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Qiskit

Qiskit is an open-source software for working with quantum computers at the level of circuits, pulses, and algorithms.

News

28.10.2024 Installed qiskit/1.2.0 on LUMI with all major Qiskit packages and added support for GPU-acceleration.

Available

Currently supported Qiskit versions:

Version Module Puhti Mahti LUMI Notes
0.45.3 qiskit/0.45.3 X X
1.0.2 qiskit/1.0.2 X X
1.1.1 qiskit/1.1.1 X X
1.2.0 qiskit/1.2.0 X

Includes all the major Qiskit packages (Terra, Nature, Aer, etc.) and GPU acceleration. The qiskit/1.0.2, qiskit/1.1.1 and qiskit/1.2.0 packages include the following qiskit plugins:

qiskit-aer-gpu>=0.14.2
qiskit-algorithms==0.3.0
qiskit-dynamics==0.5.1
qiskit-experiments==0.7.0
qiskit-finance==0.4.1
qiskit-ibm-experiment==0.4.7
qiskit-machine-learning==0.7.2
qiskit-nature==0.7.2
qiskit-optimization==0.6.1

If you find that some package is missing, you can often install it yourself with pip install --user. Please see our Python usage guide for more information on how to install packages yourself. If you think that some important Qiskit-related package should be included in the module provided by CSC, please contact our servicedesk.

All modules are based on containers using Apptainer (previously known as Singularity). Wrapper scripts have been provided so that common commands such as python, python3, pip and pip3 should work as normal. For more information, see CSC's general instructions on how to run Apptainer containers.

License

Qiskit is licensed under Apache License 2.0.

Usage

To use the default version of Qiskit, initialize it with:

module load qiskit

If you wish to have a specific version (see above for available versions), use:

module load qiskit/1.1.1

The Qiskit module can also be used from Puhti, Mahti and LUMI web interfaces using Jupyter and Jupyterlab. Check out our Jupyter documentation.

Example batch script

Example batch script for reserving one GPU and two CPU cores in a single node:

#!/bin/bash
#SBATCH --account=<project>
#SBATCH --partition=gpu
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=2
#SBATCH --mem=8G
#SBATCH --time=1:00:00
#SBATCH --gres=gpu:v100:1

module load qiskit
srun python myprog.py <options>

#!/bin/bash
#SBATCH --account=<project>
#SBATCH --partition=gpusmall
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=2
#SBATCH --time=1:00:00
#SBATCH --gres=gpu:a100:1

module load qiskit
srun python myprog.py <options>

#!/bin/bash
#SBATCH --account=<project>
#SBATCH --partition=small-g
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --time=1:00:00
#SBATCH --gpus-per-node=1

module use /appl/local/quantum/modulefiles
module load qiskit/1.2.0 
python myprog.py <options>
# or 
# srun singularity exec --rocm --home $PWD /appl/local/quantum/qiskit/qiskit_1.2.0_csc.sif python3 myprog.py

Submit the script with sbatch <script_name>.sh

Small code example

Do note that this code is just to highlight the syntax.

Note

Qiskit 1.0 came with major syntax revisions. This code demonstrates syntax for 1.0.2.

import qiskit
from qiskit_aer import AerSimulator

# Generate 3-qubit GHZ state
circ = qiskit.QuantumCircuit(3)
circ.h(0)
circ.cx(0, 1)
circ.cx(1, 2)
circ.measure_all()

shots = 1000

# Construct an ideal simulator that uses GPU
simulator = AerSimulator(method="statevector", device="GPU")

# Execute the circuit with cuStateVec enabled. 
result_ideal = simulator.run(circ,shots=shots,seed_simulator=12345, cuStateVec_enable=True).result()

counts_ideal = result_ideal.get_counts(0)
print('Counts(ideal):', counts_ideal)

More information