Explainable Classification Techniques for Quantum Dot Device Measurements

no code implementations • 21 Feb 2024 • Daniel Schug, Tyler J. Kovach, M. A. Wolfe, Jared Benson, Sanghyeok Park, J. P. Dodson, J. Corrigan, M. A. Eriksson, Justyna P. Zwolak

In the physical sciences, there is an increased need for robust feature representations of image data: image acquisition, in the generalized sense of two-dimensional data, is now widespread across a large number of fields, including quantum information science, which we consider here.

Classification

Toward Robust Autotuning of Noisy Quantum Dot Devices

1 code implementation • 30 Jul 2021 • Joshua Ziegler, Thomas McJunkin, E. S. Joseph, Sandesh S. Kalantre, Benjamin Harpt, D. E. Savage, M. G. Lagally, M. A. Eriksson, Jacob M. Taylor, Justyna P. Zwolak

In this work, we propose a framework for robust autotuning of QD devices that combines a machine learning (ML) state classifier with a data quality control module.

Microwave-driven coherent operations of a semiconductor quantum dot charge qubit

no code implementations • 29 Jul 2014 • Dohun Kim, D. R. Ward, C. B. Simmons, John King Gamble, Robin Blume-Kohout, Erik Nielsen, D. E. Savage, M. G. Lagally, Mark Friesen, S. N. Coppersmith, M. A. Eriksson

A most intuitive realization of a qubit is a single electron charge sitting at two well-defined positions, such as the left and right sides of a double quantum dot.

Mesoscale and Nanoscale Physics Quantum Physics