g-tensor Optimization in Ge/SiGe Quantum Dots
Aram Shojaei, Edmondo Valvo, Maximilian Rimbach-Russ, Eliska Greplova, Ana Silva
TLDR
This paper presents a flexible optimization framework for engineering g-tensor properties in Ge/SiGe quantum dots to enhance hole-spin qubit reliability.
Key contributions
- Introduces a flexible optimization framework to engineer g-tensor properties in Ge/SiGe quantum dots.
- Numerically optimizes quantum well potential to suppress in-plane g-tensor components.
- Enables the realization of gapless single-spin qubit encoding for improved reliability.
- Achieves potential reshaping through heterostructure engineering by adjusting silicon concentration.
Why it matters
Quantum dot variability limits hole-spin qubit performance. This paper introduces a framework to optimize g-tensor properties, enabling more reliable qubit operations. This work provides practical design principles, crucial for advancing large-scale germanium-based quantum computers.
Original Abstract
Planar germanium heterostructures hosting hole-spin qubits are among the leading platforms for scalable semiconductor-based quantum computing. Yet, device performance is hindered by significant quantum dot variability, which leads to uncertainty in qubit energy levels and random orientations of the spin quantization axis. Tailored control of the g-tensor offers a strategy to overcome these limitations and achieve more reliable qubit operations. Here, we introduce a flexible optimization framework for engineering g-tensor properties. As a benchmark, we numerically obtain the optimal reshaping of the out-of-plane potential in a SiGe-Ge-SiGe quantum well to suppress the in-plane g-tensor components and realize the recently proposed gapless single-spin qubit encoding. This reshaping is achieved through heterostructure engineering, specifically by adjusting the silicon concentration within the quantum well, though the framework remains readily adaptable to alternative design objectives. Our results provide practical design principles for improving the tunability of the spin response, paving the way towards large-scale germanium-based quantum computers.
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