A Collective Propagation Law of Optical Vortex Constellations and Longitudinal Sensing
Niladri Modak, Rafael F. Barros, Marco Ornigotti, Robert Fickler
Abstract
Optical vortices are ubiquitous phenomena naturally appearing in wave physics, yet higher-order charges inherently split into constellations of lowest-order singularities at the smallest deviation from an ideal situation. While these constellations are common phenomena in real-world scenarios, characterizing their longitudinal evolution typically relies on exhaustive full-field descriptions or the ambiguous, sequential tracking of individual singularities. Here, we reveal and experimentally demonstrate a simple deterministic law describing the paraxial longitudinal propagation of an arbitrary constellation of optical vortices in standard Gaussian backgrounds. By mapping the constituting singularity coordinates to their elementary symmetric polynomials (ESPs), we capture the holistic evolution of the constellation during propagation, completely bypassing the practical need to sequentially track indistinguishable vortices. We further show that such complex ESPs provide a useful metrological tool for the estimation of longitudinal displacements. Our results reveal a previously unrecognized compact description of collective vortex dynamics, introducing a new route to longitudinal sensing through singularimetry.
Create a lesson
Related papers
Correlation geometry and topology of structured optical beams
Jyrki Laatikainen, Olga Korotkova
Dual-comb generated in single thin-film lithium niobate microrings
Renhong Gao, Qifeng Hou, Xinzhi Zheng et al.
350-GHz-Band 4 by 4 RTD Monostatic Radar Array for Sequential Multidirectional Ranging
Li Yi, Ryoma Nakamura, Shota Ito et al.
Multi-contrast wide-field mid-infrared photothermal imaging
Anooj Thayyil Raveendran, Cornelia Reuter, Samir F. El-Mashtoly et al.
Topological photonic cavities based on dissimilar Bragg gratings
Alejandro Sánchez-Sánchez, José Manuel Luque-González, Gauthier Krizman et al.
Wavelength-Multiplexed Nonlinear Computing with a Single-Layer Diffractive Optical Processor
Yongkang Cheng, Che-Yung Shen, Yuntian Wang et al.