MODELING MASK ERRORS USING AERIAL IMAGE SENSITIVITY

摘要

One embodiment of the present invention provides techniques and systems for modeling mask errors based on aerial image sensitivity. During operation, the system can receive an uncalibrated process model which includes a mask error modeling term which is based at least on an aerial image sensitivity to mask modifications which represent mask errors. Next, the system can fit the uncalibrated process model using measured CD data. Note that the mask error modeling term can also be dependent on the local and/or long-range pattern density. In some embodiments, the mask error modeling term can include an edge bias term and a corner rounding term. The edge bias term can be based on the sensitivity of the aerial image intensity to an edge bias, and the corner rounding term can be based on the sensitivity of the aerial image intensity to a corner rounding adjustment.