High-resolution wide-field magnetic imaging with sparse sampling using nitrogen-vacancy centers
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866918317369851904 |
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| author | Liu, Keqing Tian, Jiazhao Duan, Bokun Zhang, Hao Li, Kangze Zhang, Guofeng Jelezko, Fedor Said, Ressa S. Cai, Jianming Xiao, Liantuan |
| author_facet | Liu, Keqing Tian, Jiazhao Duan, Bokun Zhang, Hao Li, Kangze Zhang, Guofeng Jelezko, Fedor Said, Ressa S. Cai, Jianming Xiao, Liantuan |
| contents | Nitrogen-vacancy (NV) centers in diamond enable quantitative magnetic imaging, yet practical implementations must balance spatial resolution against acquisition time (and thus per-pixel sensitivity). Single-NV scanning magnetometry achieves genuine nanoscale resolution, nonetheless requires typically a slow pixel-by-pixel acquisition. Meanwhile, wide-field NV-ensemble microscopy provides parallel readout over a large field of view, however is jointly limited by the optical diffraction limit and the sensor-sample standoff. Here, we present a sparse-sampling strategy for reconstructing high-resolution wide-field images from only a small number of measurements. Using simulated NV-ensemble detection of ac magnetic fields, we show that a mean-adjusted Bayesian estimation (MABE) framework can reconstruct 10000-pixel images from only 25 sampling points, achieving SSIM values exceeding 0.999 for representative smooth field distributions, while optimized dynamical-decoupling pulse sequences yield an approximately twofold improvement in magnetic-field sensitivity. The method further clarifies how sampling patterns and sampling density affect reconstruction accuracy and suggests a route toward faster and more scalable magnetic-imaging architectures that may extend to point-scanning NV sensors and other magnetometry platforms, such as SQUIDs, Hall probes, and magnetic tunnel junctions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_00679 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | High-resolution wide-field magnetic imaging with sparse sampling using nitrogen-vacancy centers Liu, Keqing Tian, Jiazhao Duan, Bokun Zhang, Hao Li, Kangze Zhang, Guofeng Jelezko, Fedor Said, Ressa S. Cai, Jianming Xiao, Liantuan Quantum Physics Nitrogen-vacancy (NV) centers in diamond enable quantitative magnetic imaging, yet practical implementations must balance spatial resolution against acquisition time (and thus per-pixel sensitivity). Single-NV scanning magnetometry achieves genuine nanoscale resolution, nonetheless requires typically a slow pixel-by-pixel acquisition. Meanwhile, wide-field NV-ensemble microscopy provides parallel readout over a large field of view, however is jointly limited by the optical diffraction limit and the sensor-sample standoff. Here, we present a sparse-sampling strategy for reconstructing high-resolution wide-field images from only a small number of measurements. Using simulated NV-ensemble detection of ac magnetic fields, we show that a mean-adjusted Bayesian estimation (MABE) framework can reconstruct 10000-pixel images from only 25 sampling points, achieving SSIM values exceeding 0.999 for representative smooth field distributions, while optimized dynamical-decoupling pulse sequences yield an approximately twofold improvement in magnetic-field sensitivity. The method further clarifies how sampling patterns and sampling density affect reconstruction accuracy and suggests a route toward faster and more scalable magnetic-imaging architectures that may extend to point-scanning NV sensors and other magnetometry platforms, such as SQUIDs, Hall probes, and magnetic tunnel junctions. |
| title | High-resolution wide-field magnetic imaging with sparse sampling using nitrogen-vacancy centers |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2602.00679 |