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Automatic athermal design of diffractive-refractive hybrid optical systems using a simplified genetic algorithm.

Siyuan Zeng, Jinjin Chen, Beibei Tong

    Applied Optics
    |March 17, 2026
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    Summary

    This study introduces an automated athermalization design method using a simplified genetic algorithm (SGA) for optical systems. The approach enhances efficiency and generalizability for infrared systems, achieving near-diffraction-limited performance across wide temperature ranges.

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    Area of Science:

    • Optical Engineering
    • Materials Science

    Background:

    • Traditional athermalization techniques lack automation, efficiency, and broad applicability.
    • Developing robust optical systems for varying temperatures is crucial for reliable performance.

    Purpose of the Study:

    • To propose an automated athermalization design method for optical systems.
    • To enhance the efficiency and generalizability of athermalization design.
    • To validate the method's effectiveness for infrared optical systems.

    Main Methods:

    • Developed an automatic athermalization approach utilizing a simplified genetic algorithm (SGA).
    • Implemented material selection for refractive-diffractive hybrid optical systems.
    • Designed and validated two infrared optical systems (3.7-4.8 µm wavelength).

    Main Results:

    • The designed infrared systems maintained near-diffraction-limited modulation transfer function (MTF) from -40°C to +70°C.
    • Field-averaged MTF variation remained below 0.01 across the temperature range.
    • The SGA method demonstrated comparable imaging performance to the hammer optimizer with a tenfold speedup.

    Conclusions:

    • The proposed simplified genetic algorithm (SGA) offers an effective and efficient automated solution for athermalization design.
    • This method significantly improves the generalizability and automation of optical system design for thermal stability.
    • The approach is particularly valuable for infrared and mid-wave infrared (MWIR) applications requiring high-performance imaging across temperature fluctuations.