Controlling spatiotemporal nonlinearities in multimode fibers with deep neural networks

Teğin, Uğur; Rahmani, Babak; Kakkava, Eirini; Borhani, Navid; Moser, Christophe

doi:10.1063/1.5138131

Cited by 57 publications

(32 citation statements)

References 31 publications

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“…To create a significant change, we consider the first six modes with equal initial energy distributions (total peak power of 200 W among all the modes). Indeed, such a configuration can be achieved using a spatial light modulator (SLM) [18]. We considered the same GRIN-F and STEP-F parameters.…”

Section: Numerical Setup and Resultsmentioning

confidence: 99%

Spatiotemporal Evolutions of Similariton Pulses in Multimode Fibers with Raman Amplification

Graini

Ortaç

2021

Photonics

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This paper aims to pave the way towards the demonstration of spatiotemporal similariton pulses’ evolution in passive multimode fibers with Raman amplification. We numerically present this issue in graded-index and step-index multimode fibers and provide a first look at the complex spatiotemporal dynamics of similariton pulses. The results showed that the similariton pulses could be generated in both multimode fibers. The temporal and spectral evolution of the pulses can be characterized as parabolic shapes with linear chirp and kW peak power. By compressing these, high-energy femtoseconds pulses can be obtained, starting initial picosecond pulses. A spatial beam profile could be preserved in both multimode fibers with the most energy coupled to the fundamental mode. Specifically, the similariton pulses’ generation with Raman amplification in a graded-index multimode fiber improves the spatial beam self-cleaning process under the different initial modes’ excitation. The observation of a new beam self-cleaning process is another attractor feature of propagation in graded-index multimode fibers.

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Section: Numerical Setup and Resultsmentioning

confidence: 99%

Spatiotemporal Evolutions of Similariton Pulses in Multimode Fibers with Raman Amplification

Graini

Ortaç

2021

Photonics

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“…This can be particularly useful in multimode fibre systems where spatiotemporal coupling increases dramatically the parameter space and complexity of nonlinear propagation dynamics. The potential of machine learning in this case was recently demonstrated with experiments tailoring supercontinuum generation in a graded index fibre through control of the injected spatial beam profile via a neural-network driven spatial light modulator [81].…”

Section: Multidimensional Systemsmentioning

confidence: 99%

Machine learning and applications in ultrafast photonics

et al. 2020

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Recent years have seen the rapid growth and development of the field of smart photonics, where machine learning algorithms are being matched to optical systems to add new functionalities and to enhance performance. An area where machine learning shows particular potential to accelerate technology is the field of ultrafast photonics -the generation and characterization of light pulses, the study of light-matter interactions on short timescales, and high-speed optical measurements. Our aim here is to highlight a number of specific areas where the promise of machine learning in ultrafast photonics has already been realized, including the design and operation of pulsed lasers, and the characterization and control of ultrafast propagation dynamics. We also consider challenges and future areas of research.

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“…There are two main types of optical fiber, the multimode, for which there are different modes of light propagation within the fiber core, and the single-mode, in which there is only one mode of propagation of the light, the straight line way. In multimode optical fibers [ 26 ], there are two types of fiber, the step-index and the gradient index. The step-index optical fiber has a very large core with the disadvantage of a strong attenuation in the order of 10 dB/km.…”

Section: Telecommunication Systems In An Isolated and Constrained Environmentmentioning

confidence: 99%

State of the Art of Telecommunication Systems in Isolated and Constrained Areas

Ferrier

Ibrahim

Issa

et al. 2021

Sensors

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Smart objects are deployed globally, contributing to improved communications and the growth of industrial systems’ performances. Unfortunately, isolated territories are generally excluded from this progress. Remote areas in Canada are no exception. Thus, about two hundred thousand people are living in isolated regions in Canadian territory. The development of these communities is slowed down not only by an outdated energy supply, but they are also dependent on telecommunication systems not fully deployed in those regions, thus contributing to the amplification of those populations’ isolation. Furthermore, the magnetic field in some regions of the planet and very often in isolated areas undergoes partial or total absorption, known as white areas, making the propagation of the signal very delicate. As a part of this article, a state of the art of telecommunication solutions available in an isolated environment is applied with a critical analysis based on several criteria. It shows the ability to use an original approach based on a captive balloon. Despite the proposed solution’s feasibility, several challenges need to be addressed before formally adopting it. These challenges include: (i) controlling the height of the balloon; (ii) stabilization of the balloon; and (iii) powering the system. The list of references given at the end of the paper should offer aids for the industry and for researchers working in this field.

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Controlling spatiotemporal nonlinearities in multimode fibers with deep neural networks

Cited by 57 publications

References 31 publications

Spatiotemporal Evolutions of Similariton Pulses in Multimode Fibers with Raman Amplification

Spatiotemporal Evolutions of Similariton Pulses in Multimode Fibers with Raman Amplification

Machine learning and applications in ultrafast photonics

State of the Art of Telecommunication Systems in Isolated and Constrained Areas

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