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Soliton gas in optical fiber experiments: nonlinear Fourier transform of the noise-induced modulational instability

Published online by Cambridge University Press:  06 February 2026

Alexandre Lebel
Affiliation:
Univ. Lille, CNRS, UMR 8523—PhLAM—Physique des Lasers Atomes et Molécules, F-59 000 Lille, France
Giacomo Roberti
Affiliation:
School of Engineering, Physics and Mathematics, Northumbria University, Newcastle upon Tyne, NE1 8ST, UK
Stephane Randoux
Affiliation:
Univ. Lille, CNRS, UMR 8523—PhLAM—Physique des Lasers Atomes et Molécules, F-59 000 Lille, France
Thibault Bonnemain
Affiliation:
Univ. Lille, CNRS, UMR 8523—PhLAM—Physique des Lasers Atomes et Molécules, F-59 000 Lille, France Laboratoire de Physique Théorique et Modélisation, CNRS UMR 8089, CY Cergy Paris Université, Cergy-Pontoise Cedex 95302, France
Francois Copie
Affiliation:
Univ. Lille, CNRS, UMR 8523—PhLAM—Physique des Lasers Atomes et Molécules, F-59 000 Lille, France
Gennady El
Affiliation:
School of Engineering, Physics and Mathematics, Northumbria University, Newcastle upon Tyne, NE1 8ST, UK
Pierre Suret*
Affiliation:
Univ. Lille, CNRS, UMR 8523—PhLAM—Physique des Lasers Atomes et Molécules, F-59 000 Lille, France
*
Corresponding author: Pierre Suret; Email: Pierre.Suret@univ-lille.fr
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Abstract

We report the experimental measurement of the density of states (DOS) associated with the soliton gas emerging during the development of the noise-induced modulation instability (MI) in optical fibres. By employing a time-lens-based heterodyne detection technique (SEAHORSE), we reconstruct the complex optical field and compute its nonlinear discrete spectrum within the framework of the inverse scattering transform. Our results show that, at early stages of the MI, the DOS matches the Weyl distribution predicted for an ‘ideal’ critically dense soliton gas, thereby confirming the relevance of the SG description for this nonlinear random wave regime. At larger effective propagation distances, we observe a progressive deformation of the DOS in the complex plane. We compare these observations with numerical simulations of a generalised nonlinear Schrödinger equation that includes losses, third-order dispersion and stimulated Raman scattering (SRS). Our simulations reproduce the main experimental trends and demonstrate that SRS is the dominant mechanism responsible for the spectral deformation. These findings highlight the need to extend the kinetic theory of soliton gas beyond purely integrable evolutions. In particular, our results call for a generalised kinetic equation (or generalised hydrodynamics description) that accounts for weak non-integrable perturbations such as SRS.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2026. Published by Cambridge University Press.
Figure 0

Figure 1. Principle of the experimental setup. A continuous-wave (cw) laser is chopped by an acousto-optic modulator (AOM) and amplified by an erbium-doped fibre amplifier (EDFA). The resulting long optical pulse of duration $T_{\mathrm{exp}} = 36~\mathrm{ns}$ is launched into a single-mode fibre operating in the anomalous-dispersion (focusing) regime. Spontaneous modulation instability arises from the intrinsic noise present on the smooth background of the pulse. Both the initial pulse and the ensuing complex field dynamics at the fibre output are captured in a single shot using a heterodyne digital holography technique (SEAHORSE) [33, 49]. Due to the finite duration of the chirped pump pulse in the time-lens based SEAHORSE, only a central temporal window of the signal, with duration $T_{0} \approx 175~\mathrm{ps}$, is recorded.

Figure 1

Figure 2. Typical intensity and phase dynamics recorded using the SEAHORSE technique (physical units). The left column shows the initial optical field launched into the fibre, while the right column displays the fully developed modulation instability (MI) observed at the fibre output ($\langle P_0\rangle=6.1$W, $L_{lab}=1$km). The raw SEAHORSE output consists of 2D fringe patterns from interference. (a,d) Raw interferometric data recorded over a temporal window of duration $T_0 \sim 175$ ps. Data processing allows for the reconstruction of the ultrafast temporal dynamics of both the phase and amplitude of the optical field in physical units: (b,e) intensity profiles at the input and output of the fibre, respectively; (c,f) corresponding phase profiles.

Figure 2

Figure 3. Single-shot experimental measurements of the phase and amplitude of complex optical fields using the SEAHORSE technique (normalised units). The intensity $|\psi|^2$, time $t$ and propagation distance $L$ are normalised according to Eq. (4). Normalised intensity (blue) and phase (red) profiles are shown. (a) Complex optical field at the fibre input (initial condition). (b–d) Complex optical fields after propagation through a 1 km single-mode fibre (SMF28), with $L_{lab} = 1$ km. The average injected powers are: (b) 3.05 W ($L_{lab} \approx 4L_{nl}$), (c) 3.85 W ($L_{lab} \approx 5L_{nl}$) and (d) 6.1 W ($L_{lab} \approx 8L_{nl}$).

