Efficient Sampling of Noisy Shallow Circuits Via Monitored Unraveling
Zihan Cheng, Matteo Ippoliti
Abstract
Building on the insight of unraveling noise channels into optimized measurements, a classical algorithm for sampling noisy random circuits is developed, increasing our understanding of the boundary of ``practically hard'' quantum computation in real-world noisy settings.
Topics & Concepts
Sampling (signal processing)ComputationElectronic circuitNoise (video)Computer scienceAlgorithmImportance samplingBoundary (topology)Theoretical computer scienceComputer engineeringElectronic engineeringMathematicsArtificial intelligenceMonte Carlo methodStatisticsTelecommunicationsEngineeringElectrical engineeringMathematical analysisImage (mathematics)DetectorQuantum Computing Algorithms and ArchitectureQuantum Information and CryptographyQuantum many-body systems