Microwave Spectrum Detection at Microscopic Scale Based on Nitrogen Vacancy Center in Diamond

A machine learning-based microwave spectrum detection method based on the nitrogen vacancy (NV) color centers in diamonds is proposed. The functional relationship between the fluorescence spectrum and standard microwave spectrum is established. The response matrix is calculated using the Tikhonov regularization technique, and an unknown microwave spectrum is reconstructed. Diamond particles with a size of only 5 x 5 mu m(2) are placed in the microfluidic structures. Consequently, the frequency detection range of the microwave spectrum is from 2.892 to 6.214 GHz with a resolution of 22 kHz. The proposed research opens new paths for microwave spectrum detection and imaging at the microscopic scale.

Automated summary

A machine learning-based microwave spectrum detection method using nitrogen vacancy (NV) color centers in diamonds is proposed. The functional relationship between fluorescence spectrum and standard microwave spectrum is established. The research enables microwave spectrum detection and imaging at the microscopic scale.