Future Impact of Quantum Computing on the Computational Landscape of Power Electronics: A Short Tutorial
- URL: http://arxiv.org/abs/2507.02577v1
- Date: Thu, 03 Jul 2025 12:33:38 GMT
- Title: Future Impact of Quantum Computing on the Computational Landscape of Power Electronics: A Short Tutorial
- Authors: Nikolaos G. Paterakis, Petros Karamanakos, Corey O'Meara, Georgios Papafotiou,
- Abstract summary: This paper offers a tutorial on fundamental concepts in quantum computing, serving as an introduction to the field.<n>The use of quantum computing for solving offline mixed-integer optimization problems commonly encountered in power electronics is examined.<n>This demonstration marks a pioneering step towards leveraging quantum methods in power electronics.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Quantum computing is emerging as a promising technology for solving complex optimization problems that arise in various engineering fields, and therefore has the potential to also significantly impact power electronics applications. This paper offers a concise tutorial on fundamental concepts in quantum computing, serving as both an introduction to the field and a bridge to its potential applications in power electronics. As a first step in this direction, the use of quantum computing for solving offline mixed-integer optimization problems commonly encountered in power electronics is examined. To this end, a simplified power electronics design problem is reformulated as a quadratic unconstrained binary optimization (QUBO) problem and executed on quantum hardware, despite current limitations such as low qubit counts and hardware noise. This demonstration marks a pioneering step towards leveraging quantum methods in power electronics. Moreover, the implications of ongoing advancements in quantum algorithms and hardware are discussed, highlighting their potential to enable the efficient solution of large-scale, multiobjective design and control problems. The presented findings suggest that early adoption and exploration of quantum computing could significantly expand the capabilities and performance of power electronic systems in the near future.
Related papers
- A Survey of Quantum Transformers: Architectures, Challenges and Outlooks [82.4736481748099]
Quantum Transformers integrate the representational power of classical Transformers with the computational advantages of quantum computing.<n>Since 2022, research in this area has rapidly expanded, giving rise to diverse technical paradigms and early applications.<n>This paper presents the first comprehensive, systematic, and in-depth survey of quantum Transformer models.
arXiv Detail & Related papers (2025-04-04T05:40:18Z) - A Review of Quantum Scientific Computing Algorithms for Engineering Problems [0.0]
Quantum computing, leveraging quantum phenomena like superposition and entanglement, is emerging as a transformative force in computing technology.
This paper systematically explores the foundational concepts of quantum mechanics and their implications for computational advancements.
arXiv Detail & Related papers (2024-08-25T21:40:22Z) - A Practitioner's Guide to Quantum Algorithms for Optimisation Problems [0.0]
NP-hard optimisation problems are common in industrial areas such as logistics and finance.
This paper aims to provide a comprehensive overview of the theory of quantum optimisation techniques.
It focuses on their near-term potential for noisy intermediate scale quantum devices.
arXiv Detail & Related papers (2023-05-12T08:57:36Z) - Quantum Machine Learning: from physics to software engineering [58.720142291102135]
We show how classical machine learning approach can help improve the facilities of quantum computers.
We discuss how quantum algorithms and quantum computers may be useful for solving classical machine learning tasks.
arXiv Detail & Related papers (2023-01-04T23:37:45Z) - Synergy Between Quantum Circuits and Tensor Networks: Short-cutting the
Race to Practical Quantum Advantage [43.3054117987806]
We introduce a scalable procedure for harnessing classical computing resources to provide pre-optimized initializations for quantum circuits.
We show this method significantly improves the trainability and performance of PQCs on a variety of problems.
By demonstrating a means of boosting limited quantum resources using classical computers, our approach illustrates the promise of this synergy between quantum and quantum-inspired models in quantum computing.
arXiv Detail & Related papers (2022-08-29T15:24:03Z) - Quantum circuit debugging and sensitivity analysis via local inversions [62.997667081978825]
We present a technique that pinpoints the sections of a quantum circuit that affect the circuit output the most.
We demonstrate the practicality and efficacy of the proposed technique by applying it to example algorithmic circuits implemented on IBM quantum machines.
arXiv Detail & Related papers (2022-04-12T19:39:31Z) - Quantum computing at the quantum advantage threshold: a down-to-business
review [1.0323063834827415]
We review the state of the art in quantum computing, promising computational models and the most developed physical platforms.
We also discuss potential applications, the requirements posed by these applications and technological pathways towards addressing these requirements.
The review is written in a simple language without equations, and should be accessible to readers with no advanced background in mathematics and physics.
arXiv Detail & Related papers (2022-03-31T16:55:39Z) - Recompilation-enhanced simulation of electron-phonon dynamics on IBM
Quantum computers [62.997667081978825]
We consider the absolute resource cost for gate-based quantum simulation of small electron-phonon systems.
We perform experiments on IBM quantum hardware for both weak and strong electron-phonon coupling.
Despite significant device noise, through the use of approximate circuit recompilation we obtain electron-phonon dynamics on current quantum computers comparable to exact diagonalisation.
arXiv Detail & Related papers (2022-02-16T19:00:00Z) - Long-Time Error-Mitigating Simulation of Open Quantum Systems on Near Term Quantum Computers [38.860468003121404]
We study an open quantum system simulation on quantum hardware, which demonstrates robustness to hardware errors even with deep circuits containing up to two thousand entangling gates.
We simulate two systems of electrons coupled to an infinite thermal bath: 1) a system of dissipative free electrons in a driving electric field; and 2) the thermalization of two interacting electrons in a single orbital in a magnetic field -- the Hubbard atom.
Our results demonstrate that algorithms for simulating open quantum systems are able to far outperform similarly complex non-dissipative algorithms on noisy hardware.
arXiv Detail & Related papers (2021-08-02T21:36:37Z) - CMOS Quantum Computing: Toward A Quantum Computer System-on-Chip [0.0]
CMOS technology provides potential for the integration of qubits with their control and readout circuits on a single chip.
This paves the way for the realization of a large-scale quantum computing system.
arXiv Detail & Related papers (2020-12-16T15:36:17Z) - Electronic structure with direct diagonalization on a D-Wave quantum
annealer [62.997667081978825]
This work implements the general Quantum Annealer Eigensolver (QAE) algorithm to solve the molecular electronic Hamiltonian eigenvalue-eigenvector problem on a D-Wave 2000Q quantum annealer.
We demonstrate the use of D-Wave hardware for obtaining ground and electronically excited states across a variety of small molecular systems.
arXiv Detail & Related papers (2020-09-02T22:46:47Z) - An Application of Quantum Annealing Computing to Seismic Inversion [55.41644538483948]
We apply a quantum algorithm to a D-Wave quantum annealer to solve a small scale seismic inversions problem.
The accuracy achieved by the quantum computer is at least as good as that of the classical computer.
arXiv Detail & Related papers (2020-05-06T14:18:44Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.