Design of two-dimensional multilevel optical anisotropic diffraction gratings with a generative adversarial network

Area of Science:

• Optics and Photonics
• Computational Electromagnetics

Background:

• Designing optical elements with specific functionalities, such as multilevel optical anisotropic diffraction gratings, is crucial for advanced optical systems.
• Traditional design methods can be complex and time-consuming, limiting the customization of grating characteristics.

Purpose of the Study:

• To develop a novel method for designing multilevel optical anisotropic diffraction gratings with customizable characteristics.
• To leverage generative adversarial networks (GANs) for efficient and precise optical grating design.

Main Methods:

• Utilizing a generative adversarial network (GAN) approach for grating design.
• Employing the far electric field (polarization and intensity) of diffracted light as input for the GAN.
• Validating the designed structures using the finite-difference time-domain (FDTD) method for numerical evaluation.

Main Results:

• The GAN successfully designed multilevel optical anisotropic diffraction gratings with specific, customizable characteristics.
• Numerical simulations confirmed that the designed gratings can be fabricated with the intended optical parameters.
• The designed gratings demonstrate potential for precise control over light polarization and intensity.

Conclusions:

• Generative adversarial networks provide an effective platform for designing advanced optical diffraction gratings.
• The developed method enables the creation of tailored optical elements for diverse applications.
• These custom gratings can lead to significant improvements in various optical devices and systems.