Learning to Concatenate Quantum Codes

The paper proposes a hybrid, learning‑based strategy for selecting quantum error‑correcting codes at each concatenation level. By estimating the effective noise channel after each level, the method chooses small, non‑additive encoders when the noise has structure and switches to standard codes as the noise becomes uniform. Simulations show that this adaptive approach can achieve a target logical error rate with up to two orders of magnitude fewer qubits than using stabilizer codes alone for strongly structured noise.

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