Qiskit is an open-source framework for working with noisy intermediate-scale quantum computers (NISQ) at the level of pulses, circuits, and algorithms.
Qiskit is made up of elements that each work together to enable quantum computing. This element is Aer, which provides high-performance quantum computing simulators with realistic noise models.
We encourage installing Qiskit via the PIP tool (a python package manager), which installs all Qiskit elements, including this one.
pip install qiskitPIP will handle all dependencies automatically for us and you will always install the latest (and well-tested) version.
To install from source, follow the instructions in the contribution guidelines.
Now that you have Qiskit Aer installed, you can start simulating quantum circuits with noise. Here is a basic example:
$ python
from qiskit import QuantumRegister, ClassicalRegister, QuantumCircuit, execute
from qiskit import Aer, IBMQ # import the Aer and IBMQ providers
from qiskit.providers.aer import noise # import Aer noise models
# Choose a real device to simulate
IBMQ.load_accounts()
device = IBMQ.get_backend('ibmq_16_melbourne')
properties = device.properties()
coupling_map = device.configuration().coupling_map
# Generate an Aer noise model for device
noise_model = noise.device.basic_device_noise_model(properties)
basis_gates = noise_model.basis_gates
# Generate a quantum circuit
q = QuantumRegister(2)
c = ClassicalRegister(2)
qc = QuantumCircuit(q, c)
qc.h(q[0])
qc.cx(q[0], q[1])
qc.measure(q, c)
# Perform noisy simulation
backend = Aer.get_backend('qasm_simulator')
job_sim = execute(qc, backend,
coupling_map=coupling_map,
noise_model=noise_model,
basis_gates=basis_gates)
sim_result = job_sim.result()
print(sim_result.get_counts(qc)){'11': 412, '00': 379, '10': 117, '01': 116}If you'd like to contribute to Qiskit, please take a look at our contribution guidelines. This project adheres to Qiskit's code of conduct. By participating, you are expect to uphold to this code.
We use GitHub issues for tracking requests and bugs. Please use our slack for discussion and simple questions. To join our Slack community use the link. For questions that are more suited for a forum we use the Qiskit tag in the Stack Exchange.
Now you're set up and ready to check out some of the other examples from our Qiskit Tutorials repository.
Qiskit Aer is the work of many people who contribute to the project at different levels. If you use Qiskit, please cite as per the included BibTeX file.