Compilation-informed probabilistic quantum error cancellation

• URL: http://arxiv.org/abs/2508.20174v1
• Date: Wed, 27 Aug 2025 18:00:10 GMT
• Title: Compilation-informed probabilistic quantum error cancellation
• Authors: Giancarlo Camilo, Thiago O. Maciel, Allan Tosta, Abdulla Alhajri, Thais de Lima Silva, Daniel Stilck França, Leandro Aolita,
• Abstract summary: We introduce a quantum error mitigation (QEM) scheme against both compilation errors and logical-gate noise that is circuit-, QEC code-, and compiler-agnostic.<n>It features maximal circuit size and QEC code-distance both independent of the target precision, in contrast to strategies based on QEC alone.<n>Our method significantly reduces quantum resource requirements for high-precision estimations, offering a practical route towards fault-tolerant quantum computation with precision-independent overheads.
• Score: 2.079863206645103
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The potential of quantum computers to outperform classical ones in practically useful tasks remains challenging in the near term due to scaling limitations and high error rates of current quantum hardware. While quantum error correction (QEC) offers a clear path towards fault tolerance, overcoming the scalability issues will take time. Early applications will likely rely on QEC combined with quantum error mitigation (QEM). We introduce a QEM scheme against both compilation errors and logical-gate noise that is circuit-, QEC code-, and compiler-agnostic. The scheme builds on quasi-probability distribution methods and uses information about the circuit's gates' compilations to attain an unbiased estimation of noiseless expectation values incurring a constant sample-complexity overhead. Moreover, it features maximal circuit size and QEC code-distance both independent of the target precision, in contrast to strategies based on QEC alone. We formulate the mitigation procedure as a linear program, demonstrate its efficacy through numerical simulations, and illustrate it for estimating the Jones polynomials of knots. Our method significantly reduces quantum resource requirements for high-precision estimations, offering a practical route towards fault-tolerant quantum computation with precision-independent overheads.

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