Experimentally Informed Decoding of Stabilizer Codes Based on Syndrome Correlations

Fuente: arXiv
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Autores principales: Remm, Ants, Lacroix, Nathan, Bödeker, Lukas, Genois, Elie, Hellings, Christoph, Swiadek, François, Norris, Graham J., Eichler, Christopher, Blais, Alexandre, Müller, Markus, Krinner, Sebastian, Wallraff, Andreas
Formato: Preprint
Publicado: 2025
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author Remm, Ants
Lacroix, Nathan
Bödeker, Lukas
Genois, Elie
Hellings, Christoph
Swiadek, François
Norris, Graham J.
Eichler, Christopher
Blais, Alexandre
Müller, Markus
Krinner, Sebastian
Wallraff, Andreas
author_facet Remm, Ants
Lacroix, Nathan
Bödeker, Lukas
Genois, Elie
Hellings, Christoph
Swiadek, François
Norris, Graham J.
Eichler, Christopher
Blais, Alexandre
Müller, Markus
Krinner, Sebastian
Wallraff, Andreas
contents High-fidelity decoding of quantum error correction codes relies on an accurate experimental model of the physical errors occurring in the device. Because error probabilities can depend on the context of the applied operations, the error model is ideally calibrated using the same circuit as is used for the error correction experiment. Here, we present an experimental approach guided by a novel analytical formula to characterize the probability of independent errors using correlations in the syndrome data generated by executing the error correction circuit. Using the method on a distance-three surface code, we analyze error channels that flip an arbitrary number of syndrome elements, including Pauli Y errors, hook errors, multi-qubit errors, and leakage, in addition to standard Pauli X and Z errors. We use the method to find the optimal weights for a minimum-weight perfect matching decoder without relying on a theoretical error model. Additionally, we investigate whether improved knowledge of the Pauli Y error channel, based on correlating the X- and Z-type error syndromes, can be exploited to enhance matching decoding. Furthermore, we find correlated errors that flip many syndrome elements over up-to-eight cycles, potentially caused by leakage of the data qubits out of the computational subspace. The presented method provides the tools for accurately calibrating a broad family of decoders, beyond the minimum-weight perfect matching decoder, without relying on prior knowledge of the error model.
format Preprint
id arxiv_https___arxiv_org_abs_2502_17722
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Experimentally Informed Decoding of Stabilizer Codes Based on Syndrome Correlations
Remm, Ants
Lacroix, Nathan
Bödeker, Lukas
Genois, Elie
Hellings, Christoph
Swiadek, François
Norris, Graham J.
Eichler, Christopher
Blais, Alexandre
Müller, Markus
Krinner, Sebastian
Wallraff, Andreas
Quantum Physics
High-fidelity decoding of quantum error correction codes relies on an accurate experimental model of the physical errors occurring in the device. Because error probabilities can depend on the context of the applied operations, the error model is ideally calibrated using the same circuit as is used for the error correction experiment. Here, we present an experimental approach guided by a novel analytical formula to characterize the probability of independent errors using correlations in the syndrome data generated by executing the error correction circuit. Using the method on a distance-three surface code, we analyze error channels that flip an arbitrary number of syndrome elements, including Pauli Y errors, hook errors, multi-qubit errors, and leakage, in addition to standard Pauli X and Z errors. We use the method to find the optimal weights for a minimum-weight perfect matching decoder without relying on a theoretical error model. Additionally, we investigate whether improved knowledge of the Pauli Y error channel, based on correlating the X- and Z-type error syndromes, can be exploited to enhance matching decoding. Furthermore, we find correlated errors that flip many syndrome elements over up-to-eight cycles, potentially caused by leakage of the data qubits out of the computational subspace. The presented method provides the tools for accurately calibrating a broad family of decoders, beyond the minimum-weight perfect matching decoder, without relying on prior knowledge of the error model.
title Experimentally Informed Decoding of Stabilizer Codes Based on Syndrome Correlations
topic Quantum Physics
url https://arxiv.org/abs/2502.17722