A modular package providing multiple features and workflow tools for the quantum approximate optimisation algorithm (QAOA), facilitating its use, prototyping, and testing. Includes several different parametrisations, integration with data science and graph analysis libraries such as Pandas and NetworkX, numerous utility functions, and convenient optimiser logging and analysis tools. Documentation contains extensive and didactic examples.
Read more about EntropicaQAOA on our blog.
The documentation for EntropicaQAOA can be found here. Alternatively, it can be complied locally as follows:
Install the Prerequisites
pip install sphinx sphinx-rtd-theme sphinx-autodoc-typehints nbsphinx nbconvert
Compile the documentation
cd docs && make html
The compiled HTML version of the documentation is then found in
entropica_qaoa/docs/build/html
.
We assume that the user has already installed Rigetti's pyQuil package, as well as the Rigetti QVM and Quil Compiler. For instructions on how to do so, see Rigetti's documentation here.
You can install the EntropicaQAOA
package using pip:
pip install entropica-qaoa
To upgrade to the latest version:
pip install --upgrade entropica-qaoa
If you want to run the Demo Notebooks, you will additionally need to install scikit-learn
and scikit-optimize
, which can be done as follows:
pip install scikit-learn && pip install scikit-optimize
Alternatively, you can clone directly from GitHub:
git clone https://github.com/entropicalabs/entropica_qaoa.git
All software tests are located in entropica_qaoa/tests/
. To run them you will need to install pytest. To speed up the testing, we have tagged tests that require more computational time (~ 5 mins or so) with runslow
, and the tests of the notebooks with notebooks
. The commands are as follows:
pytest
runs the default tests, and skips both the longer tests that need heavier simulations, as well as tests of the Notebooks in theexamples
directory.pytest --runslow
runs the the tests that require longer time.pytest --notebooks
runs the Notebook tests. To achieve this, the notebooks are converted to python scripts, and then executed. Should any errors occur, this means that the line numbers given in the error messages refer to the lines in<TheNotebook>.py
, and not in<TheNotebook>.ipynb
.pytest --all
runs all of the above tests.
EntropicaQAOA provides full native support for Rigetti’s QVM and QPUs. For access to the QPUs, sign up online at https://qcs.rigetti.com/, or reach out to support@rigetti.com.
If you find any bugs or errors, have feature requests, or code you would like to contribute, feel free to open an issue or send us a pull request on GitHub .
We are always interested to hear about projects built with EntropicaQAOA. If you have an application you’d like to tell us about, drop us an email at devteam@entropicalabs.com.