Figure 3

Figure 4. Discrete IST spectra corresponding to the fields shown in Fig. 3. (a) IST spectrum of the initial box-shaped field prior to propagation, corresponding to Fig. 3(a). (b–d) IST spectra associated with the propagated fields shown in Fig. 3(b–d), respectively. The injected average powers are: (b) $\langle P_0\rangle=3.05$ W ($L_{lab}\approx 4L_{nl}$), (c) $\langle P_0\rangle=3.85$ W ($L_{lab}\approx 5L_{nl}$) and (d) $\langle P_0\rangle=6.1$ W ($L_{lab}\approx 8L_{nl}$).

Figure 4

Figure 5. 2D density plots of IST eigenvalues in the complex plane. The colour maps represent the base-10 logarithm of the probability density function (DOS) of the discrete IST eigenvalues $\lambda$, with $\text{Re}(\lambda)$ on the horizontal axis and $\text{Im}(\lambda)$ on the vertical axis. The first row corresponds to experimental measurements (EXP). Other rows correspond to different models [see Eq. (6)]: NLSE simulations with linear losses only (NLSE), with losses and third-order dispersion (NLSE2) and with losses, third-order dispersion and stimulated Raman scattering (NLSE3). Column (a) shows the initial condition, i.e., before propagation. Columns (b–d) show the DOS after propagation through 1 km of single-mode fibre, for three different input powers: (b) $P_0 = 3.05$ W ($L_{lab} \approx 4L_\mathrm{nl}$i.e.$L\approx 2$), (c) $P_0 = 3.85$ W ($L_{lab} \approx 5L_\mathrm{nl}$i.e.$L\approx 2.5$)), (d) $P_0 = 6.1$ W ($L_{lab} \approx 8L_\mathrm{nl}$i.e.$L\approx 4$)).

Figure 5

Figure 6. Probability density function (PDF) of the real part of the IST eigenvalues, $PDF(\text{Re}(\lambda))$, as a function of $\xi = \text{Re}(\lambda)$. Experimental results (blue) are compared with numerical simulations (orange) based on the full NLSE3 model (6), which includes linear losses, third-order dispersion and stimulated Raman scattering. (a) PDFs for the initial condition corresponding to the box-shaped potential before propagation in the optical fibre. (b–d) PDFs obtained after propagation through 1 km of single-mode fibre (SMF28), shown for both experimental measurements (blue) and numerical simulations (orange). The injected average powers are: (b) $P_0 = 3.05$ W ($L_{\mathrm{lab}}\approx4L_{\mathrm{nl}}$), (c) $P_0 = 3.85$ W ($L_\mathrm{lab}=5L_{\mathrm{nl}}$), (d) $P_0 = 6.1$ W ($L_\mathrm{lab}=8L_{\mathrm{nl}}$).

Figure 6

Figure 7. Probability density function (PDF) of the imaginary part of the IST eigenvalues, $PDF(\text{Im}(\lambda))$, as a function of $\eta = \text{Im}(\lambda)$. Experimental data (blue) are compared with numerical simulations (orange) based on the full NLSE3 model, which includes linear losses, third-order dispersion and stimulated Raman scattering. The dashed line represents the Weyl’s distribution given by Eq. (3). (a) PDFs for the initial condition corresponding to the box-shaped potential before propagation in the optical fibre. (b–d) PDFs obtained after propagation through 1 km of single-mode fibre (SMF28), shown for both experimental measurements (blue) and numerical simulations (orange). The injected average powers are: (b) $P_0 = 3.05$ W ($L_\mathrm{lab}\approx4L_{\mathrm{nl}}$), (c) $P_0 = 3.85$ W ($L_\mathrm{lab}=5L_{\mathrm{nl}}$), (d) $P_0 = 6.1$ W ($L_\mathrm{lab}=8L_{\mathrm{nl}}$).

Figure 7

Figure A1. Impact of fluctuations on the IST spectrum (numerical simulations). The Probability Density Functions (PDF) of (a) the real part and (b) the imaginary part of the IST eigenvalues are shown for the two possible normalisations: ideal normalisation (blue) and experimental-like normalisation (orange). Simulations include input power fluctuations (Gaussian distribution with root mean square $\sigma \approx 0.058$). $\langle P_0\rangle=6$ W.

Figure 8

Figure B1. Probability density function (PDF) of the optical power. The PDF of $ \frac{|\psi|^{2}}{\langle |\psi|^{2} \rangle} $ measured experimentally at the fibre output is shown in blue. The PDF computed from numerical simulations of the gNLSE with losses only (‘NLSE’ in Eq. (6)) is shown in black. The PDF computed from simulations of the full gNLSE including all higher-order terms (‘NLSE2+NLSE3’ in Eq. (6)) is shown in red. The dashed line denotes the exponential reference $\exp (-|\psi|^{2}/\langle |\psi|^{2} \rangle$).