SpringSchool2023

Tutorial materials for the QIP Spring School 2023

• T1 - garden_DWAVE: Solution of the Garden Optimization problem on the D-Wave quantum annealer.

• T2 - tsp_DWAVE: Solution of the Traveling Salesman Problem through large cities in Europe using the D-Wave quantum annealer.

• T3 - garden_QAOA: QAOA (Qiskit) solution of the Garden Optimization problem.

• T4 - knapsack_QAOA: Combinatorial binary problem formulation of the Knapsack problem and its solution using the QAOA (Qiskit) algorithm.

Installation on JUNIQ

No installation is required on JUNIQ - all the packages are readily available in the default Python 3 kernel.

One only needs to clone the repository using the JupyterLab Git/Clone a Repository tool.

Installation without JUNIQ

Clone the repository

git clone https://jugit.fz-juelich.de/qip/springschool2023.git

D-Wave tutorials

For the D-Wave tutorials, one needs to install the D-Wave Ocean SDK as described in the documentation of the package dwave-ocean-sdk. For the TSP, it is additionally helpful to install cartopy for the visualizations to work.

QAOA tutorials

Setup a new local python environment and switch to it

With conda:

conda create -n ss23-qaoa python=3
conda activate ss23-qaoa

Or with venv:

python3 -m venv ss23-qaoa
source ss23-qaoa/bin/activate

Install packages

pip install qiskit 'qiskit-optimization[cplex]' matplotlib pandas networkx openpyxl jupyterlab ipywidgets

Add the new tutorial environment to the list of the Jupyter kernels

python -m ipykernel install --name=ss23-qaoa --user

Run JupyterLab

jupyter lab