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HAMMER: boosting fidelity of noisy Quantum circuits by exploiting Hamming behavior of erroneous outcomes

Published: 22 February 2022 Publication History

Abstract

Quantum computers with hundreds of qubits will be available soon. Unfortunately, high device error-rates pose a significant challenge in using these near-term quantum systems to power real-world applications. Executing a program on existing quantum systems generates both correct and incorrect outcomes, but often, the output distribution is too noisy to distinguish between them. In this paper, we show that erroneous outcomes are not arbitrary but exhibit a well-defined structure when represented in the Hamming space. Our experiments on IBM and Google quantum computers show that the most frequent erroneous outcomes are more likely to be close in the Hamming space to the correct outcome. We exploit this behavior to improve the ability to infer the correct outcome.
We propose Hamming Reconstruction (HAMMER), a post-processing technique that leverages the observation of Hamming behavior to reconstruct the noisy output distribution, such that the resulting distribution has higher fidelity. We evaluate HAMMER using experimental data from Google and IBM quantum computers with more than 500 unique quantum circuits and obtain an average improvement of 1.37x in the quality of solution. On Google’s publicly available QAOA datasets, we show that HAMMER sharpens the gradients on the cost function landscape.

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      cover image ACM Conferences
      ASPLOS '22: Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems
      February 2022
      1164 pages
      ISBN:9781450392051
      DOI:10.1145/3503222
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      Published: 22 February 2022

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      1. NISQ
      2. Quantum Compilers
      3. Quantum Computing

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      • (2024)Red-QAOA: Efficient Variational Optimization through Circuit ReductionProceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 210.1145/3620665.3640363(980-998)Online publication date: 27-Apr-2024
      • (2024)Elivagar: Efficient Quantum Circuit Search for ClassificationProceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 210.1145/3620665.3640354(336-353)Online publication date: 27-Apr-2024
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