Surf-Deformer: Mitigating Dynamic Defects on Surface Code via Adaptive Deformation

Keyi Yin, Xiang Fang, Travis S. Humble, Ang Li, Yunong Shi, Yufei Ding

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we introduce Surf-Deformer, a code deformation framework that seamlessly integrates adaptive defect mitigation functionality into the current surface code workflow. It crafts several basic deformation instructions based on fundamental gauge transformations, which can be combined to explore a larger design space than previous methods. This enables more optimized deformation processes tailored to specific defect situations, restoring the QEC capability of deformed codes more efficiently with minimal qubit resources. Additionally, we design an adaptive code layout that accommodates our defect mitigation strategy while ensuring efficient execution of logical operations. Our evaluation shows that Surf-Deformer outperforms previous methods by significantly reducing the end-To-end failure rate of various quantum programs by 35× to 70×, while requiring only about 50% of the qubit resources compared to the previous method to achieve the same level of failure rate. Ablation studies show that Surf-Deformer surpasses previous defect removal methods in preserving QEC capability and facilitates surface code communication by achieving nearly optimal throughnut.

Original languageEnglish
Title of host publicationProceedings - 2024 57th Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2024
PublisherIEEE Computer Society
Pages750-764
Number of pages15
ISBN (Electronic)9798350350579
DOIs
StatePublished - 2024
Event57th Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2024 - Austin, United States
Duration: Nov 2 2024Nov 6 2024

Publication series

NameProceedings of the Annual International Symposium on Microarchitecture, MICRO
ISSN (Print)1072-4451

Conference

Conference57th Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2024
Country/TerritoryUnited States
CityAustin
Period11/2/2411/6/24

Funding

We thank the anonymous reviewers for their constructive feedback and AWS Cloud Credit for Research. This work is supported in part by Robert N.Noyce Trust, NSF 2048144, NSF 2422169, NSF 2427109. This material is based upon work supported by the U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers, Quantum Science Center. This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725. The Pacific Northwest National Laboratory is operated by Battelle for the U.S. Department of Energy under Contract DE-AC05-76RL01830.

Keywords

  • Dynamic Defect
  • Quantum Error Correction

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