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Rb benchmarker

Skill a5c-ai/babysitter/library/specializations/domains/science/quantum-computing/skills/rb-benchmarker

Randomized benchmarking skill for gate fidelity characterizationFrom its SKILL.md

Install
npx -y skills add a5c-ai/babysitter --skill rb-benchmarker

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

SKILL.md

1.4 KB, 184 tokens by cl100k_base, as published. Nobody here has run it

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

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

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