Abstract:
Methods for generating a standard reference die for use in a die to standard reference die inspection and methods for inspecting a wafer are provided. One computer-implemented method for generating a standard reference die for use in a die to standard reference die inspection includes acquiring output of an inspection system for a centrally located die on a wafer and one or more dies located on the wafer. The method also includes combining the output for the centrally located die and the one or more dies based on within die positions of the output. In addition, the method includes generating the standard reference die based on results of the combining step.
Abstract:
Methods for detecting and classifying defects on a reticle are provided. One method includes acquiring images of the reticle at first and second conditions during inspection of the reticle. The first condition is different than the second condition. The method also includes detecting the defects on the reticle using one or more of the images acquired at the first condition. In addition, the method includes classifying an importance of the defects detected on the reticle using one or more of the images acquired at the second condition. The detecting and classifying steps are performed substantially simultaneously during the inspection.
Abstract:
A method for modeling samples includes the use of control points to define lines profiles and other geometric shapes. Each control point used within a model influences a shape within the model. Typically, the control points are used in a connect-the-dots fashion where a set of dots defines the outline or profile of a shape. The layers within the sample are typically modeled independently of the shape defined using the control points. The overall result is to minimize the number of parameters used to model shapes while maintaining the accuracy of the resulting scatterometry models.
Abstract:
An apparatus for scatterometry measurements is disclosed. The apparatus includes a modulated pump source for exciting the sample. A separate probe beam is directed to interact with the sample and the modulated optical response is measured. The measured data is subjected to a scatterometry analysis in order to evaluate geometrical sample features that induce light scattering.
Abstract:
A method and apparatus for enhancing image contrast between resist-covered and bare silicon regions of a wafer, applicable to Edge Bead Removal inspection. The wafer is illuminated separately by s-polarized light and p-polarized light impinging at near the Brewster angle of silicon or resist, and an image difference between the reflected s-polarized light and the reflected p-polarized light is derived.
Abstract:
Methods and systems for determining parameter(s) of a metrology process to be performed on a specimen are provided. One system includes one or more computer subsystems configured for automatically generating regions of interest (ROIs) to be measured during a metrology process performed for the specimen with the measurement subsystem based on a design for the specimen. The computer subsystem(s) are also configured for automatically determining parameter(s) of measurement(s) performed in first and second subsets of the ROIs during the metrology process with the measurement subsystem based on portions of the design for the specimen located in the first and second subsets of the ROIs, respectively. The parameter(s) of the measurement(s) performed in the first subset are determined separately and independently of the parameter(s) of the measurement(s) performed in the second subset.
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:
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.