Asml Netherlands B.v.

Other

Xiaofeng Liu

Rafael C Howell

Duan-Fu Stephen Hsu

Jun Ye

Hong M Chen

Luoqi Chen

Hanying Feng

Wei Zhou

Cuiping Zhang

Jianjun Jia

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.

Optimization based on machine learning

A method to improve a lithographic process for imaging a portion of a design layout onto a substrate using a lithographic projection apparatus and for transferring the imaged portion of the design layout to the substrate by an etching process, which method includes: determining a value of at least one evaluation point of the lithographic process for each of a plurality of variations of the etching process; computing a multi-variable cost function of a plurality of design variables that are characteristics of the lithographic process, wherein the multi-variable cost function is a function of deviation from the determined values of the at least one evaluation point; and reconfiguring the characteristics of the lithographic process by adjusting the design variables until a termination condition is satisfied. This method may reduce the need of repeated adjustment to the lithographic process when the etching process varies.

Etch variation tolerant optimization

A method for improving a lithographic process for imaging a portion of a design layout onto a substrate using a lithographic projection apparatus, the method including: calculating a discrete pupil profile based on a desired pupil profile; selecting a discrete change to the discrete pupil profile; and applying the selected discrete change to the discrete pupil profile. The methods according to various embodiments disclosed herein may reduce the computational cost of discrete optimization from O(a) to O(n) wherein a is constant and n is the number of knobs that can generate discrete change in the pupil profile.

Discrete source mask optimization

A method to improve a lithographic process for imaging a portion of a design layout onto a substrate using a lithographic projection apparatus having an illumination system and projection optics, the method including: obtaining an illumination source shape and a mask defocus value; optimizing a dose of the lithographic process; and optimizing the portion of the design layout for each of a plurality of slit positions of the illumination source.

Flows of optimization for lithographic processes

The present disclosure provides a computer-implemented method for analyzing variants from a plurality of nucleic acid sequence reads using a computation pipeline, which comprises a module depending on a location-dependent parameter. The method comprises executing on a processor the steps of: receiving a plurality of nucleic acid sequence reads comprising at least a first nucleic acid sequence read and a second nucleic acid sequence read; mapping the first nucleic acid sequence read and the second nucleic acid sequence read to a first location and a second location in a genome, respectively; setting a first value and a second value for the location-dependent parameter on the basis of the first location and the second location in the genome, respectively; passing the first nucleic acid sequence read and the second nucleic acid sequence read through the module using the first value and the second value, respectively; and generating a variant call.

Computation pipeline of location-dependent variant calls

The present disclosure provides a computer-implemented method of analyzing variants from a plurality of nucleic acid sequence reads. The method uses a computation pipeline having at least one invariable module and at least one variable module, wherein the variable module depends on a variable parameter. The method includes executing on a processor the steps of receiving the plurality of nucleic acid sequence reads; setting a plurality of values for the variable parameter; passing the plurality of the nucleic acid sequence reads through the invariable module to generate an intermediate output; passing the intermediate output through the variable module for multiple rounds, each round using one of the variable values; and generating a plurality of variant calls.

Computation pipeline of single-pass multiple variant calls

A method to improve a lithographic process for imaging a portion of a design layout onto a substrate using a lithographic projection apparatus, the method including: computing a multi-variable cost function of a plurality of design variables that are characteristics of the lithographic process, and reconfiguring the characteristics of the lithographic process by adjusting the design variables until a predefined termination condition is satisfied. The multi-variable cost function may be a function of one or more pattern shift errors. Reconfiguration of the characteristics may be under one or more constraints on the one or more pattern shift errors.

Pattern placement error aware optimization

Disclosed herein is a computer-implemented method to improve a lithographic process for imaging a portion of a design layout onto a substrate using a lithographic projection apparatus and for transferring the imaged portion of the design layout to the substrate by an etching process, which includes the following steps: determining a value of at least one evaluation point of the lithographic process for each of a plurality of variations of the etching process; computing a multi-variable cost function of a plurality of design variables that are characteristics of the lithographic process, wherein the multi-variable cost function is a function of deviation from the determined values of the at least one evaluation point; and reconfiguring the characteristics of the lithographic process by adjusting the design variables until a termination condition is satisfied. This method may reduce the need of repeated adjustment to the lithographic process when the etching process varies.

A computer-implemented method for obtaining values of one or more design variables of one or more design rules for a pattern transfer process comprising a lithographic projection apparatus, the method comprising: simultaneously optimizing one or more design variables of the pattern transfer process and the one or more design variables of the one or more design rules. The optimizing comprises evaluating a cost function that measures a metric characteristic of the pattern transfer process, the cost function being a function of one or more design variables of the pattern transfer process and one or more design variables of the one or more design rules.

Rule and lithographic process co-optimization

Described herein is a method for a lithographic process for imaging a portion of a design layout onto a substrate using a lithographic imaging apparatus, the lithographic process having a plurality of design variables, the method comprising: calculating a gradient of each of a plurality of evaluation points or patterns of the lithographic process, with respect to at least one of the design variables; and selecting a subset of evaluation points from the plurality of evaluation points or patterns based on the gradient.

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Campbell, CA, United States of America

Xiaofeng Liu