Automatic selection of sample values for optical metrology

1. A method comprising:

providing a first library parameter space comprising a populated parameter space of a plurality of parameters for modeling of a diffracting structure using an optical metrology system;

automatically reducing, by a processing unit, the populated parameter space to produce a second library parameter space comprising a reduced populated parameter space of the plurality of parameters, wherein the reduction of the populated parameter space is based on the following:

recommending a sampling filter that includes 1) identifying correlations between two or more parameters of the plurality of parameters, 2) processing the correlated parameters using one or more algorithms, and 3) comparing such correlations;

generating a parameterized model of the diffracting structure based on the plurality of parameters; and

generating a library for the optical metrology system using the generated parameterized model of the diffracting structure and the second library parameter space, while not using a portion of the populated parameter space that is excluded from the reduced populated parameter space,

wherein the first library parameter space and the second library parameter space are composed of a same plurality of dimensions, each dimension associated with a different parameter of the plurality of parameters.

2. The method of claim 1 , further comprising determining a physical characteristic of the diffracting structure with the library.

3. The method of claim 1 , wherein the expected sample space use is based at least in part upon prior knowledge of a customer's region of interest.

4. The method of claim 1 , wherein the reduction of the populated parameter space is further based on recommending a sampling shape based on an expected sample space usage, wherein recommending the sampling shape comprises automatically choosing a collection of multiple possible shapes and evaluating each of a set of possible sampling shapes from the collection to determine a best fit for the expected sample space use.

5. The method of claim 1 , wherein the sampling filter includes a region defined by a certain slope and a certain width.

6. The method of claim 5 , wherein the one or more algorithms include a least squares fitting to determine the slope of the region of the sample filter.

7. The method of claim 1 , wherein the processing of the correlated parameters is based at least in part on prior knowledge of parameter correlation.

8. The method of claim 1 , wherein the optical metrology system includes one or more of a spectroscopic or angle-resolved ellipsometer or spectroscopic or angle-resolved reflectometer.

9. The method of claim 1 , wherein automatically reducing, by the processing unit, the populated parameter space of the first library parameter space comprises limiting a sampling range of the plurality of parameters in the first library parameter space by either the sampling shape or the sampling filter.

10. An optical metrology system comprising:

a memory storage for storage of an optical metrology library for the system; and

a processing unit to:

provide a first library parameter space comprising a populated parameter space of a plurality of parameters for modeling of a diffracting structure using the system,

automatically reduce, by a processing unit, the populated parameter space to produce a second library parameter space comprising a reduced populated parameter space of the plurality of parameters, wherein the reduction of the populated parameter space is based on the following:

a recommendation of a sampling filter that includes 1) identifying correlations between two or more parameters of the plurality of parameters, 2) processing the correlated parameters using one or more algorithms, and 3) comparing such correlations,

generate a parametrized model of the diffracting structure based on the plurality of parameters; and

generate a library for the optical metrology system using the generated parameterized model of the diffracting structure and the second library parameter-dimensional space, while not using a portion of the populated parameter space that is excluded from the reduced populated parameter space,

wherein the first library parameter space and the second library parameter space are composed of a same plurality of dimensions, each dimension associated with a different parameter of the plurality of parameters.

11. The system of claim 10 , wherein the system includes one or more of a spectroscopic or angle-resolved ellipsometer or spectroscopic or angle-resolved reflectometer.

12. The system of claim 10 , wherein the system is further to determine a physical characteristic of the diffracting structure with the library.

13. The system of claim 10 , wherein the expected sample space use is based at least in part upon prior knowledge of a customer's region of interest.

14. The system of claim 10 , wherein the reduction of the populated parameter space is further based on a recommendation of a sampling shape based on an expected sample space usage, wherein recommending the sampling shape comprises automatically choosing a collection of multiple possible shapes stored in the memory storage and evaluating each of a set of possible sampling shapes from the collection to determine a best fit for the expected sample space use.

15. The system of claim 10 , wherein the sampling filter includes a region defined by a certain slope and a certain width.

16. The system of claim 15 , wherein the one or more algorithms include a least squares fitting to determine the slope of the region of the sample filter.

17. The system of claim 10 , wherein the processing of the correlated parameters is based at least in part on prior knowledge of parameter correlation.

18. A non-transitory computer-readable storage medium having stored thereon data representing sequences of instructions that, when executed by a processor, cause the processor to perform operations comprising:

providing a first library parameter space comprising a populated parameter space of a plurality of parameters for modeling of a diffracting structure using an optical metrology system;

automatically reducing, by a processing unit, the populated parameter space to produce a second library parameter space comprising a reduced populated parameter space of the plurality of parameters, wherein the reduction of the populated parameter space is based on the following:

recommending a sampling filter that includes 1) identifying correlations between two or more parameters of the plurality of parameters, 2) processing the correlated parameters using one or more algorithms, and 3) comparing such correlations; and

generating a parameterized model of the diffracting structure based on the plurality of parameters;

generating a library for the optical metrology system using the generated parameterized model of the diffracting structure and the second library parameter space, while not using a portion of the populated parameter space that is excluded from the reduced populated parameter space,

wherein the first library parameter space and the second library parameter space are composed of a same plurality of dimensions, each dimension associated with a different parameter of the plurality of parameters.

19. The medium of claim 18 , further comprising instructions that, when executed by the processor, cause the processor to perform operations comprising:

determining a physical characteristic of the diffracting structure with the library.

20. The medium of claim 18 , wherein the expected sample space use is based at least in part upon prior knowledge of a customer's region of interest.

21. The medium of claim 18 , wherein the sampling filter includes a region defined by a certain slope and a certain width.

22. The medium of claim 21 , wherein the one or more algorithms include a least squares fitting to determine the slope of the region of the sample filter.

23. The medium of claim 18 , wherein the processing the correlated parameters is based at least in part on prior knowledge of parameter correlation.

24. The medium of claim 18 , wherein the reduction of the populated parameter space is further based on recommending a sampling shape based on an expected sample space usage, wherein recommending the sampling shape comprises automatically choosing a collection of multiple possible shapes and evaluating each of a set of possible sampling shapes from the collection to determine a best fit for the expected sample space use.