This article introduces an innovative procedure integrating chromatic dispersion compensation (CDC) and sliding window methodology for ongoing signal processing in optical communications. Our strategy notably elevates the effectiveness of Nonlinear Fourier Transform (NFT) processing.
Linear and non-linear propagation of ultrashort pulses in a seven-core fiber was investigated experimentally and numerically in a normal dispersion regime. We observed non-uniform coupling conditions between different cores that may be the result of a random refractive index deviation. It was characterized by measurements of the power distribution and FROG traces at the output of a multicore fiber. The cores were excited by a spatial light modulator using the weighted Gerchberg-Saxton algorithm to generate phase masks. It allows us to switch-on any combination without manual alignment of the experimental setup. Finally, as the input power increased, a nonlinear coupling was observed between the selected cores, similar to a saturable absorber. So we believe that such a device could be useful for a development of high-power ultrashort fiber lasers and pulse shaping applications.
In this work, we demonstrate that the high-accuracy computation of the continuous nonlinear spectrum can be performed by using artificial neural networks. We propose the artificial neural network (NN) architecture that can efficiently perform the nonlinear Fourier (NF) optical signal processing. The NN consists of sequential convolution layers and fully connected output layers. This NN predicts only one component of the continuous NF spectrum, such that two identical NNs have to be used to predict the real and imaginary parts of the reflection coefficient. To train the NN, we precomputed 94035 optical signals. 9403 signals were used for validation and excluded from training. The final value of the relative error for the entire validation dataset was less than 0.3%. Our findings highlight the fundamental possibility of using the NNs to analyze and process complex optical signals when the conventional algorithms can fail to deliver an acceptable result.
We demonstrated how the nonlinear Fourier transform based on the Zakharov-Shabat spectral problem can be used to characterise coherent structures in dissipative systems. We consider as a particular, albeit important practical example model equation that is widely used to analyse laser radiation and demonstrate that dissipative solitons can be described by a limited number of degrees of freedom { discrete eigenvalues. Our approach can be applied for signal processing in a number of optical systems, from lasers to micro-resonators.
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