Near-field scanning optical microscopy is a powerful technique for imaging below the diffraction limit, which has been extensively used in biomedical imaging and nanophotonics. However, when the electromagnetic fields under measurement are strongly confined, they can be heavily perturbed by the presence of the near-field probe itself. Here, taking inspiration from scattering-cancellation invisibility cloaks, Huygens-Kerker scatterers, and cloaked sensors, we design and fabricate a cloaked near-field probe. We show that, by suitably nanostructuring the probe, its electric and magnetic polarizabilities can be controlled and balanced. As a result, probe-induced perturbations can be largely suppressed, effectively cloaking the near-field probe without preventing its ability to measure. We experimentally demonstrate the cloaking effect by comparing the interaction of conventional and nanostructured probes with a representative nanophotonic structure, namely, a 1D photonic-crystal cavity. Our results show that, by engineering the structure of the probe, one can systematically control its back action on the resonant fields of the sample and decrease the perturbation by >70% with most of our modified probes, and by up to 1 order of magnitude for the best probe, at probe-sample distances of 100 nm. Our work paves the way for non-invasive near-field optical microscopy of classical and quantum nanosystems.

Particle defects are important contributors to yield loss in semi-conductor manufacturing. Particles need to be detected and characterized in order to determine and eliminate their root cause. We have conceived a process flow for advanced defect classification (ADC) that distinguishes three consecutive steps; detection, review and classification. For defect detection, TNO has developed the Rapid Nano (RN3) particle scanner, which illuminates the sample from nine azimuth angles. The RN3 is capable of detecting 42 nm Latex Sphere Equivalent (LSE) particles on XXX-flat Silicon wafers. For each sample, the lower detection limit (LDL) can be verified by an analysis of the speckle signal, which originates from the surface roughness of the substrate. In detection-mode (RN3.1), the signal from all illumination angles is added. In review-mode (RN3.9), the signals from all nine arms are recorded individually and analyzed in order to retrieve additional information on the shape and size of deep sub-wavelength defects. This paper presents experimental and modelling results on the extraction of shape information from the RN3.9 multi-azimuth signal such as aspect ratio, skewness, and orientation of test defects. Both modeling and experimental work confirm that the RN3.9 signal contains detailed defect shape information. After review by RN3.9, defects are coarsely classified, yielding a purified Defect-of-Interest (DoI) list for further analysis on slower metrology tools, such as SEM, AFM or HIM, that provide more detailed review data and further classification. Purifying the DoI list via optical metrology with RN3.9 will make inspection time on slower review tools more efficient.