Virtual photo-mask critical-dimension measurement
View Patent ↗A technique for reconstructing a mask pattern corresponding to a photo-mask using a target mask pattern (which excludes defects) and an image of at least a portion of the photo-mask is described. This image may be an optical inspection image of the photo-mask that is determined using inspection optics which includes an optical path, and the reconstructed mask pattern may include additional spatial frequencies than the image. Furthermore, the reconstructed mask pattern may be reconstructed based on a characteristic of the optical path (such as an optical bandwidth of the optical path) using a constrained inverse optical calculation in which there are a finite number of discrete feature widths allowed in the reconstructed mask pattern, and where a given feature has a constant feature width. Consequently, the features in the reconstructed mask pattern may each have the constant feature width, such as an average critical dimension of the reconstructed mask pattern.
1. A computer-implemented method for determining a reconstructed mask pattern, comprising:
receiving a target mask pattern;
receiving an image of at least a portion of a photo-mask corresponding to a mask pattern, wherein the image is determined using inspection optics having an optical path; and
reconstructing, using a computer, the mask pattern from the image based on a characteristic of the optical path and the target mask pattern, wherein the mask pattern is reconstructed using a constrained inverse optical calculation in which there are a finite number of discrete feature widths allowed in the reconstructed mask pattern, and wherein a given feature has a constant feature width.
2. The method of claim 1 , wherein the reconstructed mask pattern is characterized by additional spatial frequencies than the image.
3. The method of claim 1 , wherein, in the constrained inverse optical calculation, the image is at an image plane of a model of the optical path and the mask pattern is at an object plane of the model of the optical path.
4. The method of claim 1 , wherein the characteristic includes a range of wavelengths transmitted via the optical path.
5. The method of claim 1 , wherein the features in the reconstructed mask pattern each have the constant feature width.
6. The method of claim 5 , wherein the constant feature width is an average critical dimension of the reconstructed mask pattern.
7. The method of claim 6 , wherein the method further comprises comparing the average critical dimension of the reconstructed mask pattern to an average critical dimension of the target mask pattern to determine a critical-dimension bias of the photo-mask.
8. The method of claim 7 , wherein the method further comprises determining an acceptance condition of the photo-mask based on the critical-dimension bias.
9. The method of claim 6 , wherein the average critical dimension is associated with a minimum of a cost function in the inverse optical calculation; and
wherein the cost function corresponds to a difference between the reconstructed mask pattern and the target mask pattern.
10. The method of claim 1 , wherein, by constraining the inverse optical calculation a convergence time of the inverse optical calculation is faster than that of an unconstrained inverse optical calculation.
11. The method of claim 1 , wherein primary features in the reconstructed mask pattern each have the constant feature width; and
wherein sub-resolution assist features in the reconstructed mask pattern each have another constant feature width, which is different than the constant feature width.
12. The method of claim 1 , wherein the spatial frequencies in the image are greater than or equal to a spatial frequency corresponding to an average critical dimension of the target mask pattern.
13. A non-transitory computer-program product for use in conjunction with a computer system, the computer-program product comprising a computer-readable storage medium and a computer-program mechanism embedded therein to determine a reconstructed mask pattern, the computer-program mechanism including:
instructions for receiving a target mask pattern;
instructions for receiving an image of at least a portion of a photo-mask corresponding to a mask pattern, wherein the image is determined using inspection optics having an optical path; and
instructions for reconstructing the mask pattern from the image based on a characteristic of the optical path and the target mask pattern, wherein the mask pattern is reconstructed using a constrained inverse optical calculation in which there are a finite number of discrete feature widths allowed in the reconstructed mask pattern, and wherein a given feature has a constant feature width.
14. The computer-program product of claim 13 , wherein the reconstructed mask pattern is characterized by additional spatial frequencies than the image.
15. The computer-program product of claim 13 , wherein, in the constrained inverse optical calculation, the image is at an image plane of a model of the optical path and the mask pattern is at an object plane of the model of the optical path.
16. The computer-program product of claim 13 , wherein the characteristic includes a range of wavelengths transmitted via the optical path.
17. The computer-program product of claim 13 , wherein the features in the reconstructed mask pattern each have the constant feature width.
18. The computer-program product of claim 17 , wherein the constant feature width is an average critical dimension of the reconstructed mask pattern.
19. The computer-program product of claim 18 , wherein the computer-program product further includes comparing the average critical dimension of the reconstructed mask pattern to an average critical dimension of the target mask pattern to determine a critical-dimension bias of the photo-mask.
20. The computer-program product of claim 19 , wherein the computer-program product further includes determining an acceptance condition of the photo-mask based on the critical-dimension bias.
21. The computer-program product of claim 18 , wherein the average critical dimension is associated with a minimum of a cost function in the inverse optical calculation; and
wherein the cost function corresponds to a difference between the reconstructed mask pattern and the target mask pattern.
22. The computer-program product of claim 18 , wherein, by constraining the inverse optical calculation a convergence time of the inverse optical calculation is faster than that of an unconstrained inverse optical calculation.
23. The computer-program product of claim 18 , wherein primary features in the reconstructed mask pattern each have the constant feature width; and
wherein sub-resolution assist features in the reconstructed mask pattern each have another constant feature width, which is different than the constant feature width.
24. The computer-program product of claim 18 , wherein the spatial frequencies in the image are greater than or equal to a spatial frequency corresponding to an average critical dimension of the target mask pattern.
25. A computer system, comprising:
at least one processor;
at least one memory; and
at least one program module, the program module stored in the memory and configured to be executed by the processor to determine a reconstructed mask pattern, the program module including:
instructions for receiving a target mask pattern;
instructions for receiving an image of at least a portion of a photo-mask corresponding to a mask pattern, wherein the image is determined using inspection optics having an optical path; and
instructions for reconstructing the mask pattern from the image based on a characteristic of the optical path and the target mask pattern, wherein the mask pattern is reconstructed using a constrained inverse optical calculation in which there are a finite number of discrete feature widths allowed in the reconstructed mask pattern, and wherein a given feature has a constant feature width.