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2018

Optimizing Quantum Error Correction Codes with Reinforcement Learning

Nautrup, Hendrik Poulsen, Delfosse, Nicolas, Dunjko, Vedran et al.

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Quantum error correction is widely thought to be the key to fault-tolerant quantum computation.

However, determining the most suited encoding for unknown error channels or specific laboratory setups is highly challenging.
Here, we present a reinforcement learning framework for optimizing and fault-tolerantly adapting quantum error correction codes.
We consider a reinforcement learning agent tasked with modifying a family of surface code quantum memories until a desired logical error rate is reached.

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