# Simulators

**Simulators** are classical backends that emulate quantum circuits on a classical computer. Qiskit's main simulator is AerSimulator, which tracks the full $2^n$-dimensional state vector and applies unitary operations to it. Simulators are noiseless by default, but you can add [[qiskit-noise-models|noise models]] to study real hardware effects.

Simulators are fast for small circuits (up to ~20 qubits) and useful for development and debugging. Beyond 20 qubits, memory and time grow exponentially, making simulation impractical.

```python
from qiskit_aer import AerSimulator
from qiskit import QuantumCircuit

qc = QuantumCircuit(3, 3)
qc.h([0, 1, 2])
qc.measure([0, 1, 2], [0, 1, 2])

sim = AerSimulator()
result = sim.run(qc, shots=1000).result()
print(result.get_counts(qc))
```

## Simulator Types

- **AerSimulator (default)**: general-purpose, fast, supports statevector, density matrix, and stabilizer modes
- **StatevectorSimulator**: returns the full state vector (for circuits without measurement)
- **DensityMatrixSimulator**: tracks mixed states (useful for [[qiskit-noise-models|noisy circuits]])
- **UnitarySimulator**: returns the unitary matrix of the circuit

## Noise Simulation

Add [[qiskit-noise-models|noise models]] to study how real hardware imperfections affect your circuit:

```python
from qiskit_aer.noise import NoiseModel, depolarizing_error

noise_model = NoiseModel()
noise_model.add_all_qubit_quantum_error(
    depolarizing_error(0.1, 1), ['h', 'x']
)
result = sim.run(qc, shots=1000, noise_model=noise_model).result()
```

Noisy simulation is slower but helps you design robust algorithms before hardware.