qiskit-scaleway 0.3.12

A Qiskit package to connect to Scaleway Quantum as a Service

Scaleway provider for Qiskit

Qiskit Scaleway is a Python package to run quantum circuits on Scaleway infrastructure, providing access to:

• AQT ion-trapped quantum computers
• IQM superconducting quantum computers
• Aer state vector and tensor network multi-GPU emulators
• Qsim NISQ emulators
• CUDA-Q emulators by NVIDIA
• Quantanium emulators by QPerfect

To run circuits over Quandela backends provided by Scaleway, you must use Perceval SDK through the Scaleway provider.

More info on the Quantum service web page.

Installation

We encourage installing Scaleway provider via the pip tool (a Python package manager):

pip install qiskit-scaleway

Getting started

To instantiate the ScalewayProvider, you need to have an access token and a project_id

from qiskit import QuantumCircuit
from qiskit_scaleway import ScalewayProvider

provider = ScalewayProvider(
    project_id="<your-scaleway-project-id>",
    secret_key="<your-scaleway-secret-key>",
)

Alternatively, the Scaleway Provider can discover your access token from environment variables:

export QISKIT_SCALEWAY_PROJECT_ID="project_id"
export QISKIT_SCALEWAY_SECRET_KEY="token"

Then you can instantiate the provider without any arguments:

from qiskit import QuantumCircuit
from qiskit_scaleway import ScalewayProvider

provider = ScalewayProvider()

Now you can have access to the supported backends:

# List all operational backends
backends = provider.backends(operational=True)
print(backends)

# List all backends with a minimum number of qbits
backends = provider.backends(min_num_qubits=35)
print(backends)

# Retrieve a backend by providing search criteria. The search must have a single match
backend = provider.get_backend("EMU-AER-H100") # Or any gate-based compatible QPU

Define a quantum circuit and run it

# Define a quantum circuit that produces a 4-qubit GHZ state.
qc = QuantumCircuit(4)
qc.h(0)
qc.cx(0, 1)
qc.cx(0, 2)
qc.cx(0, 3)
qc.measure_all()

## DO NOT USE TRANSPILATION
## Transpilation is done server side on QaaS service

# Create and send a job to a new QPU's session (or on an existing one)
# Custom noise models are also supported
result = backend.run(qc, method="statevector", shots=1000).result()

if result.success:
    print(result.get_counts())
else:
    print(result.to_dict()["error"])

Development

This repository is at its early stage and is still in active development. If you are looking for a way to contribute please read CONTRIBUTING.md.

Reach us

We love feedback. Feel free to reach us on Scaleway Slack community, we are waiting for you on #opensource..

License

License Apache 2.0