C032 - The measured 16-cycle error of 0.07(1) is consistent with the value 3.2 p predicted by th...
Verdict: partial
Location: Experimental error analysis
Type / expected artifact: numeric / numeric
Claim: The measured 16-cycle error of 0.07(1) is consistent with the value 3.2 p predicted by the correlated bit-flip error model.
Models: extraction claude-opus-4-8; verification gpt-5; verification_chain claude-opus-4-8 -> gpt-5; verdict_chain partial -> partial.
Limitations: paper_text_only.
Source location(s): source/main.tex:155 (Experimental error analysis).
Conclusion
Internal-consistency check. Paper: measured 16-cycle error 0.07(1), model prediction 3.2 p with measured p ~= 0.02 after 16 cycles (C031), measured fidelity F=93(1)%. Computed: 1 - 0.93 = 0.070 (matches 0.07(1)); 3.2 * 0.02 = 0.064, which lies inside the +-1 sigma band [0.060, 0.080]; |0.064 - 0.070| = 0.006 < tolerance 0.01. Consistent. Capped at partial because it depends on the measured (not reconstructed) values p~=0.02 and F=0.93; provenance paper_text_only.
Verification details
Executable rerun: run.py exited 0 in 0.366s; log verification/C032/attempts/R002/run.log.
Output excerpt:
measured 16-cycle error = 1 - F = 1 - 0.93 = 0.070 (paper: 0.07(1))
measured error band (+-1 sigma): [0.060, 0.080]
model prediction 3.2 p = 3.2 * 0.02 = 0.0640
prediction inside measured band? True
p that would give central 0.07 exactly: 0.07/3.2 = 0.0219
|3.2p - 0.07| = 0.0060 (tolerance = 0.01)