rb-benchmarker

Solid

Randomized benchmarking skill for gate fidelity characterization

AI & Automation 814 stars 53 forks Updated today MIT

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Quality Score: 93/100

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Skill Content

# RB Benchmarker ## Purpose Provides expert guidance on randomized benchmarking protocols for characterizing quantum gate fidelities and hardware performance. ## Capabilities - Standard randomized benchmarking - Interleaved randomized benchmarking - Simultaneous RB for crosstalk - Character benchmarking - Cycle benchmarking - Fidelity decay fitting - SPAM error separation - Confidence interval estimation ## Usage Guidelines 1. **Protocol Selection**: Choose RB variant based on characterization goals 2. **Sequence Generation**: Create random Clifford sequences of varying lengths 3. **Execution**: Run benchmarking experiments with sufficient statistics 4. **Fitting**: Analyze decay curves to extract fidelity parameters 5. **Reporting**: Generate comprehensive benchmarking reports ## Tools/Libraries - Qiskit Experiments - Cirq - True-Q - PyGSTi - SciPy

Details

Author
a5c-ai
Repository
a5c-ai/babysitter
Created
4 months ago
Last Updated
today
Language
JavaScript
License
MIT

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