Optimizing continuous-time quantum error correction for Markovian and non-Markovian noise models
Phys. Rev. A 114, 032438 – Published 16 September, 2026
DOI: https://doi.org/10.1103/5zyg-lhjt
Abstract
We present a protocol using neural networks to simultaneously optimize the quantum error-correcting code space and the corresponding recovery map in the framework of continuous-time quantum error correction. Given a Hilbert space and a noise process—potentially correlated across both space and time—the protocol identifies the optimal recovery strategy, measured by the average logical state fidelity. This approach enables the discovery of recovery schemes tailored to arbitrary device-level noise.
