Quantum error-correction using humming sparrow optimization based self-adaptive deep cnn noise correction module.

ABSTRACT: The error correction model's main purpose in heavy hexagonal quantum codes is to improve their reliability for quantum computing applications. Existing challenges include finding the optimal decoder for quantum error correction in heavy hexagonal codes. This research propels the frontier of quantum error correction, with a specific focus on tailoring topological quantum error-correcting codes for the unique challenges posed by superconducting qubits in quantum computers. In response, this research harnesses the power of deep learning, presenting a Humming sparrow optimization based self-adaptive deep CNN (HSO-based SADCNN) model designed for heavy hexagonal codes. This decoder incorporates a Self-adaptive Deep CNN (SADCNN) Noise Correction Module, a sophisticated component to refine error

SUBMITTER: Shinde UU 

PROVIDER: S-EPMC11192916 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature