发表机构
Facultad de Ingeniería y Arquitectura, Universidad Central de Chile; Grupo de Simulaciones, Departamento de Física, Universidad Técnica Federico Santa María（智利中央大学工程与建筑学院; 费德里科·圣塔玛丽亚理工大学物理系模拟组）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文通过计算发现，六角氮化硼中负电硼空位量子比特的相干时间随层数变化，单层时达653ns，三层后饱和，层数可作为该类传感器件的设计参数。
AI 中文摘要
六角氮化硼（\text{hBN}）中的负电硼空位（$\text{V}_\text{B}$）是首个在范德华晶体中发现的光学可寻址自旋量子比特，可实现相对于目标的原子级精准定位。其在体相\text{hBN}中的相干性受缺陷平面两侧层的硼核限制，而薄层可消除该限制。本文采用含扩展中心自旋块的广义簇关联展开方法，计算$\text{V}_\text{B}$在$\text{h}^{11}\text{B}^{15}\text{N}$中随层数变化的回波相干时间。结果显示，其相干时间$T_2$从体相极限的$199\ns$升至单层的$653\ns$，提升3.3倍，且该提升在三层时已饱和，通过子晶格分解可知提升完全源于硼核的影响。该增强效应仅在低场下出现，对堆叠配准和扭转角不敏感，要求（磁场）对准在约2度以内，本文用无自由参数模型复现了该现象的起始条件。动态解耦下，$1/e$阈值对应各厚度下的$206\ns$，但这是第一壳层调制的零点而非衰减；无阈值测量时，层间差异仍存在，且提升达170倍。因此，层数成为基于$\text{V}_\text{B}$的传感器件的设计参数。
英文摘要
The negatively charged boron vacancy ($\VB$) in hexagonal boron nitride (\hBN{}) was the first optically addressable spin qubit identified inside a van der Waals crystal, allowing atomically defined placement relative to a target. Its coherence in bulk \hBN{} is limited by the boron nuclei of the layers flanking the defect plane, which a thin flake removes. Here, we use a generalized cluster-correlation expansion with an extended central-spin block to calculate the Hahn-echo coherence time of $\VB$ in h$^{11}$B$^{15}$N as a function of layer number. Our results show that $T_2$ rises from $199\ns$ in the bulk limit to $653\ns$ in a monolayer, a factor of $3.3$ that is already saturated at three layers and that a sublattice decomposition attributes entirely to boron. The enhancement is confined to low field, is insensitive to stacking registry and twist angle, and requires alignment to within about two degrees, an onset we reproduce with no free parameters. Under dynamical decoupling, a $1/e$ threshold returns $206\ns$ for every thickness, but this is a zero of the first-shell modulation rather than a decay: measured without a threshold, the layer contrast survives and reaches a factor of $170$. Layer number thus emerges as a design parameter for $\VB$-based sensing.
