Prefect Qiskit

This library integrates Prefect with Qiskit Primitives, which are vendor-agnostic abstractions for quantum computation.

Given the high cost and limited processing time of quantum computation, fatal errors can disrupt the entire workflow. This library enhances software fault tolerance by implementing primitive execution within a Prefect workflow.

For more details, visit the full documentation here.

Installation

Prefect Qiskit requires Python 3.10 or later. We encourage install via pip

pip install prefect-qiskit

Pip will handle all dependencies automatically and you will always install the latest version.

Quantum Computing Workflow

The programming model and syntax are largely consistent with conventional Qiskit primitives, allowing easy integration of Prefect's powerful job management features into existing experiment codebases. The key difference is the use of the QuantumRuntime Block, which implements the Prefect API for quantum computing.

Unlike the conventional pattern that uses primitive class instances to create jobs, the runtime Block encapsulates vendor-specific job handling and provides robust error handling during execution.

For example, the following script samples the probability distribution of the Bell state using the Qiskit Aer simulator.

from prefect import flow, task
from prefect_qiskit import QuantumRuntime
from prefect_qiskit.vendors import QiskitAerCredentials
from qiskit.circuit import QuantumCircuit
from qiskit.transpiler import generate_preset_pass_manager


@task
def transpile_task(circuit, target):
    pm = generate_preset_pass_manager(
        optimization_level=2,
        target=target,
    )
    return pm.run(circuit)


@flow
def sample_bell():
    # 1. Create QuantumRuntime for Aer backend
    credentials = QiskitAerCredentials(
        num_qubits=2, 
        noise=True,
    )
    runtime = QuantumRuntime(
        resource_name="aer_simulator", 
        credentials=credentials,
    )
    # 2. Create ISA quantum circuit
    bell = QuantumCircuit(2)
    bell.h(0)
    bell.cx(0, 1)
    bell.measure_all()
    isa_circ = transpile_task(
        circuit=bell, 
        target=runtime.get_target(),
    )
    # 3. Execute workflow sampler
    result = runtime.sampler(
        [isa_circ], 
        options={"default_shots": 100},
    )
    print(result[0].data.meas.get_counts())


# Run the flow
if __name__ == "__main__":
    sample_bell()

Before running your workflow, start the Prefect server:

prefect server start --background

You can then run the workflow as a standard Python script. Once the workflow begins, you can monitor its execution status in the Prefect console. For common workflow usage, refer to the Prefect documentation.

[!TIP] The runtime Block also supports asynchronous execution. For massive parallel execution of primitives, using the await expression will efficiently utilize your computational resources.

Registering Blocks

Register Blocks to make them available for use with the Prefect console.

prefect block register -m prefect_qiskit
prefect block register -m prefect_qiskit.vendors

Contribution Guidelines

If you'd like to contribute to Prefect Qiskit, please take a look at our contribution guidelines. By participating, you are expected to uphold our code of conduct.

We use GitHub issues for tracking requests and bugs. For Prefect workflow, open issues and PRs against PrefectHQ/prefect instead of this repository. Likewise, open issues and PRs against Qiskit/qiskit for Qiskit Primitives.

License

Apache License 2.0