2020
DOI: 10.1364/oe.388526
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Turbulence aberration correction for vector vortex beams using deep neural networks on experimental data

Abstract: The vector vortex beams (VVB) possessing non-separable states of light, in which polarization and orbital angular momentum (OAM) are coupled, have attracted more and more attentions in science and technology, due to the unique nature of the light field. However, atmospheric transmission distortion is a recurring challenge hampering the practical application, such as communication and imaging. In this work, we built a deep learning based adaptive optics system to compensate the turbulence aberrations of the vec… Show more

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Cited by 57 publications
(16 citation statements)
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“…Significantly less work has gone into similar techniques and tools for vector beams. Recent studies have looked into the correction of polarisation errors in vector modes but the application to atmospheric turbulence compensation is still in its infancy [180][181][182][183][184][185][186].…”
Section: Correction Schemesmentioning
confidence: 99%
“…Significantly less work has gone into similar techniques and tools for vector beams. Recent studies have looked into the correction of polarisation errors in vector modes but the application to atmospheric turbulence compensation is still in its infancy [180][181][182][183][184][185][186].…”
Section: Correction Schemesmentioning
confidence: 99%
“…Characterization and manipulation of these vector vortex beams is a subject of study for laser matter interaction experiments [592]. Deep learning algorithms are also applied for turbulence aberration correction for VVBs [593].…”
Section: Literature Survey Of Phase and Polarization Singularitiesmentioning
confidence: 99%
“…Significantly less work has gone into similar techniques and tools for vector beams. Recent studies have looked into the correction of polarisation errors in vector modes but the application to atmospheric turbulence compensation is still in its infancy [160][161][162][163][164][165][166].…”
Section: Correction Schemesmentioning
confidence: 99%