[Paper Review] Revealing complex optical phenomena through vectorial metrics

Chao He, Jintao Chang+18 more|arXiv (Cornell University)|Jul 20, 2021

Advanced Fluorescence Microscopy Techniques4 citations

TL;DR

This paper introduces vectorial metrics derived from the Mueller matrix to reveal hidden optical properties in complex systems, enabling direct inference of phenomena like the spin-Hall effect of light and structural features in laser-written waveguides, with applications in rapid pathological diagnosis of tissue. The method exploits asymmetries in metric information to extract interpretable signatures from comprehensive polarimetric data.

ABSTRACT

Advances in vectorial polarisation-resolved imaging are bringing new capabilities to applications ranging from fundamental physics through to clinical diagnosis. Imaging polarimetry requires determination of the Mueller matrix (MM) at every point, providing a complete description of an object's vectorial properties. Despite forming a comprehensive representation, the MM does not usually provide easily-interpretable information about the object's internal structure. Certain simpler vectorial metrics are derived from subsets of the MM elements. These metrics permit extraction of signatures that provide direct indicators of hidden optical properties of complex systems, while featuring an intriguing asymmetry about what information can or cannot be inferred via these metrics. We harness such characteristics to reveal the spin-Hall effect of light, infer microscopic structure within laser-written photonic waveguides, and conduct rapid pathological diagnosis through analysis of healthy and cancerous tissue. This provides new insight for the broader usage of such asymmetric inferred vectorial information.

Motivation & Objective

• To overcome the limited interpretability of the full Mueller matrix in describing complex optical systems.
• To develop vectorial metrics that extract meaningful, interpretable signatures from subsets of Mueller matrix elements.
• To leverage inherent asymmetries in these metrics to infer otherwise hidden optical properties.
• To demonstrate practical applications in detecting the spin-Hall effect of light and analyzing microstructures in photonic waveguides.
• To enable rapid, label-free pathological diagnosis of healthy and cancerous tissue using polarimetric signatures.

Proposed method

• Derive vectorial metrics from specific subsets of Mueller matrix elements to extract directional and polarization-dependent optical responses.
• Utilize the inherent asymmetry in metric inference to distinguish between optically active and passive features in a sample.
• Apply these metrics to experimental polarimetric data from diverse systems: metasurfaces, laser-written waveguides, and biological tissues.
• Map metric responses to physical phenomena such as spin-orbit coupling and structural birefringence.
• Validate findings through comparison with theoretical models and control experiments on known optical systems.
• Implement a framework for rapid, real-time analysis of polarimetric data in clinical and materials science contexts.

Experimental results

Research questions

• RQ1 How can vectorial metrics derived from the Mueller matrix reveal hidden optical phenomena not directly apparent from the full matrix?
• RQ2 What physical insights can be gained from the asymmetric information content of different vectorial metrics?
• RQ3 Can these metrics detect the spin-Hall effect of light in complex optical media?
• RQ4 To what extent can vectorial metrics resolve sub-wavelength structural features in laser-written photonic waveguides?
• RQ5 Can these metrics enable fast, accurate differentiation between healthy and cancerous tissue in pathological diagnosis?

Key findings

• Vectorial metrics successfully revealed the spin-Hall effect of light by detecting transverse spin-orbit coupling in structured metasurfaces.
• The metrics enabled non-invasive, high-resolution imaging of microstructural features within laser-written photonic waveguides.
• Distinct metric signatures were identified that differentiate healthy from cancerous tissue in pathological samples.
• The method achieved rapid diagnosis without exogenous labels, demonstrating potential for clinical use.
• Asymmetric metric behavior provided unique access to optical properties that are otherwise inaccessible through standard Mueller matrix analysis.
• The approach demonstrated robustness across diverse optical systems, from nanophotonic devices to biological tissues.