Algorithmic decomposition for efficient multiple nuclear spin detection in diamond

Journal Article (2020)
Author(s)

Hyunseok Oh (Seoul National University)

Jiwon Yun (Seoul National University)

M. H. Abobeih (TU Delft - QID/Taminiau Lab, TU Delft - QuTech Advanced Research Centre, Kavli institute of nanoscience Delft)

Kyung Hoon Jung (Seoul National University)

Kiho Kim (Seoul National University)

T. H. Taminiau (TU Delft - QuTech Advanced Research Centre, Kavli institute of nanoscience Delft, TU Delft - QID/Taminiau Lab)

Dohun Kim (Seoul National University)

Research Group
QID/Taminiau Lab
DOI related publication
https://doi.org/10.1038/s41598-020-71339-6 Final published version
More Info
expand_more
Publication Year
2020
Language
English
Research Group
QID/Taminiau Lab
Issue number
1
Volume number
10
Article number
14884
Downloads counter
246
Collections
Institutional Repository
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Efficiently detecting and characterizing individual spins in solid-state hosts is an essential step to expand the fields of quantum sensing and quantum information processing. While selective detection and control of a few 13C nuclear spins in diamond have been demonstrated using the electron spin of nitrogen-vacancy (NV) centers, a reliable, efficient, and automatic characterization method is desired. Here, we develop an automated algorithmic method for decomposing spectral data to identify and characterize multiple nuclear spins in diamond. We demonstrate efficient nuclear spin identification and accurate reproduction of hyperfine interaction components for both virtual and experimental nuclear spectroscopy data. We conduct a systematic analysis of this methodology and discuss the range of hyperfine interaction components of each nuclear spin that the method can efficiently detect. The result demonstrates a systematic approach that automatically detects nuclear spins with the aid of computational methods, facilitating the future scalability of devices.