g-tensor Optimization in Ge/SiGe Quantum Dots

TL;DR

This paper presents a flexible optimization framework for engineering the g-tensor in Ge/SiGe quantum dots to enhance qubit performance and reliability in semiconductor quantum computing.

Contribution

It introduces a novel optimization method for tailoring g-tensor properties through heterostructure engineering in germanium-based quantum dots.

Findings

Optimized the out-of-plane potential to suppress in-plane g-tensor components.

Achieved heterostructure design by adjusting silicon concentration in the quantum well.

Provided practical guidelines for improving g-tensor tunability in quantum dot devices.

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.