中国物理B ›› 2010, Vol. 19 ›› Issue (8): 80307-080307.doi: 10.1088/1674-1056/19/8/080307

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Jointly-check iterative decoding algorithm for quantum sparse graph codes

邵军虎, 白宝明, 林伟, 周林   

  1. State Key Lab of Integrated Service Networks, Xidian University, Xi'an 710071, China
  • 收稿日期:2009-10-12 修回日期:2010-03-22 出版日期:2010-08-15 发布日期:2010-08-15
  • 基金资助:
    Project supported by the National Natural Science Foundation of China (Grant No. 60972046) and Grant from the National Defense Pre-Research Foundation of China.

Jointly-check iterative decoding algorithm for quantum sparse graph codes

Shao Jun-Hu(邵军虎), Bai Bao-Ming(白宝明), Lin Wei(林伟), and Zhou Lin(周林)   

  1. State Key Lab of Integrated Service Networks, Xidian University, Xi'an 710071, China
  • Received:2009-10-12 Revised:2010-03-22 Online:2010-08-15 Published:2010-08-15
  • Supported by:
    Project supported by the National Natural Science Foundation of China (Grant No. 60972046) and Grant from the National Defense Pre-Research Foundation of China.

摘要: For quantum sparse graph codes with stabilizer formalism, the unavoidable girth-four cycles in their Tanner graphs greatly degrade the iterative decoding performance with a standard belief-propagation (BP) algorithm. In this paper, we present a jointly-check iterative algorithm suitable for decoding quantum sparse graph codes efficiently. Numerical simulations show that this modified method outperforms the standard BP algorithm with an obvious performance improvement.

Abstract: For quantum sparse graph codes with stabilizer formalism, the unavoidable girth-four cycles in their Tanner graphs greatly degrade the iterative decoding performance with a standard belief-propagation (BP) algorithm. In this paper, we present a jointly-check iterative algorithm suitable for decoding quantum sparse graph codes efficiently. Numerical simulations show that this modified method outperforms the standard BP algorithm with an obvious performance improvement.

Key words: quantum error correction, sparse graph code, iterative decoding, belief-propagation algorithm

中图分类号:  (Formalism)

  • 03.65.Ca
02.10.Ox (Combinatorics; graph theory) 02.60.Cb (Numerical simulation; solution of equations) 03.67.Pp (Quantum error correction and other methods for protection against decoherence)