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Research questionHow can synthetic-noise benchmarks reliably predict decoder rankings on real quantum hardware?Decoders are often ranked using synthetic circuit-level noise, but real hardware can assign different error rates to different operations. The resulting mismatch makes it unclear when simulated rankings reflect decoder performance on a device.
Evaluation & Benchmarks
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Latest papersRecent research connected to this question, newest first.A Sim-to-Real Study of Surface-Code Decoder BenchmarkingThe evidence concerns six surface-code decoders evaluated with four progressively detailed noise models against Willow processor data across three code distances, two bases, and fifteen round counts. It also includes an independent hardware evaluation of NVIDIA's Ising pre-decoder under specified mapping and receptive-field conditions; conclusions are limited to these devices, decoders, and evaluation settings.research paper · Sep 3, 2026
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How can quantum neural networks prevent simulator-era postprocessing from silently discarding hardware measurements?How can we tell whether hardware noise distorts a quantum-kernel Gram matrix in task-relevant ways?How can quantum error-correcting encodings adapt to device-specific noise with less overhead?How can machine-learning decoders for quantum error correction generalize to unseen codes while providing calibrated uncertainty?
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