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title Quantum Computing - Quickstart
description Quickstart guide for Scaleway QaaS.
tags quantum qaas qiskit
dates
validation posted
2025-09-01
2021-05-26

import Requirements from '@macros/iam/requirements.mdx'

Scaleway Quantum Computing platform allows you to access and program Quantum Processing Units (QPUs).

This service has a simple ambition: to unify access to quantum computing.

No more juggling between different accounts, proprietary SDKs, or complex queues. From a single interface and with a single API key, you get access to:

  • Real QPUs: Execute your code on physical machines from our European partners (AQT, IQM, Quandela, Pasqal).
  • High-Performance emulators: Accelerate your quantum circuit prototyping using our Scaleway infrastructure, faster and bigger than your local laptop.

This guide shows you how to execute your first "Hello World" circuit (a Bell State) on any backend available via Qiskit.

  • A Scaleway account with a valid Project ID.
  • A Scaleway API Key (Secret Key).
  • Python and qiskit installed on your local machine

  1. Install the qiskit-scaleway provider. Refer to the Qiskit Scaleway GitHub repository for more information.

    pip install qiskit-scaleway

  2. Create a file with the following computation script. Replace $SCW_PROJECT_ID and $SCW_SECRET_KEY with your Scaleway Project ID and secret key. Change the BACKEND_NAME variable to switch from one technology to another

    This script is designed to be agnostic. It works equally well on a Aer emulator as it does on a trapped-ion or superconducting quantum computer. 
from qiskit import QuantumCircuit
from qiskit_scaleway import ScalewayProvider

# 1. Initialize the Provider
# Ensure you have your credentials ready
provider = ScalewayProvider(
    project_id="$SCW_PROJECT_ID",
    secret_key="$SCW_SECRET_KEY"
)

# 2. Choose your platform:
# Emulators (Low cost, fast, ideal for testing)
# backend_name = "EMU-AER-H100"    # Qiskit Aer emulator on GPU H100
# backend_name = "EMU-QSIM-H100"   # Google Qsim emulator on GPU H100
# backend_name = "EMU-CUDAQ-H100"  # NVIDIA CUDA-Q emulator on GPU H100

# Real QPUs (For science, billed per shot)
# backend_name = "QPU-IBEX-12PQ"   # AQT (Trapped-ions qubits)
backend_name = "QPU-GARNET-20PQ"  # IQM (Transmons qubits)

# 3. Retrieve the platform
# Example platform: 'EMU-AER-2L40S' (Aer emulator using a managed cluster of 2 Nvidia L40S GPU)
backend = provider.get_backend(backend_name)

# 3. Create a Quantum Circuit
# Let's create a Bell state with measurement
qc = QuantumCircuit(2)
qc.h(0)
qc.cx(0, 1)
qc.measure_all()

# 4. Execute on remote emulator
# The job is sent to Scaleway, executed on the GPU, and results are returned compressed.
job = backend.run(qc, shots=1000)

# 5. Get Results
result = job.result()

print("Results:", result)

  1. Save the script. In this example we save it as computation.py.

  2. Run the script.

    python ~/computation.py
Always validate your code on an emulator (`EMU-*`) before launching it on a real QPU (`QPU-*`). This saves you from paying for syntax or logic errors.