Phase shaping of dual-pumped Brillouin-Kerr frequency combs.

We investigate the spectral phase characteristics of dual-pumped Kerr frequency combs generated in a bichromatic Brillouin fiber laser architecture with normal dispersion, producing square-like pulse profiles. Using a pulse shaper, we measure the relative phase between the pump Stokes and adjacent lines, revealing a symmetric phase relationship. Our results highlight good phase coherence of the comb. By manipulating spectral amplitudes and phases, we demonstrate the transformation into various optical waveforms. The stability of our low-noise frequency comb ensures reliable performance in practical settings.

Analysis of the dispersive Fourier transform dataset using dynamic mode decomposition: evidence of multiple vibrational modes and their interplay in a three-soliton molecule.

We demonstrate that the dynamic mode decomposition technique can effectively reduce the amount of noise in the dispersive Fourier transform dataset and allow for finer quantitative analysis of the experimental data. We therefore show that the oscillation pattern of a soliton molecule actually results from the interplay of several elementary vibration modes.

Phase space topology of four-wave mixing reconstructed by a neural network.

The dynamics of ideal four-wave mixing in optical fiber is reconstructed by taking advantage of the combination of experimental measurements together with supervised machine learning strategies. The training data consist of power-dependent spectral phase and amplitude recorded at the output of a short fiber segment. The neural network is shown to be able to accurately predict the nonlinear dynamics over tens of kilometers, and to retrieve the main features of the phase space topology including multiple Fermi-Pasta-Ulam recurrence cycles and the system separatrix boundary.

Data-driven model discovery of ideal four-wave mixing in nonlinear fibre optics.

We show using numerical simulations that data driven discovery using sparse regression can be used to extract the governing differential equation model of ideal four-wave mixing in a nonlinear Schrödinger equation optical fibre system. Specifically, we consider the evolution of a strong single frequency pump interacting with two frequency detuned sidebands where the dynamics are governed by a reduced Hamiltonian system describing pump-sideband coupling. Based only on generated dynamical data from this system, sparse regression successfully recovers the underlying physical model, fully capturing the dynamical landscape on both sides of the system separatrix. We also discuss how analysing an ensemble over different initial conditions allows us to reliably identify the governing model in the presence of noise. These results extend the use of data driven discovery to ideal four-wave mixing in nonlinear Schrödinger equation systems.