Estimation of Convex Polytopes for Automatic Discovery of Charge State Transitions in Quantum Dot Arrays

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Estimation of Convex Polytopes for Automatic Discovery of Charge State Transitions in Quantum Dot Arrays. / Krause, Oswin; Brovang, Bertram; Rasmussen, Torbjorn; Chatterjee, Anasua; Kuemmeth, Ferdinand.

In: Electronics, Vol. 11, No. 15, 2327, 27.07.2022.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Krause, O, Brovang, B, Rasmussen, T, Chatterjee, A & Kuemmeth, F 2022, 'Estimation of Convex Polytopes for Automatic Discovery of Charge State Transitions in Quantum Dot Arrays', Electronics, vol. 11, no. 15, 2327. https://doi.org/10.3390/electronics11152327

APA

Krause, O., Brovang, B., Rasmussen, T., Chatterjee, A., & Kuemmeth, F. (2022). Estimation of Convex Polytopes for Automatic Discovery of Charge State Transitions in Quantum Dot Arrays. Electronics, 11(15), [2327]. https://doi.org/10.3390/electronics11152327

Vancouver

Krause O, Brovang B, Rasmussen T, Chatterjee A, Kuemmeth F. Estimation of Convex Polytopes for Automatic Discovery of Charge State Transitions in Quantum Dot Arrays. Electronics. 2022 Jul 27;11(15). 2327. https://doi.org/10.3390/electronics11152327

Author

Krause, Oswin ; Brovang, Bertram ; Rasmussen, Torbjorn ; Chatterjee, Anasua ; Kuemmeth, Ferdinand. / Estimation of Convex Polytopes for Automatic Discovery of Charge State Transitions in Quantum Dot Arrays. In: Electronics. 2022 ; Vol. 11, No. 15.

Bibtex

@article{98f0bad9969c409ca774e9d4153b1040,
title = "Estimation of Convex Polytopes for Automatic Discovery of Charge State Transitions in Quantum Dot Arrays",
abstract = "In spin based quantum dot arrays, material or fabrication imprecisions affect the behaviour of the device, which must be taken into account when controlling it. This requires measuring the shape of specific convex polytopes. We present an algorithm that automatically discovers count, shape and size of the facets of a convex polytope from measurements by alternating a phase of model-fitting with a phase of querying new measurements, based on the fitted model. We evaluate the algorithm on simulated polytopes and devices, as well as a real 2 x 2 spin qubit array. Results show that we can reliably find the facets of the convex polytopes, including small facets with sizes on the order of the measurement precision.",
keywords = "quantum dot arrays, large margin, convex polytopes, polytope estimation, active learning",
author = "Oswin Krause and Bertram Brovang and Torbjorn Rasmussen and Anasua Chatterjee and Ferdinand Kuemmeth",
year = "2022",
month = jul,
day = "27",
doi = "10.3390/electronics11152327",
language = "English",
volume = "11",
journal = "Electronics",
issn = "1450-5843",
publisher = "Faculty of Electrical Engineering Banja Luka",
number = "15",

}

RIS

TY - JOUR

T1 - Estimation of Convex Polytopes for Automatic Discovery of Charge State Transitions in Quantum Dot Arrays

AU - Krause, Oswin

AU - Brovang, Bertram

AU - Rasmussen, Torbjorn

AU - Chatterjee, Anasua

AU - Kuemmeth, Ferdinand

PY - 2022/7/27

Y1 - 2022/7/27

N2 - In spin based quantum dot arrays, material or fabrication imprecisions affect the behaviour of the device, which must be taken into account when controlling it. This requires measuring the shape of specific convex polytopes. We present an algorithm that automatically discovers count, shape and size of the facets of a convex polytope from measurements by alternating a phase of model-fitting with a phase of querying new measurements, based on the fitted model. We evaluate the algorithm on simulated polytopes and devices, as well as a real 2 x 2 spin qubit array. Results show that we can reliably find the facets of the convex polytopes, including small facets with sizes on the order of the measurement precision.

AB - In spin based quantum dot arrays, material or fabrication imprecisions affect the behaviour of the device, which must be taken into account when controlling it. This requires measuring the shape of specific convex polytopes. We present an algorithm that automatically discovers count, shape and size of the facets of a convex polytope from measurements by alternating a phase of model-fitting with a phase of querying new measurements, based on the fitted model. We evaluate the algorithm on simulated polytopes and devices, as well as a real 2 x 2 spin qubit array. Results show that we can reliably find the facets of the convex polytopes, including small facets with sizes on the order of the measurement precision.

KW - quantum dot arrays

KW - large margin

KW - convex polytopes

KW - polytope estimation

KW - active learning

U2 - 10.3390/electronics11152327

DO - 10.3390/electronics11152327

M3 - Journal article

VL - 11

JO - Electronics

JF - Electronics

SN - 1450-5843

IS - 15

M1 - 2327

ER -

ID: 317438363