Multi-objective Bayesian optimization of Si-spike-enriched Ge heterostructures predicts up to 1000x stronger spin-orbit interaction and 100x better spin-qubit quality factors than state-of-the-art Ge/SiGe wells.
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Numerical simulations predict that tensile or unstrained germanium heterostructures yield spin splittings over 100 times larger than compressive cases, enabling GHz Andreev spin qubits with 100 ns all-electric gates.
A review summarizing spin qubit platforms, long-range coupling methods, and a proposal for topological linking toward scalable quantum information processing.
citing papers explorer
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Tailoring Germanium Heterostructures for Quantum Devices with Machine Learning
Multi-objective Bayesian optimization of Si-spike-enriched Ge heterostructures predicts up to 1000x stronger spin-orbit interaction and 100x better spin-qubit quality factors than state-of-the-art Ge/SiGe wells.
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Strain engineering of Andreev spin qubits in Germanium
Numerical simulations predict that tensile or unstrained germanium heterostructures yield spin splittings over 100 times larger than compressive cases, enabling GHz Andreev spin qubits with 100 ns all-electric gates.
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Theory of spin qubits and the path to scalability
A review summarizing spin qubit platforms, long-range coupling methods, and a proposal for topological linking toward scalable quantum information processing.