Title: Photon-starved polarimetry via functional classical shadows Show Chinese title

Title: 通过功能经典阴影的光子匮乏偏振测量

Abstract: Polarimetry and optical imaging techniques face challenges in photon-starved scenarios, where the low number of detected photons imposes a trade-off between image resolution, integration time, and sample sensitivity. Here we introduce a quantum-inspired method, functional classical shadows, for reconstructing a polarization profile in the low photon-flux regime. Our method harnesses correlations between neighbouring datapoints, based on the recent realisation that machine learning can estimate multiple physical quantities from a small number of non-identical samples. This is applied to the experimental reconstruction of polarization as a function of the wavelength. Although the quantum formalism helps structuring the problem, our approach suits arbitrary intensity regimes. Show Chinese abstract

Abstract: 偏振测量和光学成像技术在光子匮乏的场景中面临挑战，其中检测到的光子数量较少，导致图像分辨率、积分时间和样品灵敏度之间存在权衡。 在这里，我们介绍了一种受量子启发的方法，功能经典阴影，用于在低光子通量范围内重建偏振剖面。 我们的方法利用相邻数据点之间的相关性，基于最近的认识，即机器学习可以从少量非相同样本中估计多个物理量。 这是应用于波长函数的偏振实验重建。 尽管量子形式有助于构建问题，但我们的方法适用于任意强度范围。