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We deploy a neural network to predict the spectro-temporal evolution of simple sinusoidal temporal modulations upon propagation in a nonlinear dispersive fibre. Thanks to the speed of the neural network, we can efficiently scan the input parameter space for the generation of on-demand frequency combs or the occurrence of substantial spectral/temporal focusing.

Inductively coupled plasma chemical vapor deposition was used to obtain thin films of siliconrich silicon nitride with a refractive index of 2.44 at optical telecommunications wavelength. The resulting layer was patterned into a 1.6 μm wide waveguide and tested for its nonlinear behavior using a 90-fs all-fiber laser centered at 1630 nm. A significant spectral broadening is demonstrated with a supercontinuum generation from 1300 nm to 1985 nm. Simulations are in fair agreement with the experiments, assuming a nonlinear index of 2 x 10-18 m2/W.

We demonstrate that coupled waveguides systems can be operated in the so called non-adiabatic regime. In this regime, light can undergo transitions between different steady states in a manner analogue to the transition of an electron between energy levels. This approach contrasts with the previous concepts in integrated photonics that rely exclusively on the adiabatic control of the flow of light. We show in particular that abrupt changes of the control parameters are not required to create such non-adiabatic transitions. The constraint for adiabaticity being lifted, light can now be manipulated optimally. And the analogy between the time evolution of a quantum system and the propagation of light in a waveguides array can be pushed one step further.

A nonlinear interaction of waves in a dispersive medium manifests itself in a four-wave mixing process that can be described as an evolution of waves’ parameters on a phase plane in a form of closed orbits. Here we propose a method to control these trajectories and to switch from one state to another in an optimal manner by implementing an abrupt change of the average power. The method is confirmed experimentally by the reconstruction of a fundamental four-wave mixing dynamics in an idealized model using iterative propagation in a short segment of fiber.

We report the first application of the Machine Learning technique of data-driven dominant balance to optical fiber noise-driven Modulation Instability, with the aim to automatically identify local regions of dispersive and nonlinear interactions governing the dynamics. We first consider the analytical solutions of Nonlinear Schrödinger Equation – solitons on finite background – where it is shown that dominant balance distinguishes two particularly different dynamical regimes: one where the nonlinear process is dominating the dispersive propagation, and one where nonlinearity and second order dispersion act together driving the localization of breathers. By means of numerical simulations, we then analyse the spatio-temporal dynamics of noise-driven Modulation Instability and demonstrate that data-driven dominant balance can successfully identify the associated dominating physical regimes even within the turbulent dynamics.

We review our recent work on the use of genetic algorithms to control non-stationary nonlinear wave dynamics in ultrafast fibre lasers, including the generation of breathing-soliton dynamics with controlled characteristics, the disclosure of the fractal dynamics of breathers, and the generation of rogue waves with controlled intensity.

The conservation of spectral asymmetry is a fundamental feature of the ideal four‐wave mixing process as it exists in a medium combining quadratic chromatic dispersion and third‐order nonlinearity. The robustness of this invariant in an experimental configuration where the excitation conditions of an optical fiber are sequentially updated, mimicking infinite propagation is tested in this paper. This theoretical and experimental study reveals the high sensitivity of the asymmetry to very slight deviations from the ideal case, and the idealized system behaves as an intermediate case between the ideal case of noncascaded four‐wave mixing and propagation in a system governed by the nonlinear Schrödinger equation is shown. [ABSTRACT FROM AUTHOR]

Extreme wave events or rogue waves (RWs) are both statistically rare and of exceptionally large amplitude. They are observed in many complex systems ranging from oceanic and optical environments to financial models and Bose–Einstein condensates. As they appear from nowhere and disappear without a trace, their emergence is unpredictable and non‐repetitive, which makes them particularly challenging to control. Here, the use of genetic algorithms (GAs), which are exclusively designed for searching and optimizing stationary or repetitive processes in nonlinear optical systems, is extended to the active control of extreme events in a fiber laser cavity. Feeding real‐time spectral measurements into a GA controlling the electronics to optimize the cavity parameters, the wave events are able to be triggered in the cavity that have the typical statistics of RWs in the frequency domain. The intensity of the induced RWs can also be tailored. This accurate control enables the generation of optical RWs with a spectral peak intensity 32.8 times higher than the significant intensity threshold. A rationale is proposed and confirmed by numerical simulations of the laser model for the related frequency up‐ and downshifting of the optical spectrum that are experimentally observed. [ABSTRACT FROM AUTHOR]

Fifty years ago, the concept of solitons in optical fibres was proposed numerically by F. Tappert and A. Hasegawa from Bell Labs. Seven years later in 1980, experiments confirmed that dispersion and the Kerr nonlinearity could combine to yield a coherent ultrashort pulse able to propagate without distortion. The implications of this discovery go well beyond the sector of telecommunications as initially suggested, and solitons now play a major role in modern ultrafast nonlinear photonics. [ABSTRACT FROM AUTHOR]

We numerically study the temporal patterns that emerge upon the propagation of one or two π phase jumps in a nonlinear optical fiber. Both normal and anomalous regimes of dispersion are considered. The analytical derivation of linear patterns based on Fresnel’s integrals provides some clues to better understand the properties of the resulting coherent structures.

We experimentally demonstrate the generation of pulse trains with repetition rates of 40-GHz, 80 GHz and 200 GHz. Our approach is based on the nonlinear compression of besselon pulses in a highly-nonlinear fiber with normal dispersion. The pulses are of high quality, with a subpicosecond duration.

We study the impact of temporal randomness on the formation of vectorial dispersive shock-waves that emerge due to the interaction of a partially coherent probe wave co-propagating together with an orthogonally polarized intense short pulse. Experiments carried out in a normally dispersive optical fiber demonstrate that the lack of coherence of the probe landscape acts as a strong diffusive term, which is able to hamper or inhibit the vectorial shock formation.

We experimentally demonstrate the generation of temporal pulse doublets from the propagation of initial super-Gaussian waveforms in an optical fiber with anomalous dispersion. The nonlinear focusing dynamics leads to picosecond structures that are characterized both in amplitude and phase. Their close-to-Gaussian Fourier-transform limited shape is found in excellent agreement with numerical simulations. This single-stage reshaping scheme is energy efficient, can sustain GHz repetition rates and temporal compression factors around 10 are demonstrated.