openquantum-sdk-qiskit 0.2.4

Qiskit Python SDK for Open Quantum

openquantum-sdk-qiskit

Qiskit 2.x addon for the Open Quantum SDK.

Installation

# Plugin (and core SDK)
pip install openquantum-sdk-qiskit

# or via extras:
pip install "openquantum-sdk[qiskit]"

Authentication

The OpenQuantum Qiskit Service uses saved accounts for authentication.

Option 1: Saved Account (Recommended)

Save your credentials once using the ClientCredentials model from the core SDK. This is the recommended, secure, one-time setup.

from openquantum_sdk.auth import ClientCredentials
from openquantum_sdk.qiskit import OpenQuantumService

OpenQuantumService.save_account(
    name="default", # The name to refer to this account later
    creds=ClientCredentials(client_id="s_...", client_secret="e460c8..."),
    use_keyring=True, # Recommended for secure storage
)

# Then, load it automatically:
svc = OpenQuantumService()

Option 2: Direct in Code

You can also pass the credentials directly when instantiating the service.

from openquantum_sdk.qiskit import OpenQuantumService
from openquantum_sdk.auth import ClientCredentials

creds=ClientCredentials(client_id="s_...", client_secret="e460c8...")

svc = OpenQuantumService(creds=creds)

Quickstart: SamplerV2

# 1) Imports — just change import path from qiskit.* to openquantum.qiskit for SamplerV2 and EstimatorV2
from openquantum_sdk.qiskit import OpenQuantumService, SamplerV2, list_backends, get_backend

# Qiskit tools
from qiskit import QuantumCircuit, transpile
from qiskit.visualization import plot_histogram

# 2) Auth — load saved account
svc = OpenQuantumService()  # auto-loads saved account by default

# 3) Discover backends (client-side filters, optional)
bks = list_backends(service = svc, name="ankaa", device_type="QPU", online=True)
print(bks)

# 4) Select a backend (by id, name, or short code)
backend = get_backend("rigetti:ankaa-3")

# 5) Build a circuit, transpile against the backend if desired
qc = QuantumCircuit(2)
qc.h(0)
qc.cx(0, 1)
qc.measure_all()

tqc = transpile(
    qc,
    backend=backend,
    optimization_level=1,
)

# 6) Create a Sampler and **run**

CONFIG = {
    "backend_class_id": "rigetti:ankaa-3",  # UUID or short code
    "job_subcategory_id": "phys:hds",  # Short code for Hamiltonian Dynamics Simulation
    "name": "bell-demo",  # optional job name prefix
}

sampler = SamplerV2(
    backend=backend,
    scheduler=svc.scheduler,
    config=CONFIG,
    export_format="qasm3",
)

# Run a job (circuit, pub for params, shots)
job = sampler.run([(tqc, None, 1000)])
result = job.result()
counts = result[0].data.meas.get_counts()
print(counts)

# 7) Plot
plot_histogram(counts)

EstimatorV2 Quickstart

# Import EstimatorV2
from openquantum_sdk.qiskit import EstimatorV2
from qiskit.quantum_info import SparsePauliOp
# Create an Estimator
est = EstimatorV2(
    backend=backend,
    scheduler=svc.scheduler,
    config=CONFIG
)
layout = tqc.layout
obs = SparsePauliOp.from_list([("II", 1), ("IZ", 2), ("XI", 3)]).apply_layout(layout) # Define observations for estimator to evaluate
# Run (circuit, observables)
job = est.run([(tqc, obs)])
result = job.result()
print(f"Expectation value: {result[0].data.evs}")

API Reference

API Reference

OpenQuantumService Helpers

Method	Description
OpenQuantumService()	Main client for auth, discovery, and factory creation.
save_account(...)	Securely save credentials for auto-loading.
list_backends(...)	Discover available BackendV2 objects (with client-side filters).
get_backend(...)	Retrieve a single BackendV2 object.

Qiskit Primitives

Class	Description
SamplerV2	Qiskit 2.x Sampler compatible primitive that submits jobs to the Open Quantum platform.
EstimatorV2	Qiskit 2.x Estimator compatible primitive that submits jobs to the Open Quantum platform.