Protocol Discovery for the Quantum Control of Majoranas by Differentiable Programming and Natural Evolution Strategies

2020/08/31 by Luuk Coopmans, Di Luo, Graham Kells +2 · 1 citation
Materials Science · Mathematics · Physics and Astronomy · #Computer science #Differentiable function #Graphene research and applications #Jump #MAJORANA #Mathematical analysis #Mathematics #Physics #Quantum #Quantum many-body systems #Quantum mechanics #Superconductivity #Topological Materials and Phenomena #Topology (electrical circuits) #cond-mat.str-el #physics.comp-ph #quant-ph

paper · pdf · doi:10.1103/prxquantum.2.020332

published as PRX Quantum 2, 020332 (2021) · Revised manuscript: Addition of results on proximity coupled semiconducting nanowire, disorder and interactions. Extra discussions and new conclusion. 18 pages, 8 figures + appendix (12 pages, 8 figures)

arxiv created 2021/04/09 · openalex publication_date 2021/06/02 · arxiv updated 2021/06/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06

Abstract

Efficient machine learning approaches are exploited to optimize the transport of Majoranas in superconducting nanowires, opening up ways to achieve quantum control of realistic dynamical quantum many-body systems.

Citations

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• Shuttling Majorana zero modes in disordered and noisy topological superconductors