Regensburg 2025 – wissenschaftliches Programm
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HL: Fachverband Halbleiterphysik
HL 44: Focus Session: Quantum Technologies in Deployed Systems I
HL 44.2: Vortrag
Mittwoch, 19. März 2025, 18:15–18:30, H13
Automated in situ optimization and disorder mitigation in a quantum device — •Jacob Benestad1, Torbjørn Rasmussen2, 3, Bertram Brovang2, Oswin Krause4, Saeed Fallahi5, 6, Geoffrey C. Gardner6, Michael J. Manfra5,6,7,8, Charles M. Marcus2, Jeroen Danon1, Ferdinand Kuemmeth2, Anasua Chatterjee2, 3, and Evert van Nieuwenburg9 — 1Department of Physics, Norwegian University of Science and Technology — 2Center for Quantum Devices, Niels Bohr Institute, University of Copenhagen — 3QuTech and Kavli Institute of Nanoscience, Delft University of Technology — 4Department of Computer Science, University of Copenhagen — 5Department of Physics and Astronomy, Purdue University — 6Birck Nanotechnology Center, Purdue University — 7Elmore Family School of Electrical and Computer Engineering, Purdue University — 8School of Materials Engineering, Purdue University — 9Lorentz Institute and Leiden Institute of Advanced Computer Science
We investigate automated in situ optimisation of a quantum point contact (QPC) device with 9 adjustable electrostatic gates atop the split-gate constriction, using the Covariance Matrix Adaptation Evolutionary Strategy (CMA-ES) with a metric for how “step-like” the conductance is when the channel is constricted. The optimization algorithm is first tested on tight-binding simulations to show how it could adapt to a disorder potential, followed by implementing it in an experiment to show a marked improvement in the quantization of device conductance.
Keywords: Quantum transport; Machine learning; Automation; Quantum devices