APPARATUS AND METHOD FOR INFERRING PARAMETERS OF A MODEL OF A MEASUREMENT STRUCTURE FOR A PATTERNING PROCESS
First Claim
1. A method of calibrating parameters of a stack model used to simulate the performance of measurement structures in a patterning process, the method comprising:
- obtaining a stack model used in a simulation of performance of measurement structures used in a patterning process;
obtaining calibration data indicative of performance of the measurement structures in the patterning process, the calibration data being empirical measurements or results of simulations of performance of the measurement structures;
after obtaining the calibration data, calibrating, by a processing system, parameters of the stack model by, until a termination condition occurs, repeatedly;
performing the simulation of performance of measurement structures using a candidate stack model having candidate-model parameters;
approximating the simulation over a range of candidate stack models, based on a result of the simulation, with a surrogate function, wherein the surrogate function;
takes as an input candidate stack models having candidate-model parameters, andoutputs a measure of fitness and/or a measure of uncertainty about fitness, wherein fitness is indicative of differences between approximated simulation results based on an input candidate stack model and the obtained calibration data; and
selecting a new candidate model based on the measure of fitness and/or measure of uncertainty about fitness.
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Abstract
A process of calibrating parameters of a stack model used to simulate the performance of measurement structures in a patterning process, the process including: obtaining a stack model used in a simulation of performance of measurement structures; obtaining calibration data indicative of performance of the measurement structures; calibrating parameters of the model by, until a termination condition occurs, repeatedly: simulating performance of the measurement structures with the simulation using a candidate model; approximating the simulation, based on a result of the simulation, with a surrogate function; and selecting a new candidate model based on the approximation.
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Citations
20 Claims
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1. A method of calibrating parameters of a stack model used to simulate the performance of measurement structures in a patterning process, the method comprising:
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obtaining a stack model used in a simulation of performance of measurement structures used in a patterning process; obtaining calibration data indicative of performance of the measurement structures in the patterning process, the calibration data being empirical measurements or results of simulations of performance of the measurement structures; after obtaining the calibration data, calibrating, by a processing system, parameters of the stack model by, until a termination condition occurs, repeatedly; performing the simulation of performance of measurement structures using a candidate stack model having candidate-model parameters; approximating the simulation over a range of candidate stack models, based on a result of the simulation, with a surrogate function, wherein the surrogate function; takes as an input candidate stack models having candidate-model parameters, and outputs a measure of fitness and/or a measure of uncertainty about fitness, wherein fitness is indicative of differences between approximated simulation results based on an input candidate stack model and the obtained calibration data; and selecting a new candidate model based on the measure of fitness and/or measure of uncertainty about fitness. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18)
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19. A system, comprising:
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one or more processors; and memory storing instructions that when executed by at least some of the processors effectuate operations comprising; obtaining a stack model used in a simulation of performance of measurement structures used in a patterning process; obtaining calibration data indicative of performance of the measurement structures in the patterning process, the calibration data being empirical measurements or results of simulations of performance of the measurement structures; after obtaining the calibration data, calibrating parameters of the stack model by, until a termination condition occurs, repeatedly; performing simulation of the performance of the measurement structures using a candidate stack model having candidate-model parameters; approximating the simulation over a range of candidate stack models, based on a result of the simulation, with a surrogate function, wherein the surrogate function; takes as an input candidate stack models having candidate-model parameters, and outputs a measure of fitness and/or a measure of uncertainty about fitness, wherein fitness is indicative of differences between approximated simulation results based on input candidate stack models and the obtained calibration data; and selecting a new candidate model based on the measures of fitness and/or measures of uncertainty about fitness; and storing the new candidate model parameters associated with the new candidate model as calibrated parameters of the stack model in memory.
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20. A method of calibrating parameters of a stack model used to simulate the performance of measurement structures for a patterning process, the method comprising:
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obtaining a stack model used in a simulation of the performance of the measurement structures; obtaining calibration data indicative of performance of the measurement structures in the patterning process, the calibration data being empirical measurements or results of simulations of performance of the measurement structures; after obtaining the calibration data, calibrating, by a processing system, parameters of the stack model by, until a termination condition occurs, repeatedly; a) simulating performance of the measurement structures based on a candidate stack model having candidate-model parameters; b) approximating the simulated performance over a range of candidate stack models, based on evaluation of a surrogate function mapping the candidate-model parameters to a measure of fitness and/or a measure of uncertainty about fitness, wherein the fitness is indicative of a difference between the approximated simulated performance and the calibration data; c) selecting a new candidate stack model based on the fitness and/or uncertainty about the fitness; d) go back to a), wherein the performance is simulated based on the new candidate stack model having new candidate model parameters.
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Specification