Optimization based on machine learning
AssigneeASML Netherlands B.V.
InventorXiaofeng Liu
Life of this patent
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Abstract
A method for improving a lithographic process for imaging a portion of a design layout onto a substrate using a lithographic apparatus, the method including: obtaining a first source of the lithographic apparatus; classifying the first source into a class among a plurality of possible classes, based on one or more numerical characteristics of the first source, using a machine learning model, by a computer; determining whether the class is among one or more predetermined classes; only when the class is among the one or more predetermined classes, adjusting one or more source design variables to obtain a second source.
Claims20
A method for improving a lithographic process for imaging a portion of a design layout onto a substrate using a lithographic apparatus, the method comprising:
- obtaining an illumination source that is in one or more predetermined classes among a plurality of possible classes, as determined, based on one or more numerical characteristics of the illumination source, by a machine learning model, the machine learning model developed on illumination source numerical characteristics in order to classify illumination sources;
- and
- optimizing, by a hardware computer system, the illumination source for imaging the portion of the design layout by adjusting one or more illumination source design variables.
A computer program product comprising a non-transitory computer readable medium having instructions therein, the instructions, upon execution by a hardware computer system, configured to cause the hardware computer system to at least:
- obtain an illumination source that is in one or more predetermined classes among a plurality of possible classes, as determined, based on one or more numerical characteristics of the illumination source, by a machine learning model, the machine learning model developed on illumination source numerical characteristics in order to classify illumination sources;
- and
- optimize the illumination source, by adjusting one or more illumination source design variables, for a lithographic process for imaging a portion of a design layout onto a substrate using a lithographic apparatus and the illumination source.
A computer program product comprising a non-transitory computer readable medium having instructions therein, the instructions, upon execution by a hardware computer system, configured to cause the hardware computer system to at least:
- obtain one or more numerical characteristics for each illumination source of a plurality of illumination sources, the illumination sources configured for imaging a portion of a design layout onto a substrate using a lithographic apparatus;
- obtain a designation of each illumination source of the plurality of illumination sources into a class among a plurality of possible classes;
- and
- train a machine learning model based on a training set comprising the one or more numerical characteristics of the illumination sources and the designated classes for the illumination sources, the trained machine learning model configured to classify an illumination source based on one or more illumination source numerical characteristics and the trained machine learning model for optimizing an illumination source, by adjustment of one or more illumination source design variables, for imaging a pattern.
Dependencies are inferred from the claim text.