Pattern measuring method, pattern measuring apparatus, and computer program storage device
The present invention is directed to a pattern measuring method and the like for deriving a roughness evaluation value from which measurement noise having a frequency component is removed. The pattern measuring method includes generating a plurality of integration signals having the different number of integration from the signals of the plurality of frames; acquiring edge position information of the pattern along an edge from the plurality of respective integration signals having the different number of integration; obtaining a difference between the edge position information and reference position information; obtaining a spectral component of a specific spatial frequency of the edge or a standard deviation based upon the difference; performing regression analysis in which a value relating to the number of integration is set as an explanatory variable, and a value relating to the spectral component or the standard deviation is set as a target variable; and outputting a value obtained by the regression analysis as a roughness index value of the pattern or a noise index value included in the signals.
1. A pattern measuring method for measuring a pattern based upon detection signals obtained by scanning a beam a plurality of times on the pattern formed on a sample, the method comprising:
acquiring signals of a plurality of frames obtained by scanning the beam a plurality of times on the pattern formed on the sample;
generating a plurality of integration signals having the different number of integration from the signals of the plurality of frames;
acquiring edge position information of the pattern along an edge from the plurality of respective integration signals having the different number of integration;
obtaining a difference between the edge position information and reference position information;
obtaining a spectral component of a specific spatial frequency of the edge or a standard deviation based upon the difference;
performing regression analysis in which a value relating to the number of integration is set as an explanatory variable, and a value relating to the spectral component or the standard deviation is set as a target variable; and
outputting a value obtained by the regression analysis as a roughness index value of the pattern or a noise index value included in the signals.
2. The pattern measuring method according to claim 1 , wherein
the regression analysis of the spectral component is performed on a plurality of specific spatial frequencies.
3. The pattern measuring method according to claim 1 , wherein
the regression analysis of the spectral component is performed on a plurality of specific spatial frequencies, and the noise index value included in the signals is obtained based upon a tilt of a model of the regression analysis.
4. The pattern measuring method according to claim 1 , wherein
at least one of an evaluation value of frequency spectral density of roughness PSD_LER(f) and frequency spectral density of measurement noise PSD_noise(f)/NF is calculated by performing regression analysis using an equation below on spatial frequency spectral density PSD_obs(N, f) of the edge included in the plurality of integration signals having the different number of integration
PSD _ obs ( NF,f )= PSD _ LER ( f )+ PSD _noise( f )/ NF
NF: number of integration
f: spatial frequency.
5. The pattern measuring method according to claim 4 , wherein
a roughness evaluation value LER is calculated based upon an equation below from a plurality of the spatial frequencies f
LER =√(∫ PSD _ LER ( f ) df ).
6. A computer program storage device comprising a storage medium readable by a processor and storing a program instruction executable by the processor, wherein
the processor is configured to:
acquire detection signals of a plurality of frames obtained by scanning a beam a plurality of times on a pattern formed on a sample;
generate a plurality of integration signals having the different number of integration from the detection signals of the plurality of frames;
acquire edge position information of the pattern along an edge from the plurality of respective integration signals having the different number of integration;
obtain a difference between the edge position information and reference position information;
obtain a spectral component of a specific spatial frequency of the edge or a standard deviation based upon the difference;
perform regression analysis in which a value relating to the number of integration is set as an explanatory variable, and a value relating to the spectral component or the standard deviation is set as a target variable; and
output a value obtained by the regression analysis as a roughness index value of the pattern or a noise index value included in the signals.
7. The computer program storage device according to claim 6 , wherein
the processor is configured to:
perform regression analysis of the spectral component on a plurality of specific spatial frequencies.
8. The computer program storage device according to claim 6 , wherein
the processor is configured to:
perform regression analysis of the spectral component on a plurality of specific spatial frequencies; and
obtain the noise index value included in the signals based upon a tilt of a model of the regression analysis.
9. The computer program storage device according to claim 6 , wherein
the processor is configured to:
calculate at least one of an evaluation value of frequency spectral density of roughness PSD_LER(f) and frequency spectral density of measurement noise PSD_noise(f)/NF by performing regression analysis using an equation below on spatial frequency spectral density PSD_obs(N, f) of the edge included in the plurality of integration signals having the different number of integration
PSD _ obs ( NF,f )= PSD _ LER ( f )+ PSD _noise( f )/ NF
NF: number of integration
f: spatial frequency.
10. The computer program storage device according to claim 9 , wherein
the processor is configured to:
calculate a roughness evaluation value LER based upon an equation below from a plurality of the spatial frequencies f
LER =√(∫ PSD _ LER ( f ) df ).
11. A pattern measuring apparatus for measuring a pattern formed on a sample, comprising:
a processor;
a memory connected to the processor; and
a computer executable program code that is stored in the memory and instructs the processor to
acquire detection signals of a plurality of frames obtained by scanning a beam a plurality of times on the pattern formed on a sample;
generate a plurality of integration signals having the different number of integration from the detection signals of the plurality of frames;
acquire edge position information of the pattern along an edge from the plurality of respective integration signals having the different number of integration;
obtain a difference between the edge position information and reference position information;
obtain a spectral component of a specific spatial frequency of the edge or a standard deviation based upon the difference;
perform regression analysis in which a value relating to the number of integration is set as an explanatory variable, and a value relating to the spectral component or the standard deviation is set as a target variable; and
output a value obtained by the regression analysis as a roughness index value of the pattern or a noise index value included in the signals.
12. The pattern measuring apparatus according to claim 11 , wherein
the program code instructs the processor to
perform regression analysis of the spectral component on a plurality of specific spatial frequencies.
13. The pattern measuring apparatus according to claim 11 , wherein
the program code instructs the processor to
perform regression analysis of the spectral component on a plurality of specific spatial frequencies; and
obtain the noise index value included in the signals based upon a tilt of a model of the regression analysis.
14. The pattern measuring apparatus according to claim 11 , wherein
the program code instructs the processor to
calculate at least one of an evaluation value of frequency spectral density of roughness PSD_LER(f) and frequency spectral density of measurement noise PSD_noise(f)/NF by performing regression analysis using an equation below on spatial frequency spectral density PSD_obs(N, f) of the edge included in the plurality of integration signals having the different number of integration
PSD _ obs ( NF,f )= PSD _ LER ( f )+ PSD _noise( f )/ NF
NF: number of integration
f: spatial frequency.
15. The pattern measuring apparatus according to claim 14 , wherein
the program code instructs the processor to
calculate a roughness evaluation value LER based upon an equation below from a plurality of spatial frequencies f
LER =√(∫ PSD _ LER ( f ) df ).