Benchmarking the Planar Honeycomb Code
Craig Gidney, Michael Newman, Matt McEwen
Abstract
We improve the planar honeycomb code by describing boundaries that need no additional physical connectivity, and by optimizing the shape of the qubit patch. We then benchmark the code using Monte Carlo sampling to estimate logical error rates and derive metrics including thresholds, lambdas, and teraquop qubit counts. We determine that the planar honeycomb code can create a logical qubit with one-in-a-trillion logical error rates using 7000 physical qubits at a 0.1% gate-level error rate (or 900 physical qubits given native two-qubit parity measurements). Our results cement the honeycomb code as a promising candidate for two-dimensional qubit architectures with sparse connectivity.
Topics & Concepts
QubitComputer scienceBenchmarkingPlanarBenchmark (surveying)AlgorithmHoneycombCode (set theory)Concatenation (mathematics)Monte Carlo methodTheoretical computer scienceParallel computingTopology (electrical circuits)MathematicsPhysicsArithmeticQuantumStatisticsGeometryQuantum mechanicsCombinatoricsMarketingSet (abstract data type)BusinessProgramming languageGeodesyGeographyComputer graphics (images)Quantum and electron transport phenomenaSemiconductor materials and devicesQuantum Computing Algorithms and Architecture