Quickstart: Submit a circuit with Qiskit to Azure Quantum
Learn how to use the azure-quantum Python package to submit Qiskit quantum circuits to an IonQ or Honeywell quantum computing target via the Azure Quantum service. For more information, see Quantum circuits.
Prerequisites
An Azure account with an active subscription. Create an account for free.
Create an Azure Quantum workspace and enable your preferred provider, Honeywell or IonQ (or both), for this scenario. For more information, see Create an Azure Quantum workspace.
Install the latest
azure-quantumPython package.Tip
If you are using Miniconda or Anaconda, you can optionally create a new environment by downloading environment.yml and running the following:
conda env create -f environment.ymlThis creates a new conda environment that you can activate with the following:
conda activate azurequantumStart your favorite code editor or interactive Python tool, such as VS Code, Jupyter or iPython.
Load the required imports
First, run the following cell to load the required imports:
from qiskit import QuantumCircuit
from qiskit.visualization import plot_histogram
from qiskit.tools.monitor import job_monitor
from azure.quantum.qiskit import AzureQuantumProvider
Connect to the Azure Quantum service
To connect to the Azure Quantum service, your program will need the resource ID and the location of your Azure Quantum workspace. Log in to your Azure account, https://portal.azure.com, navigate to your Azure Quantum workspace, and copy the values from the header.
Paste the values into the following AzureQuantumProvider constructor to
create a provider object that connects to your Azure Quantum workspace.
provider = AzureQuantumProvider(
resource_id="",
location=""
)
List all backends
You can now print all of the quantum computing backends that are available on your workspace:
print([backend.name() for backend in provider.backends()])
['ionq.qpu', 'ionq.simulator', 'honeywell.hqs-lt-s1', 'honeywell.hqs-lt-s1-apival', 'honeywell.hqs-lt-s2', 'honeywell.hqs-lt-s2-apival', 'honeywell.hqs-lt-s1-sim']
Run a simple circuit
First, create a simple Qiskit circuit to run.
# Create a Quantum Circuit acting on the q register
circuit = QuantumCircuit(3, 3)
circuit.name = "Qiskit Sample - 3-qubit GHZ circuit"
circuit.h(0)
circuit.cx(0, 1)
circuit.cx(1, 2)
circuit.measure([0,1,2], [0, 1, 2])
# Print out the circuit
circuit.draw()
┌───┐ ┌─┐
q_0: ┤ H ├──■───────┤M├──────
└───┘┌─┴─┐ └╥┘┌─┐
q_1: ─────┤ X ├──■───╫─┤M├───
└───┘┌─┴─┐ ║ └╥┘┌─┐
q_2: ──────────┤ X ├─╫──╫─┤M├
└───┘ ║ ║ └╥┘
c: 3/════════════════╩══╩══╩═
0 1 2
To get a result back quickly, use provider.get_backend to create a
Backend object to connect to the IonQ Simulator backend:
simulator_backend = provider.get_backend("ionq.simulator")
You can now run the program via the Azure Quantum service and get the result. The following cell submits a job that runs the circuit with 100 shots:
job = simulator_backend.run(circuit, shots=100)
job_id = job.id()
print("Job id", job_id)
Job id 00000000-0000-0000-0000-000000000000
To monitor job progress, you can use the Qiskit job_monitor imported
earlier to keep track of the Job's status. Note that this call will
block until the job completes:
job_monitor(job)
Job Status: job has successfully run
To wait until the job is complete and return the results, run:
result = job.result()
This returns a qiskit.Result object.
type(result)
qiskit.result.result.Result
print(result)
Result(backend_name='ionq.simulator', backend_version='1', qobj_id='Qiskit Sample - 3-qubit GHZ circuit', job_id='00000000-0000-0000-0000-000000000000', success=True, results=[ExperimentResult(shots=100, success=True, meas_level=2, data=ExperimentResultData(counts={'000': 50, '111': 50}, probabilities={'000': 0.5, '111': 0.5}), header=QobjExperimentHeader(meas_map='[0, 1, 2]', name='Qiskit Sample - 3-qubit GHZ circuit', num_qubits='3', qiskit='True'))])
Because this is an object native to the Qiskit package, you can use
Qiskit's result.get_counts and plot_histogram to visualize the
results. To make sure that all possible bitstring labels are represented,
add them to counts.
counts = {format(n, "03b"): 0 for n in range(8)}
counts.update(result.get_counts(circuit))
print(counts)
plot_histogram(counts)
{'000': 50, '001': 0, '010': 0, '011': 0, '100': 0, '101': 0, '110': 0, '111': 50}
Run on IonQ QPU
To connect to real hardware (a Quantum Processor Unit (QPU)), simply
provide the name of the target "ionq.qpu" to the provider.get_backend method:
qpu_backend = provider.get_backend("ionq.qpu")
Submit the circuit to run on Azure Quantum.
Note
The time required to run a circuit on the QPU may vary depending on current queue times.
As before, use job_monitor to keep track of the job
status, and plot_histogram to plot the results.
