The Green function approach is used for the evaluation of second-order self-energy C,,(E) in Heisenberg antiferromagnets. The decoupling scheme is discussed in detail and its step-by-step correspondence with classes of Feynman graphs is shown. The final result is in agreement with our previous results obtained by a different method and with the diagrammatic approach. It is, instead, in contrast with an expression for C,,(E) found very recently by Wenzel and Wagner. Some of the reasons which cause this discrepancy and lead to the incorrectness of their final result are discussed.

EUV lithography is a promising candidate for 2x-nm-node device manufacturing. Management of effective dose is important to meet the stringent requirements for CD control. Test pattern for a lithography tool evaluation, the effective dose monitor (EDM), shows good performance in the dose monitoring for optical lithography, for example, KrF lithography. The EDM can measure an exposure dose with no influence on defocus, because the image of an EDM pattern is produced by the zero-th-order ray in diffraction only. When this technique is applied to EUV lithography, the mask shadowing effect should be taken into consideration. We calculated the shadowing effect as a function of field position and applied it to correction of the experimental dose variation. We estimated the dose variation in EUV exposure field to be 2.55 % when corrected by the shadowing effect. We showed that the EDM is useful for EUV lithography.

The population of overlay errors in layer-to-layer structures in semiconductor manufacturing often obeys non-normal distribution functions such as elliptic, rectangular, and skewed distributions. Thus, there can be many wrong diagnoses of quality control that can lead to consumer's risk and producer's risk. In a lot acceptance test, a product should be judged by variables rather than by attributes because of the small sample size. A new acceptance test by variables was introduced for a non-normal population. It included sample skewness and kurtosis as well as mean and standard deviations. Using operating characteristic (OC) curves, it was shown that sampling inspection by variables can be applied safely to a strong nonnormal population with new variables. #

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