We demonstrate light pulse combining and pulse compression using a continuous-discrete nonlinear system implemented in a multi-core fiber (MCF). It is shown that the pulses initially injected into all of the cores of a ring MCF are combined by nonlinearity into a small number of cores with simultaneous pulse compression. We demonstrate the combining of 77% of the energy into one core with pulse compression over 14× in a 20-core MCF. We also demonstrate that a suggested scheme is insensitive to the phase perturbations. Nonlinear spatio-temporal pulse manipulation in multi-core fibers can be exploited for various applications, including pulse compression, switching, and combining.

Using the cubic Ginzburg-Landau equation as an example, we demonstrate how the inverse scattering transform can be applied to characterize coherent structures in dissipative nonlinear systems. Using this approach one can reduce the number of the effective degrees of freedom in the system when the dynamic is dominated by the coherent structures, even if they are embedded in the dispersive waves and demonstrate unstable behavior.

We demonstrate numerically light pulse combining and pulse compression using wave collapse (self-focusing) energy localization dynamics in a continuous-discrete nonlinear system, as implemented in a multicore fiber (MCF) using 1D and 2D core distribution designs. Large-scale numerical simulations were performed to determine the conditions of the most efficient coherent combining and compression of pulses injected into the considered MCFs. We demonstrate the possibility of combining in a single core 90% of the total energy of pulses initially injected into all cores of a 7-core MCF with a hexagonal lattice. A pulse compression factor of about 720 can be obtained with a 19-core ring MCF.

We propose two finite-difference algorithms of fourth order of accuracy for solving the initial problem of the Zakharov-Shabat system. Both schemes have the exponential form and conserve quadratic invariant of Zakharov-Shabat system. The second scheme contains the spectral parameter in exponent only and allows to apply the fast computational algorithm.