Learning logical Pauli noise in quantum error correction

Abstract

The characterization of quantum devices is crucial for their practical implementation but can be costly in experimental effort and classical postprocessing. Therefore, it is desirable to measure only the information that is relevant for specific applications and develop protocols that require little additional effort. In this work, we focus on the characterization of quantum computers in the context of stabilizer quantum error correction. For arbitrary stabilizer codes, subsystem codes, and data syndrome codes, we prove that the logical error channel induced by Pauli noise can be estimated from syndrome data under minimal conditions. More precisely, for any such code, we show that the estimation is possible as long as the code can correct the noise.

5+8 pages; v2: close to published version

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Cited by in corpus (9)

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• Quantum computer error structure probed by quantum error correction syndrome measurements
• Fault-tolerant compiling of classically hard IQP circuits on hypercubes
• Efficient self-consistent learning of gate set Pauli noise
• Error mitigation and circuit division for early fault-tolerant quantum phase estimation
• Characterizing physical and logical errors in a transversal CNOT via cycle error reconstruction
• Quantum subspace verification for error correction codes
• Disambiguating Pauli noise in quantum computers