不等强度光源的亚瑞利成像：近量子极限的多参量估计
Sub-Rayleigh Imaging of Unequal-Intensity Sources: Near-Quantum-Limit Multiparameter Estimation
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中文总结 AI 辅助
本文采用SPLICE方法同时估计两个非相干不等强度光源的间距与相对强度，相比直接成像（DI）实现了约6倍性能提升，误差接近量子极限。
中文摘要 AI 辅助
在光学成像中，当两个光源的间距低于瑞利-阿贝极限时，衍射会严重降低传统基于强度的估计方法的性能。近期研究进展表明，利用空间模式解复用（SPADE）可突破这一限制，且已在多个针对两个等强度未知间距光斑的实验中得到验证。当存在多个未知参数时，例如多个具有未知强度和未知间距的不等强度光源，参数间的串扰会使多参量估计问题显著更具挑战性。本文中，我们采用沿边缘相干反演的超分辨位置定位方法（SPLICE），同时估计两个非相干光源的间距和相对强度。我们展示了其相比直接成像（DI）的明显优势：在我们测试的参数范围内，其均方根误差（RMSE）约比量子极限大50%，且相比直接成像（DI）提升了6倍。当间距更小、强度失衡更大且串扰被抑制时，该提升效果会更为显著。
英文摘要
In optical imaging, diffraction strongly degrades the performance of conventional intensity-based estimation once the separation between two sources is below the Rayleigh-Abbe limit. Recent developments showed that this limitation can be surpassed using spatial-mode demultiplexing (SPADE), and this was demonstrated in several experiments for two equal-intensity spots of unknown separation. When there are multiple unknown parameters, as in the case of several unequal sources with unknown intensities and unknown separation, cross-talk among the parameters makes the multi-parameter estimation problem significantly more challenging. In this paper, we adapt super-resolved position localization by inversion of coherence along an edge (SPLICE) to estimate both the separation and relative intensity of two incoherent sources simultaneously. We demonstrate a clear advantage over direct imaging (DI), achieving a root mean squared error (RMSE) approximately $50 \%$ larger than the quantum limit and a sixfold improvement over DI within the range of parameters we tested. This improvement can be even greater for smaller separations and larger intensity imbalances when crosstalk is suppressed.
