Ran a compiler-generated 3-qubit bit-flip code on Rigetti's Cepheus-1-108Q via Braket, syndrome correctly identified the injected error in 87% of shots, 94.5% logical error recovery under hardware noise
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I've been building QSHL (Quantum Self-Healing Language), a small compiler that emits OpenQASM 3.0 with error-correction circuits generated from a high-level specification rather than hand-wired syndrome logic. I wanted to validate the syndrome extraction on real hardware, not just simulators. Setup: 3-qubit bit-flip repetition code Two parity syndromes: s0 = parity(q0,q1) s1 = parity(q1,q2) Syndrome extraction via ancilla qubits Deliberate X error injected on q0 Expected syndrome: "10" Execution: Rigetti Cephus-1-108Q via Amazon Braket 100 shots Observed syndrome distribution: 10 (expected): 87% 11: 5% 00: 5% 01: 3% Using post-process syndrome decoding, the logical recovery rate was 94.5%. The non-ideal outcomes are consistent with real hardware effects: readout noise gate infidelity decoherence routing/SWAP overhead across the device topology For comparison, the same circuit executed deterministically on SV1 (1000/1000 expected outcomes), so the spread here is clearly hardware-driven. Important caveats: this is post-process decoding, not active fault tolerance not closed-loop real-time correction not a logical memory lifetime experiment distance-1 repetition code only Next steps are: mid-circuit measurement + conditional feedback repeated syndrome cycles higher-distance codes cross-hardware benchmarking Happy to answer questions about the compiler or lowering pipeline. submitted by /u/DestinyInDepth [link] [comments]