SOURCE-LINKED INTELLIGENCE
Securing quantum error correction against misleading advice from AI agents
Can an attacker turn influence over an artificial intelligence (AI) adviser into a harmful quantum error-correction update? We identify an ambiguity in passive syndrome records that obstructs recovery selection, then show how additional calibration measurements support certified recovery updates under uncertainty and drift. In an odd-distance square toric code with error-free preparation, syndrome measurements, and recovery operations, opposite coherent $X$ rotations produce identical passive syndrome-history distributions. Yet a fixed phase correction can help at one sign and harm at the othe
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Evidence & attribution
- arXiv · Artificial Intelligence · 2026-09-16T17:26:54.000Z
- arXiv · AI, language, vision and robotics · 2026-09-16T17:26:54.000Z
First collected: 2026-09-19T20:26:32.566Z. This is not the publication date.