MACHINE LEARNING BASED INVERSE OPTICAL PROXIMITY CORRECTION AND PROCESS MODEL CALIBRATION

摘要

Described herein is 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.