Data underlying the publication "Improved Electron-Nuclear Quantum Gates for Spin Sensing and Control"

doi:10.4121/643ed69d-ced0-4d45-86b3-534a5b79c605.v1
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doi: 10.4121/643ed69d-ced0-4d45-86b3-534a5b79c605
Datacite citation style:
van Ommen, Hendrik B.; van de Stolpe, Guido; Demetriou, Nicolas; Hans Beukers; Yun, Jiwon et. al. (2024): Data underlying the publication "Improved Electron-Nuclear Quantum Gates for Spin Sensing and Control". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/643ed69d-ced0-4d45-86b3-534a5b79c605.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset

The ability to sense and control nuclear spins near solid-state defects might enable a range of quantum technologies. Dynamically Decoupled Radio-Frequency (DDRF) control offers a high degree of design flexibility and long electron-spin coherence times. However, previous studies considered simplified models and little is known about optimal gate design and fundamental limits. Here, we develop a generalised DDRF framework that has important implications for spin sensing and control. Our analytical model, which we corroborate by experiments on a single NV center in diamond, reveals the mechanisms that govern the selectivity of gates and their effective Rabi frequencies, and enables flexible detuned gate designs. We apply these insights to numerically show a 60x sensitivity enhancement for detecting weakly coupled spins and study the optimisation of quantum gates in multi-qubit registers. These results advance the understanding for a broad class of gates and provide a toolbox for application-specific design, enabling improved quantum control and sensing.


This server contains the data and jupyter notebooks to reproduce the figures (see README file for instructions). Execute the notebook files (.ipynb extension) via an iPython environment. These will load the data from the .json and .npy data files to recreate the figures.


history
  • 2024-10-28 first online, published, posted
publisher
4TU.ResearchData
organizations
QuTech and Kavli Institute of Nanoscience, Delft University of Technology

DATA

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