Print Email Facebook Twitter Deep learning enhanced individual nuclear-spin detection Title Deep learning enhanced individual nuclear-spin detection Author Jung, Kyunghoon (Seoul National University) Abobeih, M.H.M.A. (TU Delft QID/Taminiau Lab; TU Delft QuTech Advanced Research Centre; Kavli institute of nanoscience Delft) Yun, Jiwon (Seoul National University) Kim, Gyeonghun (Seoul National University) Oh, Hyunseok (Seoul National University) Henry, Ang (University College London) Taminiau, T.H. (TU Delft QID/Taminiau Lab; TU Delft QuTech Advanced Research Centre; Kavli institute of nanoscience Delft) Kim, Dohun (Seoul National University) Date 2021 Abstract The detection of nuclear spins using individual electron spins has enabled diverse opportunities in quantum sensing and quantum information processing. Proof-of-principle experiments have demonstrated atomic-scale imaging of nuclear-spin samples and controlled multi-qubit registers. However, to image more complex samples and to realize larger-scale quantum processors, computerized methods that efficiently and automatically characterize spin systems are required. Here, we realize a deep learning model for automatic identification of nuclear spins using the electron spin of single nitrogen-vacancy (NV) centers in diamond as a sensor. Based on neural network algorithms, we develop noise recovery procedures and training sequences for highly non-linear spectra. We apply these methods to experimentally demonstrate the fast identification of 31 nuclear spins around a single NV center and accurately determine the hyperfine parameters. Our methods can be extended to larger spin systems and are applicable to a wide range of electron-nuclear interaction strengths. These results pave the way towards efficient imaging of complex spin samples and automatic characterization of large spin-qubit registers. To reference this document use: http://resolver.tudelft.nl/uuid:5f26faaf-af88-45c7-8b12-3663416e9c6a DOI https://doi.org/10.1038/s41534-021-00377-3 ISSN 2056-6387 Source NPJ Quantum Information, 7 (1) Part of collection Institutional Repository Document type journal article Rights © 2021 Kyunghoon Jung, M.H.M.A. Abobeih, Jiwon Yun, Gyeonghun Kim, Hyunseok Oh, Ang Henry, T.H. Taminiau, Dohun Kim Files PDF s41534_021_00377_3.pdf 2.48 MB Close viewer /islandora/object/uuid:5f26faaf-af88-45c7-8b12-3663416e9c6a/datastream/OBJ/view