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  1. Home
  3. Inverse Lithography Source Optimization Via Compressive Sensing.
  1. Home
  3. Inverse Lithography Source Optimization Via Compressive Sensing.

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Inverse lithography source optimization via compressive sensing.

Zhiyang Song, Xu Ma, Jie Gao

    Optics Express
    |July 1, 2014

    View abstract on PubMed

    Summary
    This summary is machine-generated.

    This study introduces a novel source optimization (SO) method using compressive sensing (CS) to enhance lithographic imaging. The new approach efficiently extends the process window (PW) for improved manufacturing.

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    Area of Science:

    • Computational lithography
    • Image processing and reconstruction

    Background:

    • Current source optimization (SO) methods in lithography are computationally intensive or offer limited process window (PW) extension.
    • Pixel-based SO approaches often involve solving complex quadratic or linear programming problems.

    Purpose of the Study:

    • To develop an efficient and robust source optimization method for improving lithographic imaging.
    • To leverage compressive sensing (CS) theory for accelerated and enhanced SO design.

    Main Methods:

    • Formulating source optimization as an underdetermined linear problem, enabling acceleration.
    • Transforming the SO problem into an l1-norm image reconstruction problem based on CS principles.
    • Applying the linearized Bregman algorithm to synthesize sparse optimal source patterns.

    Main Results:

    • The proposed linear SO formulation demonstrates superior aerial image contrast compared to traditional quadratic methods.
    • Sparse regularization in inverse lithography effectively extends the process window (PW) of lithography systems.
    • Simulations confirm the superiority of the proposed SO method over existing approaches.

    Conclusions:

    • Compressive sensing provides an efficient and robust framework for source optimization in lithography.
    • The developed method enhances manufacturability and extends the process window, improving lithographic imaging performance.