Single-Cavity Dual-Comb Mueller Polarimetry for Material-Aware LiDAR

Abstract

We demonstrate a single-cavity dual-comb Mueller-matrix polarimetric LiDAR that rapidly retrieves full 4 × 4 Mueller matrices without external polarization-state generators or polarization-state analyzers. The key advance is that the intrinsic polarization beating of the polarization-multiplexed dual-combs from the single source provides a self-scanning incident Stokes-state basis, replacing the sequential polarization-state generation normally required in active Mueller polarimetry. The recovered Mueller matrices are decomposed into physically interpretable descriptors, including diattenuation, polarizance, retardance, depolarization, and polarimetric-purity indices, to construct a multidimensional material-fingerprint space. Experiments on aluminum, wood, plastic, and mirror targets show clear separation of material classes in this physics-based feature space. Combining convex-hull analysis with machine-learning classification yields 93.75% accuracy. These results establish dual-comb Mueller-matrix polarimetry as a compact and practical framework for material-aware remote sensing and other applications requiring interpretable polarization contrast.