Modeling the performance of the surface code with non-uniform error distribution: Part 2

ORAL

Abstract

Quantum error correction with the surface code is a promising route towards fault-tolerant quantum computation. Most numerical simulations of the surface code use simplified noise models with identical error rates on all qubits. However, real quantum processors have nontrivial error distributions, where some qubits are significantly worse than others. We analyze the dependence of the code performance on the distribution of the physical error rates in the system, and develop a simple and fast predictive model of the logical error rate.

Presenters

  • Volodymyr Sivak

    Google Quantum AI, Yale University

Authors

  • Volodymyr Sivak

    Google Quantum AI, Yale University

  • Michael Newman

    Google LLC, Google Quantum AI

  • Cody Jones

    Google LLC, Google Quantum AI

  • Henry Schurkus

    Google Quantum AI

  • Dvir Kafri

    Google Quantum AI

  • Yuri D Lensky

    Google Quantum AI

  • Paul Klimov

    Google Quantum AI, Google AI, Quantum

  • Kostyantyn Kechedzhi

    Google Quantum AI, Google LLC

  • Vadim Smelyanskiy

    Google Quantum AI, Google LLC