A new data reduction method is presented for single-wavelength ellipsometry. A genetic algorithm is applied to ellipsometric data to find the best fit. The sample consists of a single absorbing layer on a semi-infinite substrate. The genetic algorithm has good convergence and is applicable to many different problems, including those with different independent measurements and situations with more than two angles of incidence. Results are similar to those obtained by other inversion techniques.

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Data Obtained by Adding to the Data of Table 2 Gaussian Noise with Different Standard Deviationsa

Incidence Angle ϕ

Ellipsometric Angle

Standard Deviation

${\mathrm{\Delta}}_{m}$

${\psi}_{m}$

${\sigma}^{\mathrm{\Delta}}$

${\sigma}^{\psi}$

45

170.95

31.93

0.22

0.06

60

168.73

21.48

0.38

0.06

70

169.23

8.42

0.52

0.20

80

357.14

13.01

0.44

0.12

Ref. 8. The measurement errors ${\u220a}^{\mathrm{\Delta}}$ and ${\u220a}^{\psi}$ were chosen to be the same as the standard deviations.

Table 6

Data Generated for a Film of $n=2.2,$$k=0.22,$ and $d=10\mathbf{nm}$ on a Substrate of ${n}_{s}=4.05$ and ${k}_{s}=0.028$ with $\lambda =546.1\mathbf{nm}$

Added noise of 0.02° standard deviation.
Added noise of 0.01° standard deviation.

Table 7

Data Generated for a Film of $n=2.2,$$k=0.22,$ and $d=10\mathbf{nm}$ on a Substrate of ${n}_{s}=4.05$ and ${k}_{s}=0.028$ with $\lambda =546.1\mathbf{nm}$

Data Obtained by Adding to the Data of Table 2 Gaussian Noise with Different Standard Deviationsa

Incidence Angle ϕ

Ellipsometric Angle

Standard Deviation

${\mathrm{\Delta}}_{m}$

${\psi}_{m}$

${\sigma}^{\mathrm{\Delta}}$

${\sigma}^{\psi}$

45

170.95

31.93

0.22

0.06

60

168.73

21.48

0.38

0.06

70

169.23

8.42

0.52

0.20

80

357.14

13.01

0.44

0.12

Ref. 8. The measurement errors ${\u220a}^{\mathrm{\Delta}}$ and ${\u220a}^{\psi}$ were chosen to be the same as the standard deviations.

Table 6

Data Generated for a Film of $n=2.2,$$k=0.22,$ and $d=10\mathbf{nm}$ on a Substrate of ${n}_{s}=4.05$ and ${k}_{s}=0.028$ with $\lambda =546.1\mathbf{nm}$

Added noise of 0.02° standard deviation.
Added noise of 0.01° standard deviation.

Table 7

Data Generated for a Film of $n=2.2,$$k=0.22,$ and $d=10\mathbf{nm}$ on a Substrate of ${n}_{s}=4.05$ and ${k}_{s}=0.028$ with $\lambda =546.1\mathbf{nm}$