Hybrid Reinforcement Learning of QLego Generated Stabilizer Codes

Quantum error correction is a fundamental requirement for digital quantum computation. One of the most commonly used forms of quantum error corraction is that of stabilizer codes. The QLego formalism has introduced a systematic way of constructing new stabilizer codes out of basic lego-like building blocks. In previous work [1], we have shown how to leverage that formalism along with reinforcement learning to generate new stabilizer code. Here, we take this a step further and show how a hybrid classical-quantum algorithm can be used to generate stabilizer codes tailored for a specific quantum device.

[1] https://arxiv.org/abs/2305.06378