Article ID Journal Published Year Pages File Type
6888414 Optical Fiber Technology 2014 18 Pages PDF
Abstract
We give an overview of the current status of fiber-based noise-like pulse (NLP) research conducted over the past decade, together with presenting the newly conducted, systematic study on their temporal, spectral, and coherence characteristics in nonlinear polarization rotation (NPR)-based erbium-doped fiber ring cavity configurations. Firstly, our study includes experimental investigations on the characteristic features of NLPs both in the net anomalous dispersion regime and in the net normal dispersion regime, in comparison with coherent optical pulses that can alternatively be obtained from the same cavity configurations, i.e., with the conventional and dissipative solitons. Secondly, our study includes numerical simulations on the formation of NLPs, utilizing a simplified, scalar-field model based on the characteristic transfer function of the NPR mechanism in conjunction with the split-step Fourier algorithm, which offer a great help in exploring the interrelationship between the NLP formation and various cavity parameters, and eventually present good agreement with the experimental results. We stress that if the cavity operates with excessively high gain, i.e., higher than the levels just required for generating coherent mode-locked pulses, i.e., conventional solitons and dissipative solitons, it may trigger NLPs, depending on the characteristic transfer function of the NPR mechanism induced in the cavity. In particular, the NPR transfer function is characterized by the critical saturation power and the linear loss ratio. Finally, we also report on the applications of the fiber-based NLP sources, including supercontinuum generation in a master-oscillator power amplifier configuration seeded by a fiber-based NLP source, as one typical example. We expect that the NLP-related research area will continue to expand, and that NLP-based sources will also find more applications in the future.
Related Topics
Physical Sciences and Engineering Computer Science Computer Networks and Communications
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