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Learning and Avoiding Disorder in Multimode Fibers

Maxime W. Matthès, Yaron Bromberg, Julien de Rosny, and Sébastien M. Popoff
Phys. Rev. X 11, 021060 – Published 21 June 2021
Physics logo See Focus story: Optical Fiber Modes Resist Deformations
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Abstract

Multimode optical fibers (MMFs) have gained renewed interest in the past decade, emerging as a way to boost optical communication data rates in the context of an expected saturation of current single-mode fiber-based networks. They are also attractive for endoscopic applications, offering the possibility to achieve a similar information content as multicore fibers, but with a much smaller footprint, thus reducing the invasiveness of endoscopic procedures. However, these advances are hindered by the unavoidable presence of disorder that affects the propagation of light in MMFs and limits their practical applications. We introduce here a general framework to study and avoid the effect of disorder in wave-based systems and demonstrate its application for multimode fibers. We experimentally find an almost complete set of optical channels that are resilient to disorder induced by strong deformations. These deformation principal modes are obtained by only exploiting measurements for weak perturbations harnessing the generalized Wigner-Smith operator. We explain this effect by demonstrating that, even for a high level of disorder, the propagation of light in MMFs can be characterized by just a few key properties. These results are made possible thanks to a precise and fast estimation of the modal transmission matrix of the fiber which relies on a model-based optimization using deep learning frameworks.

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  • Received 25 November 2020
  • Revised 29 April 2021
  • Accepted 20 May 2021

DOI:https://doi.org/10.1103/PhysRevX.11.021060

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.

Published by the American Physical Society

Physics Subject Headings (PhySH)

General PhysicsAtomic, Molecular & Optical

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Optical Fiber Modes Resist Deformations

Published 21 June 2021

A machine-learning approach quickly characterizes an optical fiber, identifying transmission channels that aren’t affected by deformation.

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Authors & Affiliations

Maxime W. Matthès1, Yaron Bromberg2, Julien de Rosny1, and Sébastien M. Popoff1,*

  • 1Institut Langevin, ESPCI Paris, PSL University, CNRS, France
  • 2Racah Institute of Physics, The Hebrew University of Jerusalem, Israel

  • *Corresponding author. sebastien.popoff@espci.psl.eu

Popular Summary

Multimode fibers are large-core optical fibers that hold great promise for high-data-rate optical communications and endoscopic applications, offering a smaller footprint and less-invasive alternative to current systems. But like all wave-based communication systems, the fibers are particularly sensitive to perturbations. Unavoidable changes of the environment or modification of the geometry of the system alters the response of the system, hindering the reconstruction of the information. We propose a way to use multimode fibers that is insensitive to perturbations.

Our approach relies on a new approach to quickly and accurately measure a fiber’s transmission matrix, a mathematical characterization of how light propagates through the system. This measurement reveals a complete set of channels that are not affected by deformation of the fiber. We show that these channels are resilient to disorder induced by strong deformations, even though they are obtained by only exploiting measurements for weak perturbations. We explain this resilience by showing that, even for a high level of disorder, the way the propagation of light in large-core fibers is affected can be characterized by only a few key properties.

This approach could have an important impact on imaging and telecommunication applications where the environment typically changes in real time, disturbing the signal. Using perturbation-invariant channels to convey information or images would allow for broadening the range of those applications.

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Vol. 11, Iss. 2 — April - June 2021

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