Accurate magnetic field imaging using nanodiamond quantum sensors enhanced by machine learning

Moeta Tsukamoto; Shuji Ito; Kensuke Ogawa; Yuto Ashida; Kento Sasaki; Kensuke Kobayashi

doi:10.1038/s41598-022-18115-w

Accurate magnetic field imaging using nanodiamond quantum sensors enhanced by machine learning

Sci Rep. 2022 Sep 1;12(1):13942. doi: 10.1038/s41598-022-18115-w.

Authors

Moeta Tsukamoto¹, Shuji Ito², Kensuke Ogawa², Yuto Ashida^{2

3}, Kento Sasaki², Kensuke Kobayashi^{2

3

4}

Affiliations

¹ Department of Physics, The University of Tokyo, Bunkyo-ku, Tokyo, 113-0033, Japan. moeta.tsukamoto@phys.s.u-tokyo.ac.jp.
² Department of Physics, The University of Tokyo, Bunkyo-ku, Tokyo, 113-0033, Japan.
³ Institute for Physics of Intelligence, The University of Tokyo, Bunkyo-ku, Tokyo, 113-0033, Japan.
⁴ Trans-scale Quantum Science Institute, The University of Tokyo, Bunkyo-ku, Tokyo, 113-0033, Japan.

Abstract

Nanodiamonds can be excellent quantum sensors for local magnetic field measurements. We demonstrate magnetic field imaging with high accuracy of 1.8 [Formula: see text]T combining nanodiamond ensemble (NDE) and machine learning without any physical models. We discover the dependence of the NDE signal on the field direction, suggesting the application of NDE for vector magnetometry and the improvement of the existing model. Our method enhances the NDE performance sufficiently to visualize nano-magnetism and mesoscopic current and expands the applicability of NDE in arbitrarily shaped materials, including living organisms. This accomplishment bridges machine learning to quantum sensing for accurate measurements.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Diagnostic Imaging
Machine Learning
Magnetic Fields
Magnetometry
Nanodiamonds*

Substances

Nanodiamonds