Correlating quantum algorithm execution fidelity with underlying physical noise using a fast noise-tracking framework
ORAL
Abstract
Parameters governing qubit properties and their interactions with the environment can fluctuate significantly over time, impacting the fidelity of quantum algorithm execution. While these fluctuations are known to affect algorithmic outcomes, the relative importance of different types of noise remains unclear. We present a fast and sparse noise-tracking framework capable of characterizing device noise using minimal overhead. By interleaving a 100-qubit quantum simulation algorithm with concurrent noise tracking on a superconducting qubit device, we directly correlate fluctuations in algorithmic results with variations in underlying noise parameters.
This approach enables us to identify which noise sources most significantly affect algorithm performance, providing a pathway to prioritize mitigation strategies and improve quantum computational reliability.
This approach enables us to identify which noise sources most significantly affect algorithm performance, providing a pathway to prioritize mitigation strategies and improve quantum computational reliability.
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Publication: Agarwal, A., Lindoy, L. P., Rath, Y., Rungger, I. Correlating quantum algorithm execution fidelity with underlying physical noise using a fast noise-tracking framework (in preparation)
Agarwal, A., Lindoy, L. P., Lall, D., de Graaf, S. E., Lindström, T., & Rungger, I. (2025). Fast-tracking and disentangling of qubit noise fluctuations using minimal-data averaging and hierarchical discrete fluctuation auto-segmentation. arXiv preprint arXiv:2505.23622.
Lall, D., Agarwal, A., Zhang, W., et al. (2025). A review and collection of metrics and benchmarks for quantum computers: definitions, methodologies and software. arXiv preprint arXiv:2502.06717.
Presenters
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Abhishek Agarwal
- National Physical Laboratory (NPL)