Abstract
Deep neural networks have enabled the reconstruction of optical soliton molecules with more complex structures using the real-time spectral interferences obtained by photonic time-stretch dispersive Fourier transformation (TS-DFT) technology. In this paper, we propose to use three kinds of deep convolution networks (DCNs), including VGG, ResNets, and DenseNets, for revealing internal dynamics evolution of soliton molecules based on the real-time spectral interferences. When analyzing soliton molecules with equidistant composite structures, all three models are effective. The DenseNets with layers of 48 perform the best for extracting the dynamic information of complex five-soliton molecules from TS-DFT data. The mean Pearson correlation coefficient (MPCC) between the predicted results and the real results is about 0.9975. Further, the ResNets in which the MPCC achieves 0.9906 also has the better ability of phase extraction than VGG which the MPCC is about 0.9739. The general applicability is demonstrated for extracting internal information from complex soliton molecule structures with high accuracy. The presented DCNs-based techniques can be employed to explore undiscovered mechanisms underlying the distribution and evolution of large numbers of solitons in dissipative systems in experimental research.
Highlights
Soliton molecules are localized soliton bound states formed by self-organized dissipative soliton through subtle interaction mechanisms [1]
In order to solve the internal dynamics of complex soliton molecules, we introduced artificial intelligence combining with time-stretch dispersive Fourier transformation (TS-DFT)
Comparing the VGG, residual networks (ResNets), and DenseNet models, we demonstrate their effectiveness on TS-DFT interference spectra of more complex five-soliton molecules datasets with equal spacing pairs
Summary
Soliton molecules are localized soliton bound states formed by self-organized dissipative soliton through subtle interaction mechanisms [1]. TS-DFT observe various rare events and transient phenomena including soliton buildup [6,7], soliton pulsation [13,14], soliton explosion [15,16], and soliton molecules [2,3,4,9,10]. It appears tremendous potential in simulating dynamic process of various complex molecules. A discrete Fourier transform is performed on the interference fringes to obtain the single-shot autocorrelation traces for retrieving the soliton separation and the relative phase in the soliton molecules
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