湍流大气环境中分形结构光束的光学解复用
Optical demultiplexing of fractal-structured beams in turbulent atmospheric environments
AI总结：
本研究模拟了高湍流环境下分形编码光束的光学解复用，仅用简单阈值算法和部分光束即实现了低误码率，证实了该方法在复杂大气中的鲁棒性。
摘要：
当信息以自相似分形光束图样在空间上重复时，仅需部分衍射光束即可重建核心数据。分形编码方案的独特之处在于，图像解复用过程在一级近似下可轻松通过光学方式完成。在先前的工作中，我们通过实验和数值研究了分形编码光束及其在无附加湍流条件下的中场和远场传播。在此，我们展示了高湍流（$C_n^2 \geq 10^{-14}$ m$^{-2/3}$）下分形编码光束的初步模拟，实现了 $10^{-3}$ 的良好误码率。鉴于以下条件，这些结果令人瞩目：展示了低分形阶的数据；使用了简单的阈值算法（即未使用机器学习）；且仅需偏离光轴的三分之一光束。更鲁棒的信道编码与更高的分形阶、更大的收集面积和更高的核心奇异值分解熵相关。
英文摘要：
When information is spatially repeated in self-similar fractal beam patterns, only a portion of the diffracted beam is needed to reconstruct the kernel data. What is unique to a fractal-encoding scheme is that the image demultiplexing process can be, to a first approximation, easily performed optically. In prior work, we experimentally and numerically study fractal-encoded optical beams and their mid- and far-field propagation without added turbulence. Here, we present preliminary simulations of fractal-encoded beams with high turbulence ($C_n^2 \geq 10^{-14}$ m$^{-2/3}$) where we achieve respectable bit error rates of $10^{-3}$. These results are impressive given that: data with low fractal orders is shown, simple threshold-algorithms are used (i.e., no machine learning), and only a third of the beam, off-axis, is needed. More robust channel encoding is associated with increased fractal orders, larger collection areas, and higher kernel singular value decomposition entropy.
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