Pixelated mask optimization on quantum computers

Yosuke Okudaira; Satoshi Yashiki

doi:10.1117/12.2550780

23 March 2020 Pixelated mask optimization on quantum computers

Yosuke Okudaira, Satoshi Yashiki

Proceedings Volume 11327, Optical Microlithography XXXIII; 1132705 (2020) https://doi.org/10.1117/12.2550780
Event: SPIE Advanced Lithography, 2020, San Jose, California, United States

Abstract

In the field of microlithography, conventional computers are widely used for mask optimization. Recent progress of quantum and quantum-inspired computers has encouraged the development of quantum algorithms for numerous applications. So far, no method has been established for solving mask optimization problems with quantum computers. We introduced a simple model that describes the mask optimization problem as a quadratic unconstrained binary optimization (QUBO) problem, which is easily implemented on these computers. For simplicity, we assume there exists a target image profile on the wafer. The target can be the image of an existing mask or a virtual ideal mask which may be designed as a pixelated mask having a continuous transmission distribution. The solution is evaluated as the difference between the simulated image profile on the wafer surface and the target profile.

Conference Presentation

Citation Download Citation

Yosuke Okudaira and Satoshi Yashiki "Pixelated mask optimization on quantum computers", Proc. SPIE 11327, Optical Microlithography XXXIII, 1132705 (23 March 2020); https://doi.org/10.1117/12.2550780

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