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Identifying electronic transitions of defects in hexagonal boron nitride for quantum memories

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Zenodo2024-02-10 更新2026-05-26 收录
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This dataset contains The Excel file reveals the properties of defects, consisting of transition dipole moment, zero phonon line, lifetime, coupling constant, quality factor, and bandwidth. The raw data includes the electronic transition of both triplet and singlet spin configurations. This dataset was used to support the findings of the following work: Cholsuk et al., Identifying electronic transitions of defects in hexagonal boron nitride for quantum memories A quantum memory is a crucial keystone for enabling large-scale quantum networks. Applicable to the practical implementation, specific properties, i.e., long storage time, selective efficient coupling with other systems, and a high memory efficiency are desirable. Though many quantum memory systems have been developed thus far, none of them can perfectly meet all requirements. This work herein proposes a quantum memory based on color centers in hexagonal boron nitride (hBN), where its performance is evaluated based on a simple theoretical model of suitable defects in a cavity. Employing density functional theory calculations, 257 triplet and 211 singlet spin electronic transitions have been investigated. Among these defects, we found that some defects inherit the Lambda electronic structures desirable for a Raman-type quantum memory and optical transitions can couple with other quantum systems. Further, the required quality factor and bandwidth are examined for each defect to achieve a 95% writing efficiency. Both parameters are influenced by the radiative transition rate in the defect state. In addition, inheriting triplet-singlet spin multiplicity indicates the possibility of being a quantum sensing, in particular, optically detected magnetic resonance. This work therefore demonstrates the potential usage of hBN defects as a quantum memory in future quantum networks. (Preprint at arXiv:2310.20645; published at https://onlinelibrary.wiley.com/doi/10.1002/adom.202302760?af=R) Questions regarding this dataset should be sent to the corresponding authors.

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2023-12-10
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