Maximum Likelihood Quantum Error Mitigation for Algorithms with a Single Correct Output Article Swipe

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Dror Baron , Hrushikesh Pramod Patil , Huiyang Zhou ·

YOU? · · 2024 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2402.11830

Quantum error mitigation is an important technique to reduce the impact of noise in quantum computers. With more and more qubits being supported on quantum computers, there are two emerging fundamental challenges. First, the number of shots required for quantum algorithms with large numbers of qubits needs to increase in order to obtain a meaningful distribution or expected value of an observable. Second, although steady progress has been made in improving the fidelity of each qubit, circuits with a large number of qubits are likely to produce erroneous results. This low-shot, high-noise regime calls for highly scalable error mitigation techniques. In this paper, we propose a simple and effective mitigation scheme, qubit-wise majority vote, for quantum algorithms with a single correct output. We show that our scheme produces the maximum likelihood (ML) estimate under certain assumptions, and bound the number of shots required. Our experimental results on real quantum devices confirm that our proposed approach requires fewer shots than existing ones, and can sometimes recover the correct answers even when they are not observed from the measurement results.

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Algorithm Computer science Maximum likelihood Quantum Mathematics Statistics Physics Quantum mechanics

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Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/2402.11830
PDF: https://arxiv.org/pdf/2402.11830
OA Status: green
Related Works: 10
OpenAlex ID: https://openalex.org/W4391987897

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DOI: https://doi.org/10.48550/arxiv.2402.11830

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Title: Maximum Likelihood Quantum Error Mitigation for Algorithms with a Single Correct Output

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Language: en

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Publication year: 2024

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Publication date: 2024-02-19

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Authors: Dror Baron, Hrushikesh Pramod Patil, Huiyang Zhou

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Landing page: https://arxiv.org/abs/2402.11830

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PDF URL: https://arxiv.org/pdf/2402.11830

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Concepts: Algorithm, Computer science, Maximum likelihood, Quantum, Mathematics, Statistics, Physics, Quantum mechanics

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