arXiv (All)
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Fooling the Decoder: An Adversarial Attack on Quantum Error Correction
Neural network decoders are essential for fault-tolerant quantum computation, yet their internal mechanisms remain poorly understood. Leading machine learning decoders use recurrent and transformer models (e.g., AlphaQubit), and reinforcement learning (RL) is increasingly used to train such models.
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