Enhancing Quantum Memory Lifetime with Measurement-Free Local Error Correction and Reinforcement Learning
<|reference_start|>Enhancing Quantum Memory Lifetime with Measurement-Free Local Error Correction and Reinforcement Learning: Reliable quantum computation requires systematic identification and correction of errors that occur and accumulate in quantum hardware. To diagnose and correct such errors, standard quantum error-correcting protocols utilize $\textit{global}$ error information across the system obtained by mid-circuit readout of ancillary qubits. We investigate circuit-level error-correcting protocols that are measurement-free and based on $\textit{local}$ error information. Such a local error correction (LEC) circuit consists of faulty multi-qubit gates to perform both syndrome extraction and ancilla-controlled error removal. We develop and implement a reinforcement learning framework that takes a fixed set of faulty gates as inputs and outputs an optimized LEC circuit. To evaluate this approach, we quantitatively characterize an extension of logical qubit lifetime by a noisy LEC circuit. For the 2D classical Ising model and 4D toric code, our optimized LEC circuit performs better at extending a memory lifetime compared to a conventional LEC circuit based on Toom's rule in a sub-threshold gate error regime. We further show that such circuits can be used to reduce the rate of mid-circuit readouts to preserve a 2D toric code memory. Finally, we discuss the application of the LEC protocol on dissipative preparation of quantum states with topological phases.<|reference_end|>
@article{park2024enhancing,
    title={Enhancing Quantum Memory Lifetime with Measurement-Free Local Error
  Correction and Reinforcement Learning},
    author={Mincheol Park, Nishad Maskara, Marcin Kalinowski, Mikhail D. Lukin},
    journal={arXiv preprint arXiv:2408.09524},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.09524},
    primaryClass={quant-ph cs.LG physics.comp-ph}
}