Abstract: Implementations of the disclosure provide methods for generating an in-die reference for die-to-die defect detection techniques. The inspection methods using in-die reference comprise finding similar blocks of a lithographic mask, the similar blocks are defined by similar CAD information. A comparison distance is selected based on (i) areas of the similar blocks and (ii) spatial relationships between the similar blocks. The similar blocks are aggregated, based on the comparison distance, to provide multiple aggregated areas; and comparable regions of the lithographic mask are defined based on the multiple aggregate blocks. Images of at least some of the comparable regions of the lithographic mask are acquired using an inspection module. The acquired images are compared.

Abstract: Implementations of the disclosure provide methods for generating an in-die reference for die-to-die defect detection techniques. The inspection methods using in-die reference comprise finding similar blocks of a lithographic mask, the similar blocks are defined by similar CAD information. A comparison distance is selected based on (i) areas of the similar blocks and (ii) spatial relationships between the similar blocks. The similar blocks are aggregated, based on the comparison distance, to provide multiple aggregated areas; and comparable regions of the lithographic mask are defined based on the multiple aggregate blocks. Images of at least some of the comparable regions of the lithographic mask are acquired using an inspection module. The acquired images are compared.

Abstract: Inspection apparatus includes an imaging module, which is configured to capture images of defects at different, respective locations on a sample. A processor is coupled to process the images so as to automatically assign respective classifications to the defects, and to autonomously control the imaging module to continue capturing the images responsively to the assigned classifications.

Abstract: Inspection apparatus includes an imaging module, which is configured to capture images of defects at different, respective locations on a sample. A processor is coupled to process the images so as to automatically assign respective classifications to the defects, and to autonomously control the imaging module to continue capturing the images responsively to the assigned classifications.

Abstract: Inspection apparatus includes an imaging module, which is configured to capture images of defects at different, respective locations on a sample. A processor is coupled to process the images so as to automatically assign respective classifications to the defects, and to autonomously control the imaging module to continue capturing the images responsively to the assigned classifications.

Abstract: A method for defect classification includes storing definitions of defect classes in terms of a classification rules in a multi-dimensional feature space. Inspection data associated with defects detected in one or more samples under inspection is received. A plurality of first classification results is generated by applying an automatic classifier to the inspection data based on the definitions, the plurality of first classification results comprising a class label and a corresponding confidence level for a defect. Upon determining that a confidence level for a defect is below a predetermined confidence threshold, a plurality of second classification results are generated by applying at least one inspection modality to the defect. A report is generated comprising a distribution of the defects among the defect classes by combining the plurality of first classification results and the plurality of second classification results.

Abstract: A method for defect classification includes storing, in a computer system, a definition of a region in a feature space. The definition is associated with a class of defects and comprises a kernel function comprising a parameter. The parameter determines a shape of the region. A confidence threshold for automatic classification of at least one defect associated with the class is received. A value of the parameter associated with the confidence threshold is selected. Inspection data for a plurality of defects detected in one or more samples under inspection is received. The plurality of defects for the class are automatically classified using the kernel function and the selected value of the parameter.

Abstract: Inspection apparatus includes an imaging module, which is configured to capture images of defects at different, respective locations on a sample. A processor is coupled to process the images so as to automatically assign respective classifications to the defects, and to autonomously control the imaging module to continue capturing the images responsively to the assigned classifications.

Abstract: A method for defect classification includes storing, in a computer system, a definition of a region in a feature space. The definition is associated with a class of defects and comprises a kernel function comprising a parameter. The parameter determines a shape of the region. A confidence threshold for automatic classification of at least one defect associated with the class is received. A value of the parameter associated with the confidence threshold is selected. Inspection data for a plurality of defects detected in one or more samples under inspection is received. The plurality of defects for the class are automatically classified using the kernel function and the selected value of the parameter.

Abstract: A method for defect classification includes storing definitions of defect classes in terms of a classification rules in a multi-dimensional feature space. Inspection data associated with defects detected in one or more samples under inspection is received. A plurality of first classification results is generated by applying an automatic classifier to the inspection data based on the definitions, the plurality of first classification results comprising a class label and a corresponding confidence level for a defect. Upon determining that a confidence level for a defect is below a predetermined confidence threshold, a plurality of second classification results are generated by applying at least one inspection modality to the defect. A report is generated comprising a distribution of the defects among the defect classes by combining the plurality of first classification results and the plurality of second classification results.

Abstract: A method and system are presented for evaluating a variation of a parameter of a pattern. The method includes processing data indicative of an aerial intensity image of at least a portion of a patterned article, and determining values of a certain functional of the aerial image intensity for predetermined regions within the at least portion of the patterned article. The values of the aerial image intensity functional are indicative of a variation of at least one parameter of the pattern within the at least portion of the patterned article or are indicative of a variation of at least one parameter of a pattern manufactured by utilizing the patterned article.

