no code implementations • 22 Nov 2021 • D. L. Craig, H. Moon, F. Fedele, D. T. Lennon, B. Van Straaten, F. Vigneau, L. C. Camenzind, D. M. Zumbühl, G. A. D. Briggs, M. A. Osborne, D. Sejdinovic, N. Ares
The discrepancies between reality and simulation impede the optimisation and scalability of solid-state quantum devices.
no code implementations • 27 Jul 2021 • B. Severin, D. T. Lennon, L. C. Camenzind, F. Vigneau, F. Fedele, D. Jirovec, A. Ballabio, D. Chrastina, G. Isella, M. de Kruijf, M. J. Carballido, S. Svab, A. V. Kuhlmann, F. R. Braakman, S. Geyer, F. N. M. Froning, H. Moon, M. A. Osborne, D. Sejdinovic, G. Katsaros, D. M. Zumbühl, G. A. D. Briggs, N. Ares
The potential of Si and SiGe-based devices for the scaling of quantum circuits is tainted by device variability.
1 code implementation • 30 Sep 2020 • V. Nguyen, S. B. Orbell, D. T. Lennon, H. Moon, F. Vigneau, L. C. Camenzind, L. Yu, D. M. Zumbühl, G. A. D. Briggs, M. A. Osborne, D. Sejdinovic, N. Ares
This paper proposes a novel approach to the efficient measurement of quantum devices based on deep reinforcement learning.
no code implementations • 13 Jan 2020 • N. M. van Esbroeck, D. T. Lennon, H. Moon, V. Nguyen, F. Vigneau, L. C. Camenzind, L. Yu, D. M. Zumbühl, G. A. D. Briggs, D. Sejdinovic, N. Ares
Quantum devices with a large number of gate electrodes allow for precise control of device parameters.
2 code implementations • 8 Jan 2020 • H. Moon, D. T. Lennon, J. Kirkpatrick, N. M. van Esbroeck, L. C. Camenzind, Liuqi Yu, F. Vigneau, D. M. Zumbühl, G. A. D. Briggs, M. A. Osborne, D. Sejdinovic, E. A. Laird, N. Ares
Device variability is a bottleneck for the scalability of semiconductor quantum devices.
4 code implementations • 23 Oct 2018 • D. T. Lennon, H. Moon, L. C. Camenzind, Liuqi Yu, D. M. Zumbühl, G. A. D. Briggs, M. A. Osborne, E. A. Laird, N. Ares
Scalable quantum technologies will present challenges for characterizing and tuning quantum devices.