---
id: qiskit-aer
version: "0.17.2"
license: Apache 2.0
license_treatment: permissive
maintenance: active
---

# qiskit-aer — Aer - High performance simulators for Qiskit

License: permissive · Maintenance: active · Downloads: 853.1K/mo

## What it is and what it does

Qiskit-aer is a simulator backend that executes quantum circuits defined in Qiskit on classical hardware. It models quantum state evolution using statevector, density matrix, or unitary representations, and can inject realistic noise based on actual quantum hardware characteristics. The package depends on qiskit, numpy, scipy, psutil, and python-dateutil, and provides both low-level simulator access and high-level primitives (EstimatorV2 and SamplerV2) for variational and sampling workloads.

Developers use Aer to prototype and test quantum algorithms before running them on real quantum processors, to study the effects of noise on circuit performance, and to run parameter sweeps over large circuit families. It is the reference simulator for the Qiskit ecosystem and is widely used in quantum algorithm research and education.

Use it for:

- Prototype and debug quantum algorithms locally before submitting to real quantum hardware.
- Study how noise models from specific quantum processors affect circuit outcomes.
- Run parameter sweeps and variational optimization loops efficiently on classical hardware.
- Simulate Bell states, GHZ states, and other entanglement patterns for educational purposes.
- Benchmark quantum algorithms across different noise configurations and circuit depths.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Aer is a high-performance quantum circuit simulator for Qiskit that executes quantum algorithms with realistic noise models and supports both CPU and GPU backends.

Yes. Aer is the standard simulator for Qiskit, actively maintained, has no known vulnerabilities, and carries a permissive Apache 2.0 license. Install friction is moderate due to C++ compilation, but prebuilt wheels cover modern Python versions and common platforms. Essential if you are working with Qiskit; optional only if you have no need to simulate quantum circuits locally.

## Install

pip install qiskit-aer
uv add qiskit-aer
poetry add qiskit-aer

## Installing qiskit-aer

Before you install: Medium install friction due to compiled C++ components; prebuilt wheels available for Python 3.7–3.12 across macOS, Windows, and Linux (including ARM and ppc64le). GPU variants require CUDA 11.2+ or 12 and are x86_64 Linux only. Repository is actively maintained with recent commits.

License in practice: Apache 2.0 permissive license allows commercial and private use with minimal restrictions; you must include a copy of the license and state significant changes, but no copyleft obligations apply.

Quickstart:

pip install qiskit-aer

from qiskit_aer import AerSimulator
from qiskit import QuantumCircuit, transpile

sim = AerSimulator()
circuit = QuantumCircuit(2)
circuit.h(0)
circuit.cx(0, 1)
circuit.measure_all()

transpiled = transpile(circuit, sim)
job = sim.run(transpiled)
result = job.result()
print(result.get_counts())

GPU support requires CUDA 11.2+ (or CUDA 12 for qiskit-aer-gpu) and is only available on x86_64 Linux; CPU-only installation works on macOS, Windows, and Linux across multiple architectures.

Verify before relying:

- Performance benchmarks comparing CPU vs. GPU simulation on typical circuit sizes and depths.
- Specific noise model fidelity or accuracy claims relative to real hardware.
- Whether EstimatorV2 and SamplerV2 primitives are stable or still in development.
- Default shot count or sampling behavior when not explicitly specified.

## Package facts

- License: Apache 2.0 (permissive)
- Python support: supports_current
- Install friction: medium
- Maintenance: active
- Downloads: 853.1K/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

quantum circuit simulator, qiskit simulator backend, quantum noise simulation, quantum computing emulation, qiskit aer gpu support, quantum state vector simulation, parameterized circuit simulation, quantum-computing, simulator, gpu-accelerated

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