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Title: Compressed Optimization of Device Architectures for Semiconductor Quantum Devices

Abstract

Recent advances in nanotechnology have enabled researchers to manipulate small collections of quantum-mechanical objects with unprecedented accuracy. In semiconductor quantum-dot qubits, this manipulation requires controlling the dot orbital energies, the tunnel couplings, and the electron occupations. These properties all depend on the voltages placed on the metallic electrodes that define the device, the positions of which are fixed once the device is fabricated. While there has been much success with small numbers of dots, as the number of dots grows, it will be increasingly useful to control these systems with as few electrode voltage changes as possible. Here, we introduce a protocol, which we call the "compressed optimization of device architectures" (CODA), in order both to efficiently identify sparse sets of voltage changes that control quantum systems and to introduce a metric that can be used to compare device designs. As an example of the former, we apply this method to simulated devices with up to 100 quantum dots and show that CODA automatically tunes devices more efficiently than other common nonlinear optimizers. To demonstrate the latter, we determine the optimal lateral scale for a triple quantum dot, yielding a simulated device that can be tuned with small voltage changesmore » on a limited number of electrodes.« less

Authors:
 [1];  [2];  [3];  [3];  [1];  [1];  [4]
  1. Univ. of Wisconsin, Madison, WI (United States)
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Microsoft Research, Redmond, WA (United States)
  3. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  4. Univ. of Wisconsin, Madison, WI (United States); Univ. of New South Wales, Sydney, NSW (Australia)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1497629
Report Number(s):
SAND2019-1977J
Journal ID: ISSN 2331-7019; PRAHB2; 672814
Grant/Contract Number:  
AC04-94AL85000
Resource Type:
Accepted Manuscript
Journal Name:
Physical Review Applied
Additional Journal Information:
Journal Volume: 11; Journal Issue: 2; Journal ID: ISSN 2331-7019
Publisher:
American Physical Society (APS)
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS

Citation Formats

Frees, Adam, Gamble, John King, Ward, Daniel R., Blume-Kohout, Robin, Eriksson, M. A., Friesen, Mark, and Coppersmith, S. N. Compressed Optimization of Device Architectures for Semiconductor Quantum Devices. United States: N. p., 2019. Web. doi:10.1103/PhysRevApplied.11.024063.
Frees, Adam, Gamble, John King, Ward, Daniel R., Blume-Kohout, Robin, Eriksson, M. A., Friesen, Mark, & Coppersmith, S. N. Compressed Optimization of Device Architectures for Semiconductor Quantum Devices. United States. doi:https://doi.org/10.1103/PhysRevApplied.11.024063
Frees, Adam, Gamble, John King, Ward, Daniel R., Blume-Kohout, Robin, Eriksson, M. A., Friesen, Mark, and Coppersmith, S. N. Mon . "Compressed Optimization of Device Architectures for Semiconductor Quantum Devices". United States. doi:https://doi.org/10.1103/PhysRevApplied.11.024063. https://www.osti.gov/servlets/purl/1497629.
@article{osti_1497629,
title = {Compressed Optimization of Device Architectures for Semiconductor Quantum Devices},
author = {Frees, Adam and Gamble, John King and Ward, Daniel R. and Blume-Kohout, Robin and Eriksson, M. A. and Friesen, Mark and Coppersmith, S. N.},
abstractNote = {Recent advances in nanotechnology have enabled researchers to manipulate small collections of quantum-mechanical objects with unprecedented accuracy. In semiconductor quantum-dot qubits, this manipulation requires controlling the dot orbital energies, the tunnel couplings, and the electron occupations. These properties all depend on the voltages placed on the metallic electrodes that define the device, the positions of which are fixed once the device is fabricated. While there has been much success with small numbers of dots, as the number of dots grows, it will be increasingly useful to control these systems with as few electrode voltage changes as possible. Here, we introduce a protocol, which we call the "compressed optimization of device architectures" (CODA), in order both to efficiently identify sparse sets of voltage changes that control quantum systems and to introduce a metric that can be used to compare device designs. As an example of the former, we apply this method to simulated devices with up to 100 quantum dots and show that CODA automatically tunes devices more efficiently than other common nonlinear optimizers. To demonstrate the latter, we determine the optimal lateral scale for a triple quantum dot, yielding a simulated device that can be tuned with small voltage changes on a limited number of electrodes.},
doi = {10.1103/PhysRevApplied.11.024063},
journal = {Physical Review Applied},
number = 2,
volume = 11,
place = {United States},
year = {2019},
month = {2}
}

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    Works referencing / citing this record:

    Efficiently measuring a quantum device using machine learning
    journal, September 2019