Estimation of Convex Polytopes for Automatic Discovery of Charge State Transitions in Quantum Dot Arrays
This addresses the challenge of controlling spin-based quantum dot arrays affected by material or fabrication imprecisions, representing an incremental improvement in automation for quantum device characterization.
The paper tackles the problem of automatically discovering charge state transitions in quantum dot arrays by estimating convex polytopes from measurements, achieving reliable detection of facets including small ones on the order of measurement precision.
In spin based quantum dot arrays, material or fabrication imprecisions affect the behaviour of the device, which must be taken into account when controlling it. This requires measuring the shape of specific convex polytopes. In this work, we present an algorithm that automatically discovers count, shape and size of the facets of a convex polytope from measurements. Results on simulated devices as well as a real 2x2 spin qubit array show that we can reliably find the facets of the convex polytopes, including small facets with sizes on the order of the measurement precision.