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Benchmarking Quantum Computers and the Impact of Quantum Noise

1 Pith paper cite this work. Polarity classification is still indexing.

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abstract

Benchmarking is how the performance of a computing system is determined. Surprisingly, even for classical computers this is not a straightforward process. One must choose the appropriate benchmark and metrics to extract meaningful results. Different benchmarks test the system in different ways and each individual metric may or may not be of interest. Choosing the appropriate approach is tricky. The situation is even more open ended for quantum computers, where there is a wider range of hardware, fewer established guidelines, and additional complicating factors. Notably, quantum noise significantly impacts performance and is difficult to model accurately. Here, we discuss benchmarking of quantum computers from a computer architecture perspective and provide numerical simulations highlighting challenges which suggest caution.

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eess.SP 1

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2025 1

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representative citing papers

Localized Kernel Methods for Signal Processing

eess.SP · 2025-08-07 · reject · novelty 2.0

The manuscript is internally inconsistent: the abstract describes localized kernel signal processing, while the body is a different paper on quantum task scheduling, leaving the abstract's claims entirely unsupported.

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Showing 1 of 1 citing paper.

  • Localized Kernel Methods for Signal Processing eess.SP · 2025-08-07 · reject · none · ref 33 · internal anchor

    The manuscript is internally inconsistent: the abstract describes localized kernel signal processing, while the body is a different paper on quantum task scheduling, leaving the abstract's claims entirely unsupported.