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Si/SiGe器件的量子模拟:实验校准的微磁体效应

Quantum Simulation of Si/SiGe Devices with Experimentally Calibrated Micromagnet Effects

Andrii Sokolov, Conor Power, Mathieu Moras, Claude Rohrbacher, Brian Malone, Sergey Amitonov, Agostino Apra, Amir Sammak, Nodar Samkharadze, Elena Blokhina

arXiv 2609.27724首次发表:更新:

发表机构

Equal1 Laboratories(Equal1 实验室)

机构由 AI 辅助整理,请以论文原文为准。

AI 中文总结

本研究提出一个经实验校准的Si/SiGe六点器件三维模拟流程,结合电荷屏蔽和Jiles-Atherton磁滞模型,成功复现实验共振频率,为可扩展自旋量子比特设计提供可靠预测基础。

AI 中文摘要

硅基自旋量子比特在Si/SiGe异质结构中是可扩展量子计算的主要平台,然而,理论计算机辅助设计(CAD)模型与实验现实之间的差距仍然是一个重大挑战。标准模拟通常无法捕捉关键物理现象,如界面偶极子、寄生电荷积累以及片上微磁体的磁滞效应。在这项工作中,我们提出了一个全面的、经实验校准的6点Si/SiGe器件三维模拟流程。我们优化了半导体能带对齐,并引入了一个半经验经典电荷屏蔽模型,以准确捕捉寄生阱的形成及其对栅极杠杆臂的抑制。此外,我们应用Jiles-Atherton模型来考虑集成钴微磁体的磁滞和预磁化效应,成功再现了所有六个量子比特的实验共振频率。通过将这些校准的静电和磁特性耦合到含时旋转波近似(RWA)哈密顿量中,我们再现了实验可观测量,包括微波功率雪佛龙图。该框架为预测器件行为、评估微波线路损耗以及在制造前优化未来可扩展自旋量子比特架构提供了坚实基础。

英文摘要

Silicon-based spin qubits in Si/SiGe heterostructures are a leading platform for scalable quantum computing, yet bridging the gap between theoretical computer-aided design(CAD) models and experimental reality remains a significant challenge. Standard simulations often fail to capture critical physical phenomena, such as interface dipoles, parasitic charge accumulation, and the magnetic hysteresis of on-chip micromagnets. In this work, we present a comprehensive, experimentally calibrated 3D simulation pipeline for a 6-dot Si/SiGe device. We refine the semiconductor band alignment and introduce a semi-empirical classical charge screening model to accurately capture the formation of parasitic wells and their suppression of gate lever-arms. Furthermore, we apply the Jiles-Atherton model to account for the hysteresis and pre-magnetization of integrated cobalt micromagnets, successfully reproducing the experimental resonant frequencies across all six qubits. By coupling these calibrated electrostatic and magnetic profiles into a time-dependent rotating wave approximation (RWA) Hamiltonian, we reproduce experimental observables, including microwave power chevrons. This framework provides a robust foundation for predicting device behavior, evaluating microwave line losses, and optimizing future scalable spin qubit architectures prior to fabrication.

论文原文

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