High-performance single-shot full-Stokes polarimetry based on long-range disorder moiré metasurface

Area of Science:

• Optical Engineering
• Metasurface Technology
• Computational Sensing

Background:

• Polarimetry is crucial across science but limited by bulky traditional optics and complex metasurface fabrication.
• Existing full-Stokes polarimeters face challenges with size, cost, and alignment precision.

Purpose of the Study:

• To demonstrate a cost-effective, single-shot full-Stokes polarimeter.
• To overcome limitations of traditional polarimetry and complex metasurface fabrication.
• To develop a calibration-free deep learning approach for polarization state decoding.

Main Methods:

• Fabrication of a disordered twisted nanohole array (DTNA) metasurface using scalable microsphere lithography.
• Utilizing intrinsic disorder and moiré anisotropy for encoding polarization states.
• Developing a deep learning framework for end-to-end mapping of intensity distributions to Stokes vectors.

Main Results:

• Achieved high-precision reconstruction of Stokes parameters (S1, S2, S3) with low normalized MSEs (0.047%, 0.16%, 0.032%).
• Demonstrated robust polarization encoding through spatially diverse optical responses.
• Identified synergistic interaction of optical disorder (phase, LD, CD) as key to performance.

Conclusions:

• Presents a robust, alignment-free paradigm for high-performance integrated polarimetry.
• Offers fundamental insights into the role of disorder in computational optical sensing.
• Enables wider adoption of polarimetry in diverse scientific and imaging applications.