Qiskit is IBM's open-source Python framework for quantum computing. Build quantum circuits using gates, transpile them for hardware, simulate locally (up to ~20 qubits), and run on IBM quantum processors or other backends. Widely used for variational algorithms (VQE, QAOA), quantum simulation, and education.
A circuit is a sequence of quantum gates applied to qubits, followed by measurement. A simulator runs the circuit classically; a backend can be either a simulator (like AerSimulator) or a real quantum processor. Use transpilation to adapt your abstract circuit to the specific gate set and topology of your target backend.
from qiskit import QuantumCircuit from qiskit_aer import AerSimulator # Create Bell state: (|00⟩ + |11⟩) / √2 qc = QuantumCircuit(2, 2) qc.h(0) qc.cx(0, 1) qc.measure([0, 1], [0, 1]) # Simulate sim = AerSimulator() result = sim.run(qc, shots=1000).result() print(result.get_counts(qc)) # {'00': ~500, '11': ~500}
Circuits are abstract until transpiled—Qiskit adapts gates and layout to your backend's constraints. Run jobs on simulators for debugging, then deploy to hardware via IBM Quantum Platform or custom backends.