Work

Soft information decoding with superconducting qubits

Year: 2026

Type: article

Abstract: Quantum error correction promises a viable path to fault-tolerant computations, enabling exponential error suppression when the device's error rates remain below the protocol's threshold. However, this threshold strongly depends on the classical method used to decode the measurements of the syndrome. These classical algorithms traditionally only interpret binary data, ignoring valuable information contained in complete analog measurement data. We present the first large-scale experimental verification of soft decoding by implementing repetition codes up to distance 51 on superconducting hardware. Unlike previous demonstrations limited to small code distances, this extensive range allows us to confirm a fundamental improvement in the exponential scaling of error suppression rather than a mere constant-factor reduction in error rates. We observe a 25% increase in the threshold, which yields logical error rates up to 30 times lower than standard hard decoding. Analyzing the trade-off between information volume and decoding performance, we show that a single byte of information per measurement suffices to reach optimal decoding. This underscores the effectiveness and practicality of soft decoding on hardware, including in time-sensitive contexts such as real-time decoding.

Source: APS Open Science

DOI: 10.1103/y9fh-4x6n

Authors: Maurice D. Hanisch, Bence Hetényi, James R. Wootton

Institutions: ETH Zurich, IBM Research - Zurich, University of Basel

Language: English

Topic: Quantum Computing Algorithms and Architecture

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, National Center of Competence in Research Affective Sciences - Emotions in Individual Behaviour and Social Processes, NCCR Catalysis

Award: NCCR SPIN: Spin Qubits in Silicon