Accelerated Nano-Optical Imaging through Sparse Sampling.

Fu, Matthew; Xu, Suheng; Zhang, Shuai; Ruta, Francesco L; Pack, Jordan; Mayer, Rafael A; Chen, Xinzhong; Moore, Samuel L et al. · Nano Lett · 2024

basic_science · Level V

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Abstract

The integration time and signal-to-noise ratio are inextricably linked when performing scanning probe microscopy based on raster scanning. This often yields a large lower bound on the measurement time, for example, in nano-optical imaging experiments performed using a scanning near-field optical microscope (SNOM). Here, we utilize sparse scanning augmented with Gaussian process regression to bypass the time constraint. We apply this approach to image charge-transfer polaritons in graphene residing on ruthenium trichloride (α-RuCl<sub>3</sub>) and obtain key features such as polariton damping and dispersion. Critically, nano-optical SNOM imaging data obtained via sparse sampling are in good agreement with those extracted from traditional raster scans but require 11 times fewer sampled points. As a result, Gaussian process-aided sparse spiral scans offer a major decrease in scanning time.