Towards high-performance polarimeters with large-area uniform chiral shells: a comparative study on the polarization...

Area of Science:

• Optics and Photonics
• Materials Science
• Computational Science

Background:

• Traditional polarimeters face limitations in waveband and precision due to reliance on polarization-sensitive materials and fixed mapping relationships.
• Fabrication and detection errors further constrain the performance of existing polarization detection technologies.

Purpose of the Study:

• To demonstrate a highly precise, stable, and broadband full-Stokes polarimeter.
• To overcome the limitations of conventional polarimeters by utilizing large-area uniform chiral shells and a post-established mapping relationship.

Main Methods:

• Fabrication of uniform chiral shells via silver deposition on a microsphere monolayer.
• Establishing a post-mapping relationship using a deep learning algorithm (DLA) or Mueller matrix theory.
• Systematic investigation of chiral shell properties, mapping relationships, and detection precision across a broad waveband (500-750 nm).

Main Results:

• Achieved optical chirality (circular dichroism) of ~0.15 and anisotropy of ~1.7.
• Deep learning algorithm demonstrated superior detection precision with mean squared errors (MSEs) as low as 0.10% (S1), 0.41% (S2), and 0.24% (S3) at 710 nm.
• Broadband averaged MSEs with DLA were significantly lower (0.16% S1, 0.46% S2, 0.61% S3) compared to Mueller matrix theory (0.45% S1, 1% S2, 39.8% S3).

Conclusions:

• The developed polarimeter offers high precision, stability, and broadband operation.
• Deep learning significantly enhances detection precision and robustness, especially under challenging conditions like weak illumination.
• The novel approach using chiral shells and DLA represents a significant advancement in polarization detection and imaging technologies.