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.
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Presenters
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Volodymyr Sivak
Google Quantum AI, Yale University
Authors
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Volodymyr Sivak
Google Quantum AI, Yale University
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Michael Newman
Google LLC, Google Quantum AI
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Cody Jones
Google LLC, Google Quantum AI
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Henry Schurkus
Google Quantum AI
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Dvir Kafri
Google Quantum AI
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Yuri D Lensky
Google Quantum AI
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Paul Klimov
Google Quantum AI, Google AI, Quantum
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Kostyantyn Kechedzhi
Google Quantum AI, Google LLC
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Vadim Smelyanskiy
Google Quantum AI, Google LLC