A machine-learning pipeline maps sparse simulated conductance data to a disorder-aware topological invariant (PDI), matching an idealized scattering-matrix oracle while using 10x fewer measurements.
X-shaped and y-shaped andreev resonance profiles in a superconducting quantum dot,
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MEDA: Measurement-Efficient Disorder-Aware Majorana Zero Mode Detection in Realistic Devices
A machine-learning pipeline maps sparse simulated conductance data to a disorder-aware topological invariant (PDI), matching an idealized scattering-matrix oracle while using 10x fewer measurements.