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Symmetry-preserving modeling for lithographic imaging.

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    A new method preserves symmetries in computational imaging by projecting iterative vectors onto a symmetric subspace. This project-to-symmetry-subspace (PTSS) approach prevents symmetry loss in optical kernel generation.

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    Area of Science:

    • Computational imaging
    • Optical lithography
    • Numerical modeling

    Background:

    • Preserving physical system symmetries in numerical models is a significant challenge in computational imaging and lithography.
    • Iterative generation of optical kernels can lead to symmetry loss, impacting model accuracy.

    Purpose of the Study:

    • To introduce a novel method, project-to-symmetry-subspace (PTSS), for preserving symmetries during optical kernel generation.
    • To address the challenge of symmetry loss in computational imaging numerical models.

    Main Methods:

    • The project-to-symmetry-subspace (PTSS) method involves projecting iterative vectors onto a predefined symmetric subspace.
    • This projection is applied during the decomposition of the transmission cross coefficient (TCC).

    Main Results:

    • The PTSS method successfully generates truncated sets of optical kernels.
    • The generated optical kernels exhibit significantly reduced symmetry errors, irrespective of the truncation order.

    Conclusions:

    • The PTSS method effectively prevents symmetry loss in the iterative generation of optical kernels.
    • This approach ensures the faithful preservation of symmetries in computational imaging and lithography models.