Orthogonality breaking sensing model based on the instantaneous Stokes vector and the Mueller calculus
No\'e Ortega-Quijano, Julien Fade, Muriel Roche, Fran\c{c}ois Parnet,, Mehdi Alouini

TL;DR
This paper presents a comprehensive analysis of orthogonality breaking polarimetric sensing using the instantaneous Stokes vector and Mueller calculus, demonstrating its robustness and specificity to diattenuation in various sample conditions.
Contribution
It introduces a formalism-based model for orthogonality breaking sensing, confirming its immunity to birefringence and depolarization, and identifies optimal configurations for fiber-based endoscopic measurements.
Findings
Orthogonality breaking is caused by sample diattenuation.
The technique is immune to birefringence and diagonal depolarization.
Optimal source configuration enhances fiber-based measurements.
Abstract
Polarimetric sensing by orthogonality breaking has been recently proposed as an alternative technique for performing direct and fast polarimetric measurements using a specific dual-frequency dual-polarization (DFDP) source. Based on the instantaneous Stokes-Mueller formalism to describe the high-frequency evolution of the DFDP beam intensity, we thoroughly analyze the interaction of such a beam with birefringent, dichroic and depolarizing samples. This allows us to confirm that orthogonality breaking is produced by the sample diattenuation, whereas this technique is immune to both birefringence and diagonal depolarization. We further analyze the robustness of this technique when polarimetric sensing is performed through a birefringent waveguide, and the optimal DFDP source configuration for fiber-based endoscopic measurements is subsequently identified. Finally, we consider a stochastic…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
