Abstract: The presently disclosed subject matter includes a computer system and a computer-implemented method dedicated to utilizing a machine learning model trained to generate synthetic examination output images that reflect variations in tool configurations. By incorporating different priors related to operational parameters during inference, the system ensures that the synthetic images more accurately represent real-world examination outputs of a specific examination tool. These synthetic images can be applied to various applications, including defect detection and tool matching.

Abstract: A method and system for optimizing a metrology algorithm used by an inspection tool for inspecting predetermined sites of a semiconductor wafer during fabrication so as to allow repetitive and consistent inspection for multiple sites of the wafer by both a single inspection tool of a given type using the metrology algorithm and also across a fleet of different inspection tools of the same type using the metrology algorithm. An aggregate loss function is computed from a sum of component loss functions. In one aspect, each component loss function is amplified by a non-linear function that applies a positive gain for in-range measurements and for out-of-range measurements, applies a steep penalty that swamps any cumulative gains associated with other component loss functions. In another aspect, distribution-based metrics are used to measure similarity between two distributions of measurements for multiple locations across two different tools.