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arXiv 2508.09024cond-mat.mes-hallquant-ph
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量子点电荷稳定图中的自动电荷跃迁检测

Automated Charge Transition Detection in Quantum Dot Charge Stability Diagrams

Fabian Hader, Fabian Fuchs, Sarah Fleitmann, Karin Havemann, Benedikt Scherer, Jan Vogelbruch, Lotte Geck, Stefan van Waasen

AI总结:

本文研究了量子点电荷稳定图中电荷跃迁边缘的自动检测方法,利用 SimCATS 框架的模拟数据进行训练与定量比较,并在 GaAs 和 SiGe 量子比特样品的实验数据上验证了优化方法的有效性,以推进量子比特调节的完全自动化。

摘要:

栅极定义的半导体量子点需要适当数量的电子才能作为量子比特运行。电子数量通常通过分析电荷稳定图来调节,其中电荷跃迁表现为边缘。因此,为了完全自动化量子比特调节,必须自动且可靠地识别这些边缘。本文研究了可能的检测方法,描述了使用来自 SimCATS 框架的模拟数据进行的训练,并考虑到未来的硬件实现进行了定量比较。此外,我们还研究了优化方法在来自 GaAs 和 SiGe 量子比特样品的实验测量数据上的质量。

英文摘要:

Gate-defined semiconductor quantum dots require an appropriate number of electrons to function as qubits. The number of electrons is usually tuned by analyzing charge stability diagrams, in which charge transitions manifest as edges. Therefore, to fully automate qubit tuning, it is necessary to recognize these edges automatically and reliably. This paper investigates possible detection methods, describes their training with simulated data from the SimCATS framework, and performs a quantitative comparison with a future hardware implementation in mind. Furthermore, we investigated the quality of the optimized approaches on experimentally measured data from a GaAs and a SiGe qubit sample.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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