Autonomous Estimation of High-Dimensional Coulomb Diamonds from Sparse Measurements

Quantum dot arrays possess ground states governed by Coulomb energies, utilized prominently singly occupied quantum dots, each implementing a spin qubit. For such processors, the controlled transitions between are of operational significance, as these allow control information within array qubit initialization and entangling gates. few-dot arrays, traditionally mapped out performing dense raster-scan measurements in control-voltage space. These become impractical for larger due to large number needed sample high-dimensional gate-voltage hypercube comparatively little extracted. We develop hardware-triggered detection method based on reflectometry, acquire directly corresponding states. distributed sparsely voltage space executing line searches proposed learning algorithm. Our autonomous software-hardware algorithm accurately estimates polytope blockade boundaries, experimentally demonstrated 2$\times$2 silicon dots.