提出自动校准系统BATIS,解决量子点器件高温调试难题
Bootstrapping, autonomous testing, and initialization system for Si/Si$_x$Ge$_{1-x}$ multi-quantum-dot devices
- 设计自举式自动测试系统,无需深度冷冻即可完成初始诊断
- 在1.3K下实现4个量子点的通道形成,仅需一次测量
- 对复杂量子点阵列有普适性,适合大规模量子计算研发
半导体量子点器件已成为自旋基量子计算发展的核心。然而,现代量子点器件的日益复杂使校准与控制(尤其在较高温度下)成为进展瓶颈,亟需稳健且可扩展的自主解决方案。主要障碍来自氧化层中的捕获电荷,导致栅极电压产生随机偏移,标准偏差约83 mV。高效表征和调谐大规模量子点量子比特依赖于自动化协议的选择。本文提出一种物理直观的自举、自主测试与初始化系统(BATIS),旨在简化量子点器件评估与校准流程。BATIS可在高维栅压空间中导航,自动完成漏电流测试、所有电流通道形成及存在捕获电荷时的栅极表征。其通道形成采用非标准方法,无论通道数量多少,仅需一组测量。该系统在1.3 K下于四量子点Si/Si_xGe_{1-x}器件上验证,首次实现了初始诊断无需深低温环境,显著提升可扩展性并缩短设置时间。凭借仅需极少器件结构先验知识,BATIS为多种量子点系统提供平台无关解法,填补了量子点自动调谐的关键空白。
原文摘要 · Abstract (English)
Semiconductor quantum dot (QD) devices have become central to advancements in spin-based quantum computing. However, the increasing complexity of modern QD devices makes calibration and control -- particularly at elevated temperatures -- a bottleneck to progress, highlighting the need for robust and scalable autonomous solutions. A major hurdle arises from trapped charges within the oxide layers, which induce random offset voltage shifts on gate electrodes, with a standard deviation of approximately 83 mV of variation within state-of-the-art present-day devices. Efficient characterization and tuning of large arrays of QD qubits depend on choices of automated protocols. Here, we introduce a physically intuitive framework for a bootstrapping, autonomous testing, and initialization system (BATIS) designed to streamline QD device evaluation and calibration. BATIS navigates high-dimensional gate voltage spaces, automating essential steps such as leakage testing, formation of all current channels, and gate characterization in the presence of trapped charges. For forming the current channels, BATIS follows a non-standard approach that requires a single set of measurements regardless of the number of channels. Demonstrated at 1.3 K on a quad-QD Si/Si$_x$Ge$_{1-x}$ device, BATIS eliminates the need for deep cryogenic environments during initial device diagnostics, significantly enhancing scalability and reducing setup times. By requiring only minimal prior knowledge of the device architecture, BATIS represents a platform-agnostic solution, adaptable to various QD systems, which bridges a critical gap in QD autotuning.
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