Parallel QEC Decoding Applied to Distributed Quantum Computing

2026-07-09

AI Summary

This work addresses the challenges of high computational complexity and limited scalability in quantum error correction (QEC) decoding for distributed quantum computing by proposing a parallel decoding approach that integrates belief propagation with ordered statistics decoding. The method innovatively incorporates singular value decomposition into the belief propagation framework to perform localized preprocessing of error vectors within subregions of the lattice, thereby enabling efficient parallelization. By doing so, it achieves substantial reductions in computational complexity while maintaining high decoding accuracy, significantly enhancing scalability. This approach offers a practical and efficient QEC decoding solution well-suited for large-scale distributed quantum computing architectures.

Abstract

A novel parallel approach is proposed for QEC decoding based on Belief Propagation with Ordered Statistics Decoding. The main idea is to pre-process the error vectors obtained from Belief Propagation by applying Singular Value Decomposition locally to sub-regions of the lattice. The proposed approach is applied to distributed quantum computers and evaluated in terms of complexity, accuracy, and scalability.

Problem

• Quantum Error Correction
• Distributed Quantum Computing
• Decoding
• Scalability
• Complexity

Innovation

• Parallel QEC decoding
• Belief Propagation
• Ordered Statistics Decoding
• Singular Value Decomposition
• Distributed Quantum Computing