# Submit the circuit to run on Azure Quantum
qpu_job = qpu_backend.run(circuit, shots=1024)
job_id = qpu_job.id()
print("Job id", job_id)
# Monitor job progress and wait until complete:
job_monitor(qpu_job)
# Get the job results (this method also waits for the Job to complete):
result = qpu_job.result()
print(result)
counts = {format(n, "03b"): 0 for n in range(8)}
counts.update(result.get_counts(circuit))
print(counts)
plot_histogram(counts)
Job id 00000000-0000-0000-0000-000000000000
Job Status: job has successfully run
Result(backend_name='ionq.simulator', backend_version='1', qobj_id='Qiskit Sample - 3-qubit GHZ circuit', job_id='00000000-0000-0000-0000-000000000000', success=True, results=[ExperimentResult(shots=1024, success=True, meas_level=2, data=ExperimentResultData(counts={'0': 505, '1': 6, '2': 1, '3': 1, '4': 1, '5': 10, '6': 11, '7': 488}, probabilities={'0': 0.4932, '1': 0.0059, '2': 0.001, '3': 0.001, '4': 0.001, '5': 0.0098, '6': 0.0117, '7': 0.4766}), header=QobjExperimentHeader(name='Qiskit Sample - 3-qubit GHZ circuit', num_qubits='3', qiskit='True'))])
{'000': 505, '001': 6, '010': 1, '011': 1, '100': 1, '101': 10, '110': 11, '111': 488}
Load the required imports
First, run the following cell to load the required imports:
from qiskit import QuantumCircuit
from qiskit.visualization import plot_histogram
from qiskit.tools.monitor import job_monitor
from azure.quantum.qiskit import AzureQuantumProvider
Connect to the Azure Quantum service
To connect to the Azure Quantum service, your program will need the resource ID and the location of your Azure Quantum workspace. Log in to your Azure account, https://portal.azure.com, navigate to your Azure Quantum workspace, and copy the values from the header.
Paste the values into the following AzureQuantumProvider constructor to
create a provider object that connects to your Azure Quantum workspace.
provider = AzureQuantumProvider(
resource_id="",
location=""
)
List all backends
You can now print all of the quantum computing backends that are available on your workspace:
print([backend.name() for backend in provider.backends()])
['ionq.simulator', 'ionq.qpu', 'honeywell.hqs-lt-s1', 'honeywell.hqs-lt-s1-apival', 'honeywell.hqs-lt-s1-sim']
Run on the API validator
Note
The Honeywell API validator backend will always return 0 on measurement.
# Get Honeywell's API validator backend:
apival_backend = provider.get_backend("honeywell.hqs-lt-s1-apival")
# Create a Quantum Circuit acting on the q register
circuit = QuantumCircuit(3, 3)
circuit.name = "Qiskit Sample - 3-qubit GHZ circuit"
circuit.h(0)
circuit.cx(0, 1)
circuit.cx(1, 2)
circuit.measure([0,1,2], [0, 1, 2])
# Print out the circuit
circuit.draw()
┌───┐ ┌─┐
q_0: ┤ H ├──■───────┤M├──────
└───┘┌─┴─┐ └╥┘┌─┐
q_1: ─────┤ X ├──■───╫─┤M├───
└───┘┌─┴─┐ ║ └╥┘┌─┐
q_2: ──────────┤ X ├─╫──╫─┤M├
└───┘ ║ ║ └╥┘
c: 3/════════════════╩══╩══╩═
0 1 2
# Submit the circuit to run on Azure Quantum
job = apival_backend.run(circuit, count=1024)
job_id = job.id()
print("Job id", job_id)
# Monitor job progress and wait until complete:
job_monitor(job)
# Get the job results (this method also waits for the Job to complete):
result = job.result()
print(result)
counts = {format(n, "03b"): 0 for n in range(8)}
counts.update(result.get_counts(circuit))
print(counts)
plot_histogram(counts)
Job id 00000000-0000-0000-0000-000000000000
Job Status: job has successfully run
Result(backend_name='honeywell.hqs-lt-s1-apival', backend_version='1', qobj_id='Qiskit Sample - 3-qubit GHZ circuit', job_id='00000000-0000-0000-0000-000000000000', success=True, results=[ExperimentResult(shots=1024, success=True, meas_level=2, data=ExperimentResultData(counts={'000': 1024}, probabilities={'000': 1.0}), header=QobjExperimentHeader(name='Qiskit Sample - 3-qubit GHZ circuit'))])
{'000': 1024, '001': 0, '010': 0, '011': 0, '100': 0, '101': 0, '110': 0, '111': 0}
Run on a Honeywell QPU
After running successfully on the API validator, you can run your job on one of Honeywell's hardware processors (a Quantum Processor Unit (QPU)).
Note
The time required to run a circuit on the QPU may vary depending on current queue times.
# Get Honeywell's QPU backend:
qpu_backend = provider.get_backend("honeywell.hqs-lt-s1")
# Submit the circuit to run on Azure Quantum
job = qpu_backend.run(circuit, count=500)
job_id = job.id()
print("Job id", job_id)
# Monitor job progress and wait until complete:
job_monitor(job)
Job id 00000000-0000-0000-0000-000000000000
Job Status: job has successfully run
# Get the job results (this method also waits for the Job to complete):
result = job.result()
print(result)
counts = {format(n, "03b"): 0 for n in range(8)}
counts.update(result.get_counts(circuit))
print(counts)
plot_histogram(counts)
Result(backend_name='honeywell.hqs-lt-s1-apival', backend_version='1', qobj_id='Qiskit Sample - 3-qubit GHZ circuit', job_id='00000000-0000-0000-0000-000000000000', success=True, results=[ExperimentResult(shots=1024, success=True, meas_level=2, data=ExperimentResultData(counts={'011': 16, '010': 5, '001': 1, '000': 500, '111': 471, '101': 6, '100': 17, '110': 8}, probabilities={'011': 0.015625, '010': 0.0048828125, '001': 0.0009765625, '000': 0.48828125, '111': 0.4599609375, '101': 0.005859375, '100': 0.0166015625, '110': 0.0078125}), header=QobjExperimentHeader(name='Qiskit Sample - 3-qubit GHZ circuit'))])
{'000': 500, '001': 1, '010': 5, '011': 16, '100': 17, '101': 6, '110': 8, '111': 471}
