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Research Trends in Quantum Error Decoders for Fault-Tolerant Quantum Computing

결함허용 양자 컴퓨팅을 위한 양자 오류 복호기 연구 동향

  • E.Y. Cho ;
  • J.H. On ;
  • C.Y. Kim ;
  • G. Cha
  • 조은영 (클라우드기반SW연구실) ;
  • 온진호 (클라우드기반SW연구실) ;
  • 김재열 (클라우드기반SW연구실) ;
  • 차규일 (클라우드기반SW연구실)
  • Published : 2023.10.01

Abstract

Quantum error correction is a key technology for achieving fault-tolerant quantum computation. Finding the best decoding solution to a single error syndrome pattern counteracting multiple errors is an NP-hard problem. Consequently, error decoding is one of the most expensive processes to protect the information in a logical qubit. Recent research on quantum error decoding has been focused on developing conventional and neural-network-based decoding algorithms to satisfy accuracy, speed, and scalability requirements. Although conventional decoding methods have notably improved accuracy in short codes, they face many challenges regarding speed and scalability in long codes. To overcome such problems, machine learning has been extensively applied to neural-network-based error decoding with meaningful results. Nevertheless, when using neural-network-based decoders alone, the learning cost grows exponentially with the code size. To prevent this problem, hierarchical error decoding has been devised by combining conventional and neural-network-based decoders. In addition, research on quantum error decoding is aimed at reducing the spacetime decoding cost and solving the backlog problem caused by decoding delays when using hardware-implemented decoders in cryogenic environments. We review the latest research trends in decoders for quantum error correction with high accuracy, neural-network-based quantum error decoders with high speed and scalability, and hardware-based quantum error decoders implemented in real qubit operating environments.

Keywords

Acknowledgement

본 연구 논문은 정부(과학기술정보통신부)의 재원으로 정보통신기획평가원의 지원을 받아 수행된 연구임[No. 2020-0-00014, 결함 허용 논리양자큐빗 컴퓨팅 환경을 제공하는 양자운영체제 원천기술 개발].

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