0000000000771692

AUTHOR

G. Granger

Highly efficient few-mode spatial beam self-cleaning at 15µm

We experimentally demonstrate that spatial beam self-cleaning can be highly efficient when obtained with a few-mode excitation in graded-index multimode optical fibers. By using 160 ps long, highly chirped (6 nm bandwidth at -3dB) optical pulses at 1562 nm, we demonstrate a one-decade reduction of the power threshold for spatial beam self-cleaning, with respect to previous experiments using pulses with laser wavelengths at 1030-1064 nm. Self-cleaned beams remain spatio-temporally stable for more than a decade of their peak power variation. The impact of input pulse temporal duration is also studied.

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Spatio-Temporal Beam Mapping for Studying Nonlinear Dynamics in Graded Index Multimode Fiber

We experimentally demonstrate high-resolution mapping of the spatio-temporal dynamics of the beam cleaning process in graded index multimode fibers. This high-resolution characterization reveals the time-dependent nature of the beam self-cleaning process.

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Kerr beam self-cleaning in the telecom band

Multimode graded index (GRIN) fibers received a renewed interest in recent years, in particular for the development of new laser sources [1]. In many cases, the use of GRIN fibers is limited by multimodal propagation, leading to a spatially modulated intensity distribution (speckles) at the fiber output. Recent studies have found that quasi-single mode propagation can be recovered in GRIN fibers by the so-called Kerr self-cleaning effect [2]. It consists in the spontaneous recovery of the spatial beam quality, without any frequency shift [2] (as opposed to, e.g., Raman beam self-cleaning [3]). This nonlinear process was only observed so far at laser wavelengths around 1 μm, for peak power l…

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Experimental evidence of the real multimode nature of geometric parametric instability

We show experimentally that geometric parametric instability in graded-index multimode fibers is composed by several multimode spectral components. The experimental observation is obtained by using a new 3D technique of high-resolution spatial and spectral analysis.

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