qiskit
IBM quantum computing framework. Use when targeting IBM Quantum hardware, working with Qiskit Runtime for production workloads, or needing IBM optimization tools. Best for IBM hardware execution, quantum error mitigation, and enterprise quantum computing. For Google hardware use cirq; for gradient-based quantum ML use pennylane; for open quantum system simulations use qutip.
npx skills add LeonChaoX/qinyan-academic-skills --skill qiskit --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Qiskit ## Overview Qiskit is the world's most popular open-source quantum computing framework with 13M+ downloads. Build quantum circuits, optimize for hardware, execute on simulators or real quantum computers, and analyze results. Supports IBM Quantum (100+ qubit systems), IonQ, Amazon Braket, and other providers. **Key Features:** - 83x faster transpilation than competitors - 29% fewer two-qubit gates in optimized circuits - Backend-agnostic execution (local simulators or cloud hardware) - Comprehensive algorithm libraries for optimization, chemistry, and ML ## Quick Start ### Installation ```bash uv pip install qiskit uv pip install "qiskit[visualization]" matplotlib ``` ### First Circuit ```python from qiskit import QuantumCircuit from qiskit.primitives import StatevectorSampler # Create Bell state (entangled qubits) qc = QuantumCircuit(2) qc.h(0) # Hadamard on qubit 0 qc.cx(0, 1) # CNOT from qubit 0 to 1 qc.measure_all() # Measure both qubits # Run locally sampler = StatevectorSampler() result = sampler.run([qc], shots=1024).result() counts = result[0].data.meas.get_counts() print(counts) # {'00': ~512, '11': ~512} ``` ### Visualization ```python from qiskit.visualization im
- Overview
- Quick Start
- Installation
- First Circuit
- Visualization
- Core Capabilities
- 1. Setup and Installation
- 2. Building Quantum Circuits
- 3. Primitives (Sampler and Estimator)
- 4. Transpilation and Optimization
- 5. Visualization
- 6. Hardware Backends
- 7. Qiskit Patterns Workflow
- 8. Quantum Algorithms and Applications
uv pip install qiskit uv pip install "qiskit[visualization]" matplotlib
What does the qiskit skill do?
IBM quantum computing framework. Use when targeting IBM Quantum hardware, working with Qiskit Runtime for production workloads, or needing IBM optimization tools. Best for IBM hardware execution, quantum error mitigation, and enterprise quantum computing. For Google hardware use cirq; for gradient-based quantum ML use pennylane; for open quantum system simulations use qutip.
How do I install it?
Run `npx skills add LeonChaoX/qinyan-academic-skills --skill qiskit --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From LeonChaoX/qinyan-academic-skills, a repository with 759 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.