Journal
PHYSICA STATUS SOLIDI-RAPID RESEARCH LETTERS
Volume 17, Issue 5, Pages -Publisher
WILEY-V C H VERLAG GMBH
DOI: 10.1002/pssr.202200498
Keywords
machine learning; microwave spectrum detection; nitrogen vacancy color center in diamond
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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.
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.
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