Expansion of Polarization Vector Map Calculations for Structured Photonics: Modeling Eccentricity and Tilt Variations

Polarization is a critical property of light in structured photonics, enabling applications such as optical communications, high-precision sensing, and beam shaping.This paper expands upon prior work by analyzing the impact of varying Stokes parameters on polarization properties, including eccentricity (), tilt (2), and chirality.We validate polarization states by mapping them onto the Poincar sphere, reconstruct complex wavefronts, and study the effect of discretization on beam fidelity.Using calculations and experimental modeling, we demonstrate improvements in high-fidelity structure synthesis with increasing channel discretization, laying the groundwork for advanced photonic applications.

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Publication Details

Journal
eScholarship (California Digital Library)
Published
2024-10-01
Primary Topic
Neural Networks and Reservoir Computing
Type
article
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article

Expansion of Polarization Vector Map Calculations for Structured Photonics: Modeling Eccentricity and Tilt Variations

eScholarship (California Digital Library)
Neural Networks and Reservoir Computing
article

Expansion of Polarization Vector Map Calculations for Structured Photonics: Modeling Eccentricity and Tilt Variations

article en

Abstract

Polarization is a critical property of light in structured photonics, enabling applications such as optical communications, high-precision sensing, and beam shaping.This paper expands upon prior work by analyzing the impact of varying Stokes parameters on polarization properties, including eccentricity (), tilt (2), and chirality.We validate polarization states by mapping them onto the Poincar sphere, reconstruct complex wavefronts, and study the effect of discretization on beam fidelity.Using calculations and experimental modeling, we demonstrate improvements in high-fidelity structure synthesis with increasing channel discretization, laying the groundwork for advanced photonic applications.

eScholarship (California Digital Library)
UCLA Health (US)
Openalex Percentile: Top 54%
Neural Networks and Reservoir Computing
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