Federated Model Training Method for Distributed IoT Terminals Based on Privacy-Preserving FedAvg

Abstract

 Effective error correction is required to mitigate the effects of physical noise and safeguard logical qubits for fault-tolerant computation in order to realize large-scale quantum computers. Because physical gate defects, measurement mistakes, leakage errors, and correlated noise can propagate across processing levels, single-level quantum error correction is typically not appropriate for large-scale quantum structures. This research proposes a multi-level quantum error correction framework for scalable quantum computing architectures. Physical-layer syndrome extraction, logical-layer stabilizer decoding, and architecture-level error propagation control are the methods used. To minimize the buildup of logical errors in the deep circuit and under qubit connection limits, a multi-level decoding technique is employed. According to the simulation results, the suggested framework increases the fault-tolerant circuit success rate by 12.6% over single-level correction and has a logical error rate of 1.7×10⁻⁵ under a physical error rate of 10⁻³. According to the research, a large-scale quantum computing system can be made more reliable by utilizing many tiers of quantum error correction.