Abstract:
Methods and systems for detecting defects on a specimen are provided. One system includes a storage medium configured for storing images for a physical version of a specimen generated by an inspection system. At least two dies are formed on the specimen with different values of one or more parameters of a fabrication process performed on the specimen. The system also includes computer subsystem(s) configured for comparing portions of the stored images generated at locations on the specimen at which patterns having the same as-designed characteristics are formed with at least two of the different values. The portions of the stored images that are compared are not constrained by locations of the dies on the specimen, locations of the patterns within the dies, or locations of the patterns on the specimen. The computer subsystem(s) are also configured for detecting defects at the locations based on results of the comparing.
Abstract:
Methods and systems for generating simulated images from design information are provided. One system includes one or more computer subsystems and one or more components executed by the computer subsystem(s), which include a generative model. The generative model includes two or more encoder layers configured for determining features of design information for a specimen. The generative model also includes two or more decoder layers configured for generating one or more simulated images from the determined features. The simulated image(s) illustrate how the design information formed on the specimen appears in one or more actual images of the specimen generated by an imaging system.
Abstract:
Methods and systems for performing diagnostic functions for a deep learning model are provided. One system includes one or more components executed by one or more computer subsystems. The one or more components include a deep learning model configured for determining information from an image generated for a specimen by an imaging tool. The one or more components also include a diagnostic component configured for determining one or more causal portions of the image that resulted in the information being determined and for performing one or more functions based on the determined one or more causal portions of the image.
Abstract:
Methods and systems for generating simulated output for a specimen are provided. One method includes acquiring information for a specimen with one or more computer systems. The information includes at least one of an actual optical image of the specimen, an actual electron beam image of the specimen, and design data for the specimen. The method also includes inputting the information for the specimen into a learning based model. The learning based model is included in one or more components executed by the one or more computer systems. The learning based model is configured for mapping a triangular relationship between optical images, electron beam images, and design data, and the learning based model applies the triangular relationship to the input to thereby generate simulated images for the specimen.
Abstract:
Methods and systems for detecting anomalies in images of a specimen are provided. One system includes one or more computer subsystems configured for acquiring images generated of a specimen by an imaging subsystem. The computer subsystem(s) are also configured for determining one or more characteristics of the acquired images. In addition, the computer subsystem(s) are configured for identifying anomalies in the images based on the one or more determined characteristics without applying a defect detection algorithm to the images or the one or more characteristics of the images.
Abstract:
Methods and systems for generating a high resolution image for a specimen from one or more low resolution images of the specimen are provided. One system includes one or more computer subsystems configured for acquiring one or more low resolution images of a specimen. The system also includes one or more components executed by the one or more computer subsystems. The one or more components include a model that includes one or more first layers configured for generating a representation of the one or more low resolution images. The model also includes one or more second layers configured for generating a high resolution image of the specimen from the representation of the one or more low resolution images.
Abstract:
Universal target based inspection drive metrology includes designing a plurality of universal metrology targets measurable with an inspection tool and measurable with a metrology tool, identifying a plurality of inspectable features within at least one die of a wafer using design data, disposing the plurality of universal targets within the at least one die of the wafer, each universal target being disposed at least proximate to one of the identified inspectable features, inspecting a region containing one or more of the universal targets with an inspection tool, identifying one or more anomalistic universal targets in the inspected region with an inspection tool and, responsive to the identification of one or more anomalistic universal targets in the inspected region, performing one or more metrology processes on the one or more anomalistic universal metrology targets with the metrology tool.
Abstract:
Systems and methods for generating information for use in a wafer inspection process are provided. One method includes acquiring output of an inspection system for die(s) located on wafer(s), combining the output for the die(s) based on within die positions of the output, determining, on a within die position basis, a statistical property of variation in values of characteristic(s) of the combined output, and assigning the within die positions to different groups based on the statistical properties determined for the within die positions. The method also includes storing information for the within die positions and the different groups to which the within die positions are assigned in a storage medium that is accessible to the inspection system for performing the wafer inspection process, which includes applying defect detection parameter(s) to additional output of the inspection system generated for a wafer based on the information thereby detecting defects on the wafer.