Key Findings
Quantinuum reported a logical memory fidelity of 99.9995% on its commercial Helios trapped-ion quantum computer. This performance corresponds to a logical error rate of 5 × 10-6 per syndrome-extraction round when utilizing a distance-7 code. The results, based on a 137-barium (137 Ba+) QCCD processor, show that logical error rates are suppressed exponentially as the code distance increases from d = 3 to d = 7.
Technical Implementation
The achievement relies on three primary architectural pillars:
- Exponential Distance Scaling: With an experimental suppression factor of Λ = 12, Quantinuum projects that target logical error rates of 10-12 across 100 logical qubits can be reached using approximately 30,000 physical qubits.
- Leakage Reduction: The system employs a dual-layer approach to prevent state leakage. This includes hardware-level 3-cycle mid-circuit 1762 nm optical repumping, which reduces leakage by 6.5x, and software-driven SWAP-superdense leakage reduction circuits.
- Neural Network Decoders: To enable real-time streaming decoding, Quantinuum implemented 3D Convolutional Neural Networks (3D CNN) and Round-Token Transformers (RTT) on NVIDIA H100 hardware. These models achieved per-round latencies between 0.2 ms and 0.5 ms.
Comparative Analysis
Quantinuum distinguished its logical memory fidelity from Google Quantum AI’s magic-state cultivation results on the Willow processor. While Google achieved 99.99% magic-state fidelity via post-selection (retaining ~8% of attempts), Quantinuum’s Helios benchmark measures end-to-end logical memory accuracy. Quantinuum noted that in 2025, it previously demonstrated 99.993% magic-state fidelity with an 85% retention rate using its QCCD architecture, requiring smaller space-time overheads.
Significance and Outlook
These empirical results align with the performance targets for Apollo, Quantinuum’s planned universal fault-tolerant quantum system scheduled for 2029.
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