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Installation Instructions

Let's see how to install the Circuit Knitting Toolbox (CKT). The first thing to do is choose how you're going to run and install the packages. There are three primary ways to do this:

Users who wish to run within a containerized environment may skip the pre-installation and move straight to :ref:`Option 3`.

Pre-Installation

Users who wish to install locally (using either :ref:`Option 1` or :ref:`Option 2`) are encouraged to follow a brief set of common instructions to prepare a Python environment for installation of CKT:

First, create a minimal environment with only Python installed in it. We recommend using Python virtual environments.

python3 -m venv /path/to/virtual/environment

Activate your new environment.

source /path/to/virtual/environment/bin/activate

Note: If you are using Windows, use the following commands in PowerShell:

python3 -m venv c:\path\to\virtual\environment
c:\path\to\virtual\environment\Scripts\Activate.ps1

Option 1: Pip Installation

Upgrade pip and install the CKT package.

pip install --upgrade pip
pip install circuit-knitting-toolbox

Option 2: Install from Source

Users who wish to develop in the repository or run the tutorials locally may want to install from source.

In either case, the first step is to clone the CKT repository.

git clone git@github.com:Qiskit-Extensions/circuit-knitting-toolbox.git

Next, upgrade pip and enter the repository.

pip install --upgrade pip
cd circuit-knitting-toolbox

The next step is to install CKT to the virtual environment. If you plan on running the tutorials, install the notebook dependencies in order to run all the visualizations in the notebooks. If you plan on developing in the repository, you may want to install the dev dependencies.

Adjust the options below to suit your needs.

pip install tox notebook -e '.[notebook-dependencies,dev]'

If you installed the notebook dependencies, you can get started with CKT by running the notebooks in the docs.

cd docs/
jupyter notebook

Option 3: Use within Docker

We have provided a Dockerfile, which can be used to build a Docker image, as well as a compose.yaml file, which allows one to use the Docker image with just a few simple commands.

git clone git@github.com:Qiskit-Extensions/circuit-knitting-toolbox.git
cd circuit-knitting-toolbox
docker compose build
docker compose up

Depending on your system configuration, you may need to type sudo before each docker compose command.

Note

If you are instead using podman and podman-compose, the commands are:

podman machine start
podman-compose --podman-pull-args short-name-mode="permissive" build
podman-compose up

Once the container is running, you should see a message like this:

notebook_1  |     To access the server, open this file in a browser:
notebook_1  |         file:///home/jovyan/.local/share/jupyter/runtime/jpserver-7-open.html
notebook_1  |     Or copy and paste one of these URLs:
notebook_1  |         http://e4a04564eb39:8888/lab?token=00ed70b5342f79f0a970ee9821c271eeffaf760a7dcd36ec
notebook_1  |      or http://127.0.0.1:8888/lab?token=00ed70b5342f79f0a970ee9821c271eeffaf760a7dcd36ec

Locate the last URL in your terminal (the one that includes 127.0.0.1), and navigate to that URL in a web browser to access the Jupyter Notebook interface.

The home directory includes a subdirectory named persistent-volume. All work you’d like to save should be placed in this directory, as it is the only one that will be saved across different container runs.

Platform Support

We expect this package to work on any platform supported by Qiskit. If you are experiencing issues running the software on your device, you may consider :ref:`using the toolbox within Docker <Option 3>`.