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Machine learning optimization of Majorana hybrid nanowires. (arXiv:2208.02182v2 [cond-mat.mes-hall] UPDATED)
Aug. 10, 2022, 1:11 a.m. | Matthias Thamm, Bernd Rosenow
cs.LG updates on arXiv.org arxiv.org
As the complexity of quantum systems such as quantum bit arrays increases,
efforts to automate expensive tuning are increasingly worthwhile. We
investigate machine learning based tuning of gate arrays using the CMA-ES
algorithm for the case study of Majorana wires with strong disorder. We find
that the algorithm is able to efficiently improve the topological signatures,
learn intrinsic disorder profiles, and completely eliminate disorder effects.
For example, with only 20 gates, it is possible to fully recover Majorana zero
modes …
More from arxiv.org / cs.LG updates on arXiv.org
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