@inproceedings{0a812b344d394984a007da2d53b7f5ab,
title = "SLM phase mask optimization for fiber OAM mode excitation",
abstract = "Fiber orbital angular momentum (OAM) modes can be employed in mode-division multiplexing to increase the channel capacity in optical communication systems. Over the years, several experiments to excite high-purity OAM modes by using one phase-only spatial light modulator (SLM) have been conducted. Since phase-only SLMs are intrinsically imperfect for this purpose due to the impossibility to simultaneously modulate both amplitude and phase in the light source, optimal phase masks need to be generated by iterative algorithms. However, if the state of every pixel in the mask is an unknown of the problem, the computational cost is extremely high. The system circular symmetry can be exploited to overcome this issue. Here, for the first time, this approach is implemented and a simple machine learning algorithm is developed to calculate optimal phase masks with a low number of unknowns and iterations. Simulated and experimental results show that the developed technique is capable of exciting high-purity OAM modes. ",
keywords = "Orbital angular momentum of light, Fiber mode excitation, Gradient descent, Spatial light modulator, Machine learning",
author = "Antonio Astorino and Ba{\~n}as, \{Andrew Rafael\} and Karsten Rottwitt and Jesper Gl{\"u}ckstad",
year = "2019",
doi = "10.1117/12.2507424",
language = "English",
volume = "10935",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE - International Society for Optical Engineering",
editor = "Jesper Gl{\"u}ckstad and Andrews, \{David L. \} and \{Galvez \}, \{Enrique J.\}",
booktitle = "Proceedings of SPIE",
note = "SPIE Photonics West OPTO 2019 ; Conference date: 02-02-2019 Through 07-02-2019",
}