Spatial-to-Temporal Orbital Angular Momentum Mapping in Twisted Light Fields

TL;DR

This paper introduces a machine learning method that maps spatial orbital angular momentum in twisted light fields to temporal signals, allowing OAM recognition with minimal detector hardware, simplifying measurement processes.

Contribution

The novel speckle-based machine learning approach enables OAM recognition using only 1-D or 0-D detectors, reducing hardware complexity compared to traditional 2D detection methods.

Findings

Achieved OAM recognition with single-pixel detectors

Demonstrated effective mapping of spatial to temporal OAM signals

Reduced hardware requirements for OAM measurement

Abstract

Optical angular momentum (OAM) in light beams is manifested as the two-dimensional spatial distribution of its complex amplitude, necessitating a 2D detector for its measurement. Here we present a novel speckle-based machine learning approach for OAM recognition, which enables recognition using a 1-D array detector or even a 0-D single-pixel detector.