scaleway/pulser-scaleway

scaleway/pulser-scaleway

Description: Scaleway provider implementation for Pulser SDK

Language: Python

License: Apache-2.0

Stars: 2

Forks: 0

Open issues: 0

Created: 2025-08-05T13:15:07Z

Pushed: 2025-11-24T16:41:43Z

Default branch: main

Fork: no

Archived: no

README:

Scaleway provider for Pulser

Scaleway provider implementation to use neutral atoms based quantum computers.

Pulser Scaleway is a Python package to run quantum sequence on Scaleway infrastructure, providing access to Pasqal neutral atom quantum computers.

More info on the Quantum service web page.

Installation

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

pip install pulser-scaleway

Getting started

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

from pulser_scaleway import ScalewayProvider

qaas_connection = ScalewayProvider(
project_id=os.environ["PULSER_SCALEWAY_PROJECT_ID"],
secret_key=os.environ["PULSER_SCALEWAY_SECRET_KEY"],
)

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

export PULSER_SCALEWAY_PROJECT_ID="project_id"
export PULSER_SCALEWAY_SECRET_KEY="token"

Then you can instantiate the provider without any arguments:

from pulser_scaleway import ScalewayProvider

qaas_connection = ScalewayProvider()

Now you have access to the supported backends and can design your pulse sequence. See the technical documentation on how to write a sequence.

# Retrieve all QPU devices (emulated or real)
devices = qaas_connection.fetch_available_devices()
fresnel_device = devices["QPU-FRESNEL-100PQ-FR"]

# Create a register of trapped atoms before performing operation on them
register = Register.square(5, 5).with_automatic_layout(fresnel_device)

# Declare the sequence of pulses to perform on the register
sequence = Sequence(register, fresnel_device)
sequence.declare_channel("rydberg_global", "rydberg_global")
t = sequence.declare_variable("t", dtype=int)

amp_wf = BlackmanWaveform(t, np.pi)
det_wf = RampWaveform(t, -5, 5)
sequence.add(Pulse(amp_wf, det_wf, 0), "rydberg_global")

# Declare a backend based on the sequence and remote connection
backend = QPUBackend(sequence=sequence, connection=qaas_connection)

# Run jobs with different arguments over the same sequence and register
results = backend.run(
job_params=[
{"runs": 100, "variables": {"t": 1000}},
{"runs": 20, "variables": {"t": 2000}},
],
wait=True,
)

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](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](LICENSE)