Mixed physical-logical datasets for zero-noise extrapolation reduce estimator variance and physical runtime by orders of magnitude compared to pure logical or pure physical strategies when error correction suppresses noise by a factor of 0.1 or less.
Error mitigation for partially error-corrected quantum computers
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Hardware benchmarks of repetition and triangular color codes for quantum error detection show promise for scaling despite exponential sample costs and embedding overheads.
A literature review of VQAs covering ansatz design, classical optimization, barren plateaus, error mitigation strategies, and theoretical adaptations for fault-tolerant quantum computing.
citing papers explorer
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Runtime-efficient zero-noise extrapolation from mixed physical and logical data
Mixed physical-logical datasets for zero-noise extrapolation reduce estimator variance and physical runtime by orders of magnitude compared to pure logical or pure physical strategies when error correction suppresses noise by a factor of 0.1 or less.
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Opportunities and challenges in scaling quantum error detection on hardware
Hardware benchmarks of repetition and triangular color codes for quantum error detection show promise for scaling despite exponential sample costs and embedding overheads.
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A Review of Variational Quantum Algorithms: Insights into Fault-Tolerant Quantum Computing
A literature review of VQAs covering ansatz design, classical optimization, barren plateaus, error mitigation strategies, and theoretical adaptations for fault-tolerant quantum computing.