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
Metadata
Release files for pennylane-oqcqcaas 0.2.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pennylane_oqcqcaas-0.2.2.tar.gz | 4.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pennylane_oqcqcaas-0.2.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 11.0 kB
Release files / pennylane_oqcqcaas-0.2.2.tar.gz
| Download URL | pennylane_oqcqcaas-0.2.2.tar.gz |
|---|---|
| Size | 4.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
72fa5f68fb3864b6dda88714e489d4ba65bdfd22527db93451675def1b9e6d10
|
|
BLAKE2b-256 checksum How to use checksums |
b600a66853d8e99b650abfdd4f5cb6ee47ab0150148f3497c441efcc7cccbfcd
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Mar 5, 2026.
Transparency logRelease files / pennylane_oqcqcaas-0.2.2-py3-none-any.whl
| Download URL | pennylane_oqcqcaas-0.2.2-py3-none-any.whl |
|---|---|
| Size | 6.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
9fdf3e949280aeafa3d74bee0dcd6611636ead76d9f6970459cd02ca0f13ac07
|
|
BLAKE2b-256 checksum How to use checksums |
6ed754fe5c921108967a10e3320135792dc649e9660befb8be8482f1e04eb8ab
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Mar 5, 2026.
Transparency log