Abstract: Systems and methods for detecting defects on a wafer are provided. One method includes generating output for a wafer by scanning the wafer with an inspection system using first and second optical states of the inspection system. The first and second optical states are defined by different values for at least one optical parameter of the inspection system. The method also includes generating first image data for the wafer using the output generated using the first optical state and second image data for the wafer using the output generated using the second optical state. In addition, the method includes combining the first image data and the second image data corresponding to substantially the same locations on the wafer thereby creating additional image data for the wafer. The method further includes detecting defects on the wafer using the additional image data.

Abstract: Methods and systems for detecting and classifying defects on a specimen are provided. One system includes one or more components executed by one or more computer subsystems. The one or more components include a neural network configured for detecting defects on a specimen and classifying the defects detected on the specimen. The neural network includes a first portion configured for determining features of images of the specimen generated by an imaging subsystem. The neural network also includes a second portion configured for detecting defects on the specimen based on the determined features of the images and classifying the defects detected on the specimen based on the determined features of the images.

Abstract: Methods and systems for training a neural network for defect detection in low resolution images are provided. One system includes an inspection tool that includes high and low resolution imaging subsystems and one or more components that include a high resolution neural network and a low resolution neural network. Computer subsystem(s) of the system are configured for generating a training set of defect images. At least one of the defect images is generated synthetically by the high resolution neural network using an image generated by the high resolution imaging subsystem. The computer subsystem(s) are also configured for training the low resolution neural network using the training set of defect images as input. In addition, the computer subsystem(s) are configured for detecting defects on another specimen by inputting the images generated for the other specimen by the low resolution imaging subsystem into the trained low resolution neural network.

Abstract: Systems and methods for determining information for defects on a wafer are provided. One system includes an illumination subsystem configured to direct light having one or more illumination wavelengths to a wafer. The one or more illumination wavelengths are selected to cause fluorescence from one or more materials on the wafer without causing fluorescence from one or more other materials on the wafer. The system also includes a detection subsystem configured to detect only the fluorescence from the one or more materials or to detect non-fluorescent light from the wafer without detecting the fluorescence from the one or more materials. In addition, the system includes a computer subsystem configured to determine information for defects on the wafer using output generated by the detection subsystem responsive to the detected fluorescence or the detected non-fluorescent light.

Abstract: Systems configured to inspect a wafer are provided. One system includes an illumination subsystem configured to direct pulses of light to an area on a wafer; a scanning subsystem configured to scan the pulses of light across the wafer; a collection subsystem configured to image pulses of light scattered from the area on the wafer to a sensor, wherein the sensor is configured to integrate a number of the pulses of scattered light that is fewer than a number of the pulses of scattered light that can be imaged on the entire area of the sensor, and wherein the sensor is configured to generate output responsive to the integrated pulses of scattered light; and a computer subsystem configured to detect defects on the wafer using the output generated by the sensor.

Abstract: Methods and systems for determining parameter(s) of a process to be performed on a specimen are provided. One system includes one or more computer subsystems configured for determining an area of a defect detected on a specimen. The computer subsystem(s) are also configured for correlating the area of the defect with information for a design for the specimen and determining a spatial relationship between the area of the defect and the information for the design based on results of the correlating. In addition, the computer subsystem(s) are configured for automatically generating a region of interest to be measured during a process performed for the specimen with a measurement subsystem based on the spatial relationship.

Abstract: Methods and systems for determining one or more characteristics for defects detected on a specimen are provided. One system includes one or more computer subsystems configured for identifying a first defect that was detected on a specimen by an inspection system with a first mode but was not detected with one or more other modes. The computer subsystem(s) are also configured for acquiring, from the storage medium, one or more images generated with the one or more other modes at a location on the specimen corresponding to the first defect. In addition, the computer subsystem(s) are configured for determining one or more characteristics of the acquired one or more images and determining one or more characteristics of the first defect based on the one or more characteristics of the acquired one or more images.

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 detecting defects on a wafer using adaptive local thresholding and color filtering are provided. One method includes determining local statistics of pixels in output for a wafer generated using an inspection system, determining which of the pixels are outliers based on the local statistics, and comparing the outliers to the pixels surrounding the outliers to identify the outliers that do not belong to a cluster of outliers as defect candidates. The method also includes determining a value for a difference in color between the pixels of the defect candidates and the pixels surrounding the defect candidates. The method further includes identifying the defect candidates that have a value for the difference in color greater than or equal to a predetermined value as nuisance defects and the defect candidates that have a value for the difference in color less than the predetermined value as real defects.

Abstract: Methods and systems for detecting defects on a specimen are provided. One system includes one or more computer subsystems configured for acquiring images generated by an imaging subsystem at multiple instances of a pattern of interest (POI) within a die formed on the specimen. The multiple instances include two or more instances that are located at aperiodic locations within the die. The computer subsystem(s) are also configured for generating a POI reference image from two or more of the images generated at the multiple instances of the POI within the die. The computer subsystem(s) are further configured for comparing the images generated at the multiple instances of the POI within the die to the POI reference image and detecting defects in the multiple instances of the POI based on results of the comparing.

