Julius-Maximilians-Universität Würzburg, D-97070 Würzburg, Germany.
Laboratoire Kastler Brossel, Université Pierre et Marie Curie, Ecole Normale Supérieure, CNRS, Collège de France, F-75005 Paris, France.
Phys Rev Lett. 2021 Jul 23;127(4):043903. doi: 10.1103/PhysRevLett.127.043903.
Accessing subwavelength information about a scene from the far-field without invasive near-field manipulations is a fundamental challenge in wave engineering. Yet it is well understood that the dwell time of waves in complex media sets the scale for the waves' sensitivity to perturbations. Modern coded-aperture imagers leverage the degrees of freedom (d.o.f.) offered by complex media as natural multiplexor but do not recognize and reap the fundamental difference between placing the object of interest outside or within the complex medium. Here, we show that the precision of localizing a subwavelength object can be improved by several orders of magnitude simply by enclosing it in its far field with a reverberant passive chaotic cavity. We identify deep learning as a suitable noise-robust tool to extract subwavelength localization information encoded in multiplexed measurements, achieving resolutions well beyond those available in the training data. We demonstrate our finding in the microwave domain: harnessing the configurational d.o.f. of a simple programmable metasurface, we localize a subwavelength object along a curved trajectory inside a chaotic cavity with a resolution of λ/76 using intensity-only single-frequency single-pixel measurements. Our results may have important applications in photoacoustic imaging as well as human-machine interaction based on reverberating elastic waves, sound, or microwaves.
从远场获取关于场景的亚波长信息而无需侵入性近场操作，这是波动工程中的一个基本挑战。然而，人们已经充分认识到，波在复杂介质中的停留时间决定了波对微扰的敏感程度。现代编码孔径成像仪利用复杂介质提供的自由度（d.o.f.）作为自然复用器，但没有认识到并利用将感兴趣的物体置于复杂介质外部或内部之间的根本区别。在这里，我们表明，通过用混响无源混沌腔将亚波长物体封闭在其远场中，可以将亚波长物体的定位精度提高几个数量级。我们将深度学习识别为一种合适的抗噪工具，用于从复用测量中提取编码的亚波长定位信息，实现的分辨率远远超过训练数据中可用的分辨率。我们在微波领域证明了我们的发现：利用简单可编程超表面的配置自由度，我们使用仅强度单频单像素测量，在混沌腔内沿着弯曲轨迹对亚波长物体进行定位，分辨率为 λ/76。我们的结果可能在光声成像以及基于混响弹性波、声音或微波的人机交互中有重要应用。
