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URSI General Assembly and Scientific Symposium

Insights on Quantum Computing Operators for EM Optimization

Riccardo Enrico Zich, Eleonora Lorenza Zich, Riccardo Enrico Zich

Published Jan 1, 2023• 1 citation
Publisher

Abstract

The introduction of quantum computing is right now dramatically impacting the research activities in many engineering fields, in particular where a lot of data have to be considered, stored, analyzed to find the best possible strategy to tackle a complex problem, such as dealing with electromagnetic (EM) optimization.In fact, EM problems are critical from a computational point of view, because they often require thousands of different numerical solutions that can be obtained by extremely time and resource consuming numerical solvers both in the frequency or in the time domain.In this framework, the combined application of quantum computing and evolutionary optimization algorithms can have a great effectiveness to manage the electromagnetic optimization of complex structures.

DOI
10.46620/ursigass.2023.3623.bfcv1138

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The introduction of quantum computing is right now dramatically impacting the research activities in many engineering fields, in particular where a lot of data have to be considered, stored, analyzed to find the best possible strategy to tackle a complex problem, such as dealing with electromagnetic (EM) optimization.In fact, EM problems are critical from a computational point of view, because they often require thousands of different numerical solutions that can be obtained by extremely time and resource consuming numerical solvers both in the frequency or in the time domain.In this framework, the combined application of quantum computing and evolutionary optimization algorithms can have a great effectiveness to manage the electromagnetic optimization of complex structures.
Quantum computing is an extremely promising tool that could dramatically change many engineering fields where computationally heavy tasks have to be dealt with such as electromagnetic optimization. Electromagnetic problems, in fact, are extremely computationally expensive, and an heuristic optimization may need thousands of generations. In this paper, the problems and the potential of the introduction of quantum computing in optimization has been investigated. Numerical results on the preliminary test are provided here while more detailed results will be directly presented at the conference.
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