Abstract: A method, system and a computer program product for evaluating an evaluated pattern of a mask, the method includes: receiving multiple moments that represent an image of the evaluated pattern; wherein a size of information required for representing the multiple moments is substantially smaller than a size of pixel information that form the image of the evaluated pattern; and processing the multiple moments in order to determine at least one shape parameter of the evaluated pattern.

Abstract: A method for characterizing a surface of a sample object, the method including dividing the surface into pixels which are characterized by a parameter variation, and defining blocks of the surface as respective groups of the pixels. The method further includes irradiating the pixels in multiple scans over the surface with radiation having different, respective types of polarization, and detecting returning radiation from the pixels in response to each of the scans. For each scan, respective block signatures of the blocks are constructed, in response to the returning radiation from the group of pixels in each block. Also for each scan, a block signature variation using the respective block signatures of the blocks is determined. In response to the block signature variation, one or more of the types of polarization for use in subsequent examination of a test object are selected.

Abstract: A method and system are presented for evaluating a variation of a parameter of a pattern, the method includes: processing data indicative of an aerial intensity image of at least a portion of a patterned article, and determining values of a certain functional of the aerial image intensity for predetermined regions within said at least portion of the patterned article, said values of the aerial image intensity functional being indicative of a variation of at least one parameter of the pattern within said at least portion of the patterned article or of a variation of at least one parameter of a pattern manufactured by utilizing the patterned article.

Abstract: A method for characterizing a surface of a sample object, the method including dividing the surface into pixels which are characterized by a parameter variation, and defining blocks of the surface as respective groups of the pixels. The method further includes irradiating the pixels in multiple scans over the surface with radiation having different, respective types of polarization, and detecting returning radiation from the pixels in response to each of the scans. For each scan, respective block signatures of the blocks are constructed, in response to the returning radiation from the group of pixels in each block. Also for each scan, a block signature variation using the respective block signatures of the blocks is determined. In response to the block signature variation, one or more of the types of polarization for use in subsequent examination of a test object are selected.

Abstract: A method, system and a computer program product for evaluating an evaluated pattern of a mask, the method includes: receiving multiple moments that represent an image of the evaluated pattern; wherein a size of information required for representing the multiple moments is substantially smaller than a size of pixel information that form the image of the evaluated pattern; and processing the multiple moments in order to determine at least one shape parameter of the evaluated pattern.

Abstract: A method for qualifying printability of a mask, including performing a first inspection of the mask with an optical assembly at a first numerical aperture of collection (NAC) of radiation from the mask, and determining, in response to the first inspection, a first possible defect in the mask and a first location of the first possible defect. The method also includes performing a second inspection of the mask with the optical assembly at a second NAC of radiation from the mask, different from the first NAC, and determining, in response thereto, a second possible defect in the mask and a second location of the second possible defect. The method further includes performing a comparison of the first and second locations, and in response to the comparison, determining that the first and second possible defects represent a real defect if the first location matches the second location.

Abstract: A method for qualifying printability of a mask, including performing a first inspection of the mask with an optical assembly at a first numerical aperture of collection (NAC) of radiation from the mask, and determining, in response to the first inspection, a first possible defect in the mask and a first location of the first possible defect. The method also includes performing a second inspection of the mask with the optical assembly at a second NAC of radiation from the mask, different from the first NAC, and determining, in response thereto, a second possible defect in the mask and a second location of the second possible defect. The method further includes performing a comparison of the first and second locations, and in response to the comparison, determining that the first and second possible defects represent a real defect if the first location matches the second location.

Abstract: A reticle inspection system and method for complete and fast inspection of phase shift mask reticles, both for incoming inspection and for periodic and pre-exposure inspection tool, is employable by facilities such as mask shops as an inspection tool compatible to the mask shop's customers. The inventive system and method detect phase errors in an aerial image by acquiring the image of the phase shift mask under the same optical conditions as the exposure conditions (i.e. wavelength, numerical aperture, sigma, and illumination aperture type). Images are acquired at a positive out-of-focus and a negative out-of-focus, and are compared in order to enhance possible phase error. The term “phase error” refers to the acceptable range of the phase deviation from the programmed 180° on the phase shift mask, by using the exposure system to achieve the image on the photoresist, satisfying the requirements of the wafer specification.

Abstract: A method and apparatus for inspecting isolated features on a reticle is provided wherein the isolated features are analyzed for defects globally as individual, whole features, rather than locally, pixel-by-pixel. In one embodiment, the reticle is imaged to produce pixels having a gray level, and an isolated feature is identified. An energy value for the isolated feature to be inspected is calculated by summing the gray levels of its pixels. A plurality of scatter values for the feature in different directions in the feature is calculated based on the equilibrium center of the feature to produce a unique “signature” for the inspected feature. The energy and scatter values of the inspected feature's signature are then compared with energy and scatter values associated with a corresponding reference feature to determine whether a defect exists in the inspected feature.