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 × 5 μm² 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.

中文翻译：

---

基于钻石中氮空位中心的微观尺度微波光谱检测

提出了一种基于钻石中氮空位 (NV) 色心的基于机器学习的微波光谱检测方法。建立了荧光光谱与标准微波光谱之间的函数关系。使用 Tikhonov 正则化技术计算响应矩阵，并重建未知的微波频谱。尺寸仅为 5 × 5 μm ^{2 的}金刚石颗粒被放置在微流体结构中。因此，微波频谱的频率检测范围为 2.892 至 6.214 GHz，分辨率为 22 kHz。拟议的研究为微观尺度的微波光谱检测和成像开辟了新途径。