QuOp_MPI

A Parallel Framework for Quantum Variational Algorithms

QuOp_MPI is a Python 3 module designed for parallel, distributed-memory simulation of Quantum Variational Algorithms (QVAs) with arbitrary phase-shift and mixing operators.

Current Version: 1.2.1

For an in-depth discussion on design, usage, and performance, please refer to the preprint on arXiv.

Related Publications

Package Development:

1. Matwiejew, E. & Wang, J. B. QuOp_MPI: A framework for parallel simulation of quantum variational algorithms. Journal of Computational Science 62, 101711 (2022).
2. Matwiejew, E. & Wang, J. QSW_MPI: A framework for parallel simulation of quantum stochastic walks. Computer Physics Communications 107724 (2020).

Numerical Results Provided by QuOp_MPI:

1. Bennett, T., Matwiejew, E., Marsh, S. & Wang, J. B. Quantum Walk-Based Vehicle Routing Optimisation. Frontiers in Physics 9, (2021).
2. Slate, N., Matwiejew, E., Marsh, S. & Wang, J. B. Quantum walk-based portfolio optimisation. Quantum 5, 513 (2021).
3. Matwiejew, E., Pye J. & Wang J. B. Quantum Optimisation for Continuous Multivariable Functions by a Structured Search. arXiv:2210.06227 (2022).

Installation

Prerequisites

Before installing QuOp_MPI, ensure that the following system dependencies are met:

• Compiler: GCC 7+ with Fortran support (e.g., using mpifort).
• MPI: Open-MPI or MPICH.
• HDF5: Configured with --enable-fortran --enable-shared --enable-parallel.
• FFTW3: Configured with --enable-fortran --enable-shared --enable-mpi.
• Python: 3.11+

You can install these prerequisites using your Linux package manager or Homebrew on macOS. Instructions for building HDF5 and FFTW3 from source are provided later in this README.

Package Installation

First, install the following build dependencies:

python -m pip install --upgrade pip setuptools
python -m pip install scikit-build cmake ninja

Next, choose one of the following build methods:

Standard Build:

To install from source (ensure that all build prerequisites are set), run:

python -m pip install .

Note

If you encounter installation issues on a repeated build, try removing the _skbuild directory:

rm -rf _skbuild

Development Build:

For development or modifying QuOp_MPI, use the following steps:

cmake -B build -S .
cmake --build build --target install
python -m pip install -e .

Optional Dependencies

QuOp_MPI provides optional dependencies for documentation and examples.

• Install all optional dependencies at once:

  python -m pip install '.[all]'

• Manual installation: If you prefer, install dependencies manually:

  python -m pip install numpydoc==1.5.0 sphinxcontrib-bibtex==2.5.0 sphinx-rtd-theme==1.2.0
  python -m pip install pandas-datareader==0.10.0 yfinance==0.2.12 matplotlib>=3.6.0 seaborn>=0.11.2 jupyter-client>=6.1.2 jupyter-core>=4.6.3

Usage Examples

After installation, you can test the package using one of the provided examples. For instance, to run the maxcut example:

cd examples/maxcut
mpiexec -N 2 python3 maxcut.py

Documentation

The documentation is built using Sphinx. After installing the optional documentation dependencies, generate the docs with:

python setup.py build_sphinx

Building FFTW3 and HDF5 From Source

If pre-built parallel versions of FFTW3 and HDF5 are not available on your system, compile them from source as follows:

# HDF5
wget https://support.hdfgroup.org/ftp/HDF5/releases/hdf5-1.10/hdf5-1.10.6/src/hdf5-1.10.6.tar.gz
tar -xvf hdf5-1.10.6.tar.gz
cd hdf5-1.10.6
./configure --enable-fortran --enable-shared --enable-parallel --prefix=/usr/local
make && sudo make install
cd ..

# FFTW3
wget http://www.fftw.org/fftw-3.3.8.tar.gz
tar -xvf fftw-3.3.8.tar.gz
cd fftw-3.3.8
./configure --enable-mpi --enable-fortran --enable-shared --prefix=/usr/local
make && sudo make install
cd ..

Environment Setup

If QuOp_MPI is unable to locate the HDF5 or FFTW shared libraries, update your library path. Add the following line to your ~/.bashrc:

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/lib

Then, reload your environment:

source ~/.bashrc

License

QuOp_MPI is distributed under the GNU General Public License v3.0 (GPLv3). The full license text is available in the LICENSE file.

Contact Information

For bug reports or inquiries, please submit an issue on GitHub or contact:

Edric Matwiejew Email: [email protected]