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IEEE Transactions on Microwave Theory and Techniques

Antenna Array Analysis Through Universal Quantum Computing Processors—A Study on Noise Modeling and Impact

Luca Tosi, Paolo Rocca

Published Dec 29, 2023• 5 citations
Publisher

Abstract

An in-depth study on the effect of real quantum computer noise is proposed in relation to the execution of the quantum Fourier transform (QFT) applied to electromagnetic simulations and in particular to phased array (PA) analysis. In this work, a mathematical formulation of the noise and information loss sources in quantum computers is detailed and embedded in a noise model. The effect of noise on quantum computations is studied using a real quantum computer as well as with the support of a quantum computer emulator.

DOI
10.1109/tmtt.2023.3344878

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An in-depth study on the effect of real quantum computer noise is proposed in relation to the execution of the quantum Fourier transform (QFT) applied to electromagnetic simulations and in particular to phased array (PA) analysis. In this work, a mathematical formulation of the noise and information loss sources in quantum computers is detailed and embedded in a noise model. The effect of noise on quantum computations is studied using a real quantum computer as well as with the support of a quantum computer emulator.
A study on the analysis of the power-pattern of phased-array antennas (PAs) based on the quantum Fourier transform (QFT) is presented. The computation of the power pattern given the set of complex excitations of the PA elements is addressed within the quantum computing (QC) framework by means of a customized procedure that exploits the quantum mechanics principles and theory. A representative set of numerical results, yielded with a quantum computer emulator, is reported and discussed to validate the proposed method also pointing out its features in comparison with the classical approach based on the discrete Fourier transform (DFT).
The analysis of the power pattern of linear phased arrays (PAs) is addressed by exploiting advantages offered by the Quantum Computing (QC) framework. The proposed approach is described in its mathematical formulation and the parallel between the classical Discrete Fourier Transform (DFT) and the Quantum Fourier Transform (QFT) algorithm is discussed in the context of the power pattern analysis. The proposed QFT-based method is validated by means of proof-of-concept results, in order to show the peculiarity of the quantum method in terms of accuracy and computational cost.
Variational quantum algorithms have received substantial theoretical and empirical attention. As the underlying variational quantum circuit (VQC) can be represented by Fourier series that contain an exponentially large spectrum in the number of input features, hope for quantum advantage remains. Nevertheless, it remains an open problem if and how quantum Fourier models (QFMs) can concretely outperform classical alternatives, as the eventual sources of non-classical computational power (for instance, the role of entanglement) are far from being fully understood. Likewise, hardware noise continues to pose a challenge that will persist also along the path towards fault tolerant quantum computers. In this work, we study VQCs with Fourier lenses, which provides possibilities to improve their understanding, while also illuminating and quantifying constraints and challenges. We seek to elucidate critical characteristics of QFMs under the influence of noise. Specifically, we undertake a systematic investigation into the impact of noise on the Fourier spectrum, expressibility, and entangling capability of QFMs through extensive numerical simulations and link these properties to training performance. The insights may inform more efficient utilisation of quantum hardware and support the design of tailored error mitigation and correction strategies. Decoherence imparts an expected and broad detrimental influence across all Ansätze. Nonetheless, we observe that the severity of these deleterious effects varies among different model architectures, suggesting that certain configurations may exhibit enhanced robustness to noise and show computational utility.