Open-Source Quantum Development
Qiskit [kiss-kit] is an open-source SDK for working with quantum computers at the level of pulses, circuits, and application modules.
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What Can Qiskit Do
Circuit Library
Qiskit includes a comprehensive set of quantum gates and a variety of pre-built circuits so users at all levels can use Qiskit for research and application development.
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Transpiler
The transpiler translates Qiskit code into an optimized circuit using a backend’s native gate set, allowing users to program for any quantum processor. Users can transpile with Qiskit's default optimization, use a custom configuration or develop their own plugin.
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Run on any hardware
Qiskit helps users schedule and run quantum programs on a variety of local simulators and cloud-based quantum processors. It supports several quantum hardware designs, such as superconducting qubits and trapped ions.
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Try it yourself
Ready to explore Qiskit’s capabilities for yourself? Learn how to run Qiskit in the cloud or your local Python environment.
Learn moreBackend compatibility
You can use Qiskit to construct quantum programs and run them on simulators or real quantum computers. With our extensive network of providers you can compile your Qiskit code for a huge range of different backends, more than any other quantum framework!
Select a provider below and explore code examples of how to use it with Qiskit:
- Qiskit (with built-in simulator) Learn more
- Aer Learn more
- Amazon Braket Learn more
- AQT Learn more
- Azure Quantum Learn more
- Gaqqie Learn more
- IBM Quantum Learn more
- IonQ Learn more
- IQM Learn more
- MQT DDSIM Learn more
- NVIDIA cuStateVec Learn more
- QC Ware Forge Learn more
- QuaC Learn more
- Quantinuum Learn more
- Rigetti Learn more
- Strangeworks Learn more
Install
pip install qiskit
Build and run
# Build circuit
from qiskit.circuit.library import QuantumVolume
circuit = QuantumVolume(5)
# Transpile circuit
from qiskit import transpile
transpiled_circuit = transpile(circuit, basis_gates=['sx', 'rz', 'cx'])
transpiled_circuit.draw()
from qiskit.primitives import Sampler
sampler = Sampler()
# Build circuit
from qiskit import QuantumCircuit
circuit = QuantumCircuit(2, 2)
circuit.h(0)
circuit.cx(0,1)
circuit.measure([0,1], [0,1])
# Run the circuit and get result distribution
job = sampler.run(circuit)
quasi_dist = job.result().quasi_dists[0]
print(quasi_dist)
from qiskit.primitives import Estimator
estimator = Estimator()
# Express hydrogen molecule Hamiltonian as an operator
from qiskit.quantum_info import SparsePauliOp
H2_operator = SparsePauliOp.from_list([
("II", -1.052373245772859), ("IZ", 0.39793742484318045), ("ZI", -0.39793742484318045), ("ZZ", -0.01128010425623538), ("XX", 0.18093119978423156)])
# Calculate ground state energy using VQE
from qiskit.circuit.library import TwoLocal
from qiskit.algorithms.optimizers import SLSQP
from qiskit.algorithms.minimum_eigensolvers import VQE
ansatz = TwoLocal(num_qubits=2, rotation_blocks="ry", entanglement_blocks="cz")
optimizer = SLSQP(maxiter=100)
vqe = VQE(estimator, ansatz, optimizer)
result = vqe.compute_minimum_eigenvalue(operator=H2_operator)
print(result.eigenvalue)
Learn with Qiskit
Gain access to a free, digital textbook to study the concepts of quantum computing using Qiskit.
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