Hotspot Detection Based On Litho-Aware Machine Learning

Aspects of the disclosed technology relate to techniques of hotspot detection. Pinching-type hotspot candidates and bridging-type hotspot candidates are first identified in the layout design based on predetermined criteria. Simulation is then performed to derive aerial image intensity values for a plurality of sites on each of the pinching-type and bridging-type hotspot candidates. Pinching-type hotspots are determined from the pinching-type hotspot candidates based on one or more machine learning models for pinching-type hotspots, and bridging-type hotspots are determined from the bridging-type hotspot candidates based on one or more machine learning models for bridging-type hotspots. The input vector for the machine learning models is the aerial image intensity values for the plurality of sites.