Speaker
Bernd Rosenow
(Leipzig University)
Description
As the complexity of quantum systems such as quantum bit arrays increases, efforts to automate expensive tuning become increasingly worthwhile. We study 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 destroyed by disorder with optimized gate voltages.
Primary authors
Bernd Rosenow
(Leipzig University)
Mr
Matthias Thamm
(Leipzig University)