Abstract: Methods and systems for generating a simulated image from an input image are provided. One system includes one or more computer subsystems and one or more components executed by the one or more computer subsystems. The one or more components include a neural network that includes two or more encoder layers configured for determining features of an image for a specimen. The neural network also includes two or more decoder layers configured for generating one or more simulated images from the determined features. The neural network does not include a fully connected layer thereby eliminating constraints on size of the image input to the two or more encoder layers.

Abstract: Systems and methods for detecting defects on a reticle are provided. One system includes computer subsystem(s) that include one or more image processing components that acquire images generated by an inspection subsystem for a wafer, a main user interface component that provides information generated for the wafer and the reticle to a user and receives instructions from the user, and an interface component that provides an interface between the one or more image processing components and the main user interface. Unlike currently used systems, the one or more image processing components are configured for performing repeater defect detection by applying a repeater defect detection algorithm to the images acquired by the one or more image processing components, and the repeater defect detection algorithm is configured to detect defects on the wafer using a hot threshold and to identify the defects that are repeater defects.

Abstract: Methods and systems for detecting defects in patterns formed on a specimen are provided. One system includes one or more components executed by one or more computer subsystems, and the component(s) include first and second learning based models. The first learning based model generates simulated contours for the patterns based on a design for the specimen, and the simulated contours are expected contours of a defect free version of the patterns in images of the specimen generated by an imaging subsystem. The second learning based model is configured for generating actual contours for the patterns in at least one acquired image of the patterns formed on the specimen. The computer subsystem(s) are configured for comparing the actual contours to the simulated contours and detecting defects in the patterns formed on the specimen based on results of the comparing.

Abstract: Methods and systems for transforming positions of defects detected on a wafer are provided. One method includes aligning output of an inspection subsystem for a first frame in a first swath in a first die in a first instance of a multi-die reticle printed on the wafer to the output for corresponding frames, swaths, and dies in other reticle instances printed on the wafer. The method also includes determining different swath coordinate offsets for each of the frames, respectively, in the other reticle instances based on the swath coordinates of the output for the frames and the corresponding frames aligned thereto and applying one of the different swath coordinate offsets to the swath coordinates reported for the defects based on the other reticle instances in which they are detected thereby transforming the swath coordinates for the defects from swath coordinates in the other reticle instances to the first reticle instance.

Abstract: Methods and systems for performing one or more functions for a specimen using output simulated for the specimen are provided. One system includes one or more computer subsystems configured for acquiring output generated for a specimen by one or more detectors included in a tool configured to perform a process on the specimen. The system also includes one or more components executed by the one or more computer subsystems. The one or more components include a learning based model configured for performing one or more first functions using the acquired output as input to thereby generate simulated output for the specimen. The one or more computer subsystems are also configured for performing one or more second functions for the specimen using the simulated output.

Abstract: Methods and systems for determining characteristic(s) of patterns of interest (POIs) are provided. One system is configured to acquire output of an inspection system generated at the POI instances without detecting defects at the POI instances. The output is then used to generate a selection of the POI instances. The system then acquires output from an output acquisition subsystem for the selected POI instances. The system also determines characteristic(s) of the POI using the output acquired from the output acquisition subsystem.

Abstract: Methods and systems for training a neural network are provided. One system includes one or more components executed by one or more computer subsystems. The one or more components include a neural network configured for determining inverted features of input images in a training set for a specimen input to the neural network, a forward physical model configured for reconstructing the input images from the inverted features thereby generating a set of output images corresponding to the input images in the training set, and a residue layer configured for determining differences between the input images in the training set and their corresponding output images in the set. The one or more computer subsystems are configured for altering one or more parameters of the neural network based on the determined differences thereby training the neural network.

Abstract: Systems and methods for performing one or more processes on a specimen are provided. One system includes a deposition module incorporated into an existing tool configured to perform an inspection and/or metrology process. The deposition module is configured to deposit one or more materials on a specimen prior to the inspection and/or metrology process performed on the specimen. In some embodiments, the system also includes a stripping module incorporated into the existing tool, and the stripping module is configured to remove material(s) from the specimen subsequent to the inspection and/or metrology process performed on the specimen. The existing tool includes an illumination subsystem configured to direct light having one or more illumination wavelengths to the specimen; a detection subsystem configured to detect light from the specimen; and a computer subsystem configured to determine information for the specimen using output generated by the detection subsystem responsive to the detected light.

Abstract: Methods and systems for monitoring a non-defect related characteristic of a patterned wafer are provided. One computer-implemented method includes generating output responsive to light from a patterned wafer using an inspection system. The method also includes determining differences between a value of a non-defect related characteristic of the patterned wafer and a known value of the non-defect related characteristic based on differences between one or more attributes of the output and one or more attributes of other output of the inspection system for a different patterned wafer having the known value of the non-defect related characteristic.

Abstract: Systems and methods for determining information for defects on a wafer are provided. One system includes an illumination subsystem configured to direct light having one or more illumination wavelengths to a wafer. The one or more illumination wavelengths are selected to cause fluorescence from one or more materials on the wafer without causing fluorescence from one or more other materials on the wafer. The system also includes a detection subsystem configured to detect only the fluorescence from the one or more materials or to detect non-fluorescent light from the wafer without detecting the fluorescence from the one or more materials. In addition, the system includes a computer subsystem configured to determine information for defects on the wafer using output generated by the detection subsystem responsive to the detected fluorescence or the detected non-fluorescent light.