English

Industrial 300$\,$mm wafer processed spin qubits in natural silicon/silicon-germanium

Mesoscale and Nanoscale Physics 2024-09-23 v2 Materials Science Quantum Physics

Abstract

The realisation of an universal quantum computer will require the operation of thousands to millions of qubits. The possibility of using existing industrial semiconductor fabrication techniques and infrastructure for up-scaling and reproducibility makes silicon based spin qubits one of the most promising platforms to achieve this goal. The implementation of the up to now largest semiconductor based quantum processor was realized in a silicon/silicon-germanium heterostructure known for its low charge noise, long qubit coherence times and fast driving speeds, but the high structural complexity creates challenges for industrial implementations. Here we demonstrate quantum dots hosted in a natural Si/SiGe heterostructure fully fabricated by an industrial 300\,mm semiconductor wafer process line from heterostructure growth to Co micromagnet monolithic integration. We report charge noise values below 2μeV/Hz\,\mathrm{\mu eV/\sqrt{Hz}}, spin relaxation times of over 1\,s and coherence times T2T_2^* and T2HT_2^H of 1μs\,\mathrm{\mu s} and 50μs\,\mathrm{\mu s} respectively, for quantum wells grown using natural silicon. Further, we achieve Rabi frequencies up to 5\,MHz and single qubit gate fidelities above 99%\,\%. In addition to scalability, the high reproducibility of the 300\,mm processes enables the deterministic study of qubit metric dependencies on process parameters, which is essential for optimising qubit quality.

Keywords

Cite

@article{arxiv.2409.12731,
  title  = {Industrial 300$\,$mm wafer processed spin qubits in natural silicon/silicon-germanium},
  author = {Thomas Koch and Clement Godfrin and Viktor Adam and Julian Ferrero and Daniel Schroller and Noah Glaeser and Stefan Kubicek and Ruoyu Li and Roger Loo and Shana Massar and George Simion and Danny Wan and Kristiaan De Greve and Wolfgang Wernsdorfer},
  journal= {arXiv preprint arXiv:2409.12731},
  year   = {2024}
}