RB Benchmarker
SkillDev toolsRandomized benchmarking skill for gate fidelity characterization
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the RB Benchmarker skill
What this skill tells your AI
The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/science/quantum-computing/skills/rb-benchmarker/SKILL.md and read by ahel’s review.
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
- Protocol Selection: Choose RB variant based on characterization goals
- Sequence Generation: Create random Clifford sequences of varying lengths
- Execution: Run benchmarking experiments with sufficient statistics
- Fitting: Analyze decay curves to extract fidelity parameters
- Reporting: Generate comprehensive benchmarking reports
Tools/Libraries
- Qiskit Experiments
- Cirq
- True-Q
- PyGSTi
- SciPy
Signals
- GitHub stars
- 2k
- Forks
- 112
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
rb-benchmarker- Source
- github.com/a5c-ai/babysitter