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Author

Askery Canabarro

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Preprint Jul 2026

Machine-learned syndrome post-selection for reliable quantum error correction

Quantum error correction can be enhanced by post-selecting out runs that are likely to produce a logical failure, but the most accurate measures for that require costly decoder-level information. We introduce a practical, decoder-agnostic post-selection method that learns directly from syndrome data. The method trains...

Tobias Haug, Askery Canabarro, Leandro Aolita · 1 citation

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