Machine learning based inverse optical proximity correction and process model calibration

Abstract

A method for calibrating a process model and training an inverse process model of a patterning process. The training method includes obtaining a first patterning device pattern from simulation of an inverse lithographic process that predicts a patterning device pattern based on a wafer target layout, receiving wafer data corresponding to a wafer exposed using the first patterning device pattern, and training an inverse process model configured to predict a second patterning device pattern using the wafer data related to the exposed wafer and the first patterning device pattern.

Dependencies are inferred from the claim text.