Application of Power Flow Problem to an Open Quantum Neural Hardware

Ekin Erdem Aygül; Melih Can Topal; Ufuk Korkmaz; Deniz Türknence

doi:10.1109/ICECET58911.2023.10389382

Application of Power Flow Problem to an Open Quantum Neural Hardware

Ekin Erdem Aygül, Melih Can Topal, Ufuk Korkmaz, Deniz Türknence

Department of Electrical Engineering

Istanbul Technical University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Significant progress in the construction of physical hardware for quantum computers has necessitated the development of new algorithms or protocols for the application of real-world problems on quantum computers. One of these problems is the power flow problem, which helps us understand the generation, distribution, and consumption of electricity in a system. In this study, the solution of a balanced 4-bus power system supported by the Newton-Raphson method is investigated using a newly developed dissipative quantum neural network hardware. This study presents the findings on how the proposed quantum network can be applied to the relevant problem and how the solution performance varies depending on the network parameters.

Original language	English
Title of host publication	International Conference on Electrical, Computer and Energy Technologies, ICECET 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350327816
DOIs	https://doi.org/10.1109/ICECET58911.2023.10389382
Publication status	Published - 2023
Event	2023 IEEE International Conference on Electrical, Computer and Energy Technologies, ICECET 2023 - Cape Town, South Africa Duration: 16 Nov 2023 → 17 Nov 2023

Publication series

Name	International Conference on Electrical, Computer and Energy Technologies, ICECET 2023

Conference

Conference	2023 IEEE International Conference on Electrical, Computer and Energy Technologies, ICECET 2023
Country/Territory	South Africa
City	Cape Town
Period	16/11/23 → 17/11/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

collisional model
information reservoir
quantum neuron
training and learning

Access to Document

10.1109/ICECET58911.2023.10389382

Cite this

Aygül, E. E., Topal, M. C., Korkmaz, U., & Türknence, D. (2023). Application of Power Flow Problem to an Open Quantum Neural Hardware. In International Conference on Electrical, Computer and Energy Technologies, ICECET 2023 (International Conference on Electrical, Computer and Energy Technologies, ICECET 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICECET58911.2023.10389382

Aygül, Ekin Erdem ; Topal, Melih Can ; Korkmaz, Ufuk et al. / Application of Power Flow Problem to an Open Quantum Neural Hardware. International Conference on Electrical, Computer and Energy Technologies, ICECET 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (International Conference on Electrical, Computer and Energy Technologies, ICECET 2023).

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series = "International Conference on Electrical, Computer and Energy Technologies, ICECET 2023",

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Aygül, EE, Topal, MC, Korkmaz, U & Türknence, D 2023, Application of Power Flow Problem to an Open Quantum Neural Hardware. in International Conference on Electrical, Computer and Energy Technologies, ICECET 2023. International Conference on Electrical, Computer and Energy Technologies, ICECET 2023, Institute of Electrical and Electronics Engineers Inc., 2023 IEEE International Conference on Electrical, Computer and Energy Technologies, ICECET 2023, Cape Town, South Africa, 16/11/23. https://doi.org/10.1109/ICECET58911.2023.10389382

Application of Power Flow Problem to an Open Quantum Neural Hardware. / Aygül, Ekin Erdem; Topal, Melih Can; Korkmaz, Ufuk et al.
International Conference on Electrical, Computer and Energy Technologies, ICECET 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (International Conference on Electrical, Computer and Energy Technologies, ICECET 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - Significant progress in the construction of physical hardware for quantum computers has necessitated the development of new algorithms or protocols for the application of real-world problems on quantum computers. One of these problems is the power flow problem, which helps us understand the generation, distribution, and consumption of electricity in a system. In this study, the solution of a balanced 4-bus power system supported by the Newton-Raphson method is investigated using a newly developed dissipative quantum neural network hardware. This study presents the findings on how the proposed quantum network can be applied to the relevant problem and how the solution performance varies depending on the network parameters.

AB - Significant progress in the construction of physical hardware for quantum computers has necessitated the development of new algorithms or protocols for the application of real-world problems on quantum computers. One of these problems is the power flow problem, which helps us understand the generation, distribution, and consumption of electricity in a system. In this study, the solution of a balanced 4-bus power system supported by the Newton-Raphson method is investigated using a newly developed dissipative quantum neural network hardware. This study presents the findings on how the proposed quantum network can be applied to the relevant problem and how the solution performance varies depending on the network parameters.

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Aygül EE, Topal MC, Korkmaz U, Türknence D. Application of Power Flow Problem to an Open Quantum Neural Hardware. In International Conference on Electrical, Computer and Energy Technologies, ICECET 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (International Conference on Electrical, Computer and Energy Technologies, ICECET 2023). doi: 10.1109/ICECET58911.2023.10389382

Application of Power Flow Problem to an Open Quantum Neural Hardware

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Keywords

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