qiskit

# Qiskit ## When to Use - You are building or optimizing quantum circuits with Qiskit for simulators or real hardware. - You need IBM Quantum-style tooling for transpilation, execution, visualization, or algorithm libraries. - You want guidance on moving from a simple circuit prototype to backend-aware execution. ## 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 ...