pennylane-oqcqcaas 0.2.2

PennyLane Plugin for OQC QCaaS

pennylane-oqc

PennyLane plugin for OQC QCaaS devices

Build and Install

poetry build

Developer Setup

poetry install

ExperimentalConfig

ExperimentalConfig is a drop-in replacement for CompilerConfig that lets you attach backend-specific (Toshiko-fermioniq simulator) settings—like enabling noise, supplying a noise model, or setting a tensor-network bond dimension—without changing the rest of your workflow. It forwards standard compiler fields (e.g., repeats, results_format, optimizations) and adds noise, bond_dimension, and noise_model. Install the extra dependencies with: pip install 'oqc-qcaas-client[experimental]'. This will install extra qcshared package which is necessary for the noise-model definition

from qcaas_client.client import OQCClient, QPUTask, ExperimentalConfig
from compiler_config.config import QuantumResultsFormat, Tket, TketOptimizations

client = OQCClient(url=OQC_URL, authentication_token=OQC_AUTH_TOKEN)
opts = Tket(); opts.tket_optimizations = TketOptimizations.Two

config = ExperimentalConfig(
    repeats=1000,
    results_format=QuantumResultsFormat().binary_count(),
    optimizations=opts,          # same as CompilerConfig
    noise=True,                  # enable noisy execution
    bond_dimension=64,           # TN simulator control (if supported)
    noise_model=None,            # or a NoiseModel/dict
)

task = QPUTask(program=openqasm_str, config=config, qpu_id=os.environ["OQC_DEVICE"])
result = client.schedule_tasks([task], qpu_id=os.environ["OQC_DEVICE"])

Test Runs

Note tests look for .env file from which to source these env variables that are required for the plugin. Suggest placing this file in the root of the test directory.

• "OQC_URL"
• "OQC_DEVICE"
• "OQC_AUTH_TOKEN"

poetry run python -m pytest