Environmental monitoring using orbital angular momentum mode decomposition enhanced machine learning

TL;DR

This paper introduces a machine learning method that uses orbital angular momentum mode decomposition of vortex beams to accurately monitor environmental conditions like temperature and wind speed in turbulent free-space channels.

Contribution

The work presents a novel mode decomposition assisted machine learning approach for environmental sensing using optical vortex beams, achieving high accuracy in turbulence parameter estimation.

Findings

Measured temperature variations with 0.49°C accuracy

Measured wind speed variations with 0.029 m/s accuracy

Effective environmental monitoring over 36m turbulent channels

Abstract

Atmospheric interaction with light has been an area of fascination for many researchers over the last century. Environmental conditions, such as temperature and wind speed, heavily influence the complex and rapidly varying optical distortions propagating optical fields experience. The continuous random phase fluctuations commonly make deciphering the exact origins of specific optical aberrations challenging. The generation of eddies is a major contributor to atmospheric turbulence, similar in geometric structure to optical vortices that sit at the centre of OAM beams. Decomposing the received optical fields into OAM provides a unique spatial similarity that can be used to analyse turbulent channels. In this work, we present a novel mode decomposition assisted machine learning approach that reveals trainable features in the distortions of vortex beams that allow for effective environmental monitoring. This novel technique can be used reliably with Support Vector Machine regression models to measure temperature variations of 0.49C and wind speed variations of 0.029 m/s over a 36m experimental turbulent free-space channels with controllable and verifiable temperature and wind speed with short 3s measurement. The predictable nature of these findings could indicate the presence of an underlying physical relationship between environmental conditions that lead to specific eddy formation and the OAM spiral spectra.