Improved ptychographic inspection of EUV reticles via inclusion of prior information

The development of actinic mask metrology tools represents one of the major challenges to be addressed on the roadmap of extreme ultra violet (EUV) lithography. Technological advancements in EUV lithography result in the possibility to print increasingly fine and highly resolved structures on a silicon wafer, however the presence of fine–scale defects, interspersed in the printable mask layout, may lead to defective wafer prints. Hence the development of
actinic methods for review of potential defect sites becomes paramount. Here, we report on a ptychographic algorithm that makes use of prior information about the object to be retrieved, generated by means of rigorous computations, to improve the detectability of defects whose dimensions are of the order of the wavelength. The comprehensive study demonstrates that the inclusion of prior information as a regularizer in the ptychographic optimization problem
results in a higher reconstruction quality and an improved robustness to noise with respect to the standard ptychographic iterative engine (PIE). We show that the proposed method decreases the number of scan positions necessary to retrieve an high quality image and relaxes requirements in terms of signal to noise ratio (SNR). The results are further compared with the state–of–art total
variation based ptychographic imaging