中央研究院 資訊科學研究所

活動訊息

友善列印

學術演講

Exploiting Degeneracy in Belief Propagation Decoding of Quantum Codes

  • 講者賴青沂 教授 (國立交通大學電信所)
    邀請人:鐘楷閔
  • 時間2021-01-19 (Tue.) 13:30 – 15:30
  • 地點資訊所新館101演講廳
摘要

Quantum information needs to be protected by quantum error-correcting codes due to imperfect quantum devices and operations. One would like to have an efficient and high-performance decoding procedure for quantum codes. A potential candidate is Pearl's belief propagation (BP), but its performance suffers from the many short cycles inherent in quantum codes. Many attempts to improve BP decoding of quantum codes have been made in the literature; however,  there is a general impression that BP cannot work for topological codes, such as the surface and toric codes. In this paper, we propose a decoding algorithm (called MBP)  for quantum codes based on  BP  but with a memory effect without any additional overhead. MBP exploits the degeneracy of quantum codes so that it has a better chance to find the most probable error or its degenerate errors. Moreover, the memory effect helps BP converge. MBP significantly improves the decoding performance of usual BP  for various quantum codes, especially highly-degenerate codes (that is, codes with many low-weight stabilizers). For the surface or toric codes, our MBP decoder achieves a threshold of ~16% or  ~17.5%, respectively, over the depolarizing channel.

Reference: https://doi.org/10.1109/JSAIT.2020.3011758

BIO

Quantum information needs to be protected by quantum error-correcting codes due to imperfect quantum devices and operations. One would like to have an efficient and high-performance decoding procedure for quantum codes. A potential candidate is Pearl's belief propagation (BP), but its performance suffers from the many short cycles inherent in quantum codes. Many attempts to improve BP decoding of quantum codes have been made in the literature; however,  there is a general impression that BP cannot work for topological codes, such as the surface and toric codes. In this paper, we propose a decoding algorithm (called MBP)  for quantum codes based on  BP  but with a memory effect without any additional overhead. MBP exploits the degeneracy of quantum codes so that it has a better chance to find the most probable error or its degenerate errors. Moreover, the memory effect helps BP converge. MBP significantly improves the decoding performance of usual BP  for various quantum codes, especially highly-degenerate codes (that is, codes with many low-weight stabilizers). For the surface or toric codes, our MBP decoder achieves a threshold of ~16% or  ~17.5%, respectively, over the depolarizing channel.

Reference: https://doi.org/10.1109/JSAIT.2020.3011758