Accelerated Nano-Optical Imaging through Sparse Sampling

• DOI: 10.1021/acs.nanolett.3c03733
• Publication Date: 2024-02-08T16:16:37Z
• Authors: Matthew Fu; Suheng Xu; Shuai Zhang; Francesco L. Ruta; Jordan Pack; Rafael A. Mayer; Xinzhong Chen; Samuel L. Moore; Daniel J. Rizzo; Bjarke S. Jessen; Matthew Cothrine; David G. Mandrus; Kenji Watanabe; Takashi Taniguchi; Cory R. Dean; Abhay N. Pasupathy; Valentina Bisogni; P. James Schuck; Andrew J. Millis; Mengkun Liu; D. N. Basov

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 the measurement time, for example, in nano-optical imaging experiments performed using near-field optical microscope (SNOM). Here, we utilize sparse augmented with Gaussian process regression to bypass constraint. We apply this approach image charge-transfer polaritons graphene residing ruthenium trichloride (α-RuCl