qiskit

Qiskit - Quantum Computing Framework

Open-source quantum computing framework for building, simulating, and running quantum algorithms on quantum computers and simulators.

When to Use

• Building quantum circuits and gates
• Running quantum algorithms (VQE, QAOA, Grover, Shor)
• Quantum chemistry calculations (integration with PySCF)
• Quantum machine learning
• Quantum simulation and noise modeling
• Transpiling circuits for real quantum hardware
• Quantum optimization problems
• Quantum error correction
• Quantum cryptography
• Educational quantum computing demonstrations

Reference Documentation

Official docs: https://qiskit.org/documentation/
Search patterns: qiskit.circuit.QuantumCircuit, qiskit.algorithms.VQE, qiskit.quantum_info, qiskit_nature

Core Principles

Use Qiskit For

Task	Module	Example
Circuit building	qiskit	QuantumCircuit(2, 2)
Quantum algorithms	qiskit.algorithms	VQE(ansatz, optimizer)
Quantum simulation	qiskit.providers.aer	AerSimulator()
Quantum chemistry	qiskit_nature	GroundStateEigensolver()
Noise modeling	qiskit.providers.aer.noise	NoiseModel()
Transpilation	qiskit.transpiler	transpile(circuit, backend)
Quantum ML	qiskit_machine_learning	VQC(feature_map, ansatz)
Visualization	qiskit.visualization	plot_histogram(counts)

Do NOT Use For

• Classical machine learning (use scikit-learn, PyTorch)
• Classical optimization (use SciPy)
• General numerical computing (use NumPy)
• Classical cryptography (use cryptography package)
• Large-scale classical simulation (use classical simulators)

Quick Reference

Installation

# Core Qiskit
pip install qiskit

# With visualization tools
pip install qiskit[visualization]

# Quantum chemistry extension
pip install qiskit-nature qiskit-nature-pyscf

# Machine learning extension
pip install qiskit-machine-learning

# Optimization extension
pip install qiskit-optimization

# Full installation
pip install 'qiskit[all]' qiskit-nature qiskit-machine-learning qiskit-optimization