告)号：US20130158957A1

    公开(公告)日：2013-06-20

    申请号：US13610613

    申请日：2012-09-11

    申请人： Lie-Quan Lee ,  Leonid Poslavsky

    发明人： Lie-Quan Lee ,  Leonid Poslavsky

    IPC分类号： G06F17/40 ,  G06F17/50

    CPC分类号： G06F17/5009 ,  G01B11/24 ,  G01B21/04 ,  G01B2210/56 ,  G06F2217/16

    摘要： Methods of library generation with derivatives for optical metrology are described. For example, a method of generating a library for optical metrology includes determining a function of a parameter data set for one or more repeating structures on a semiconductor substrate or wafer. The method also includes determining a first derivative of the function of the parameter data set. The method also includes providing a spectral library based on both the function and the first derivative of the function.

    摘要翻译： 描述了用于光学测量的衍生物的图书馆生成方法。 例如，生成用于光学测量的库的方法包括确定半导体衬底或晶片上的一个或多个重复结构的参数数据集的函数。 该方法还包括确定参数数据集的函数的一阶导数。 该方法还包括基于函数的函数和一阶导数提供谱库。

    AUTOMATIC WAVELENGTH OR ANGLE PRUNING FOR OPTICAL METROLOGY
    8.
    发明申请
    AUTOMATIC WAVELENGTH OR ANGLE PRUNING FOR OPTICAL METROLOGY 审中-公开
    自动波长或角度激光光学计量学

    公开(公告)号：US20140358485A1

    公开(公告)日：2014-12-04

    申请号：US14293625

    申请日：2014-06-02

    申请人： Lie-Quan Lee ,  Leonid Poslavsky

    发明人： Lie-Quan Lee ,  Leonid Poslavsky

    IPC分类号： G01N21/17

    CPC分类号： G03F7/70625 ,  G01D21/00 ,  G01N23/20 ,  G05B99/00 ,  G06F11/30 ,  G06F17/40 ,  G06Q50/04 ,  Y02P90/30

    摘要： Automatic wavelength or angle pruning for optical metrology is described. An embodiment of a method for automatic wavelength or angle pruning for optical metrology includes determining a model of a structure including a plurality of parameters; designing and computing a dataset of wavelength-dependent or angle-dependent data for the model; storing the dataset in a computer memory; performing with a processor an analysis of the dataset for the model including applying an outlier detection technology on the dataset, and identifying any data outliers, each data outlier being a wavelength or angle; and, if any data outliers are identified in the analysis of the dataset of the model, removing the wavelengths or angles corresponding to the data outliers from the dataset to generate a modified dataset, and storing the modified dataset in the computer memory.

    摘要翻译： 描述了用于光学测量的自动波长或角度修剪。 用于光学测量的用于自动波长或角度修剪的方法的实施例包括确定包括多个参数的结构的模型; 设计和计算模型的波长相关或角度相关数据的数据集; 将数据集存储在计算机存储器中; 使用处理器执行对所述模型的数据集的分析，包括在所述数据集上应用异常值检测技术，以及识别任何数据异常值，每个数据异常值是波长或角度; 并且如果在模型数据集的分析中识别出任何数据异常值，则从数据集中去除与数据异常值相对应的波长或角度以产生经修改的数据集，并将修改的数据集存储在计算机存储器中。

    Accurate and fast neural network training for library-based critical dimension (CD) metrology
    9.
    发明授权
    Accurate and fast neural network training for library-based critical dimension (CD) metrology 有权
    基于图书馆的关键维度（CD）计量学的准确快速的神经网络训练

    公开(公告)号：US08577820B2

    公开(公告)日：2013-11-05

    申请号：US13041253

    申请日：2011-03-04

    申请人： Wen Jin ,  Vi Vuong ,  Junwei Bao ,  Lie-Quan Lee ,  Leonid Poslavsky

    发明人： Wen Jin ,  Vi Vuong ,  Junwei Bao ,  Lie-Quan Lee ,  Leonid Poslavsky

    IPC分类号： G06F15/18

    CPC分类号： G06N3/08 ,  G06N3/0454

    摘要： Approaches for accurate neural network training for library-based critical dimension (CD) metrology are described. Approaches for fast neural network training for library-based CD metrology are also described. In an example, a method includes optimizing a threshold for a principal component analysis (PCA) of a spectrum data set to provide a principal component (PC) value, estimating a training target for one or more neural networks, training the one or more neural networks based both on the training target and on the PC value provided from optimizing the threshold for the PCA, and providing a spectral library based on the one or more trained neural networks.

    摘要翻译： 描述了基于图书馆的关键维度（CD）计量学的准确神经网络训练的方法。 还介绍了基于图书馆的CD测量的快速神经网络训练方法。 在一个示例中，方法包括优化频谱数据集的主成分分析（PCA）的阈值以提供主成分（PC）值，估计一个或多个神经网络的训练目标，训练一个或多个神经元 基于训练目标和通过优化PCA的阈值提供的PC值的网络，以及基于一个或多个训练有素的神经网络提供谱库。