hafnian 0.5.0

Open source library for hafnian calculation

The fastest exact hafnian library for real and complex matrices. For more information, please see the documentation.

Features

• The fastest calculation of the hafnian, loop hafnian, permanent, and torontonian, of general and certain structured matrices.

• An easy to use interface to use the loop hafnian to calculate Fock matrix elements of Gaussian states via the included quantum module.

Installation

Pre-built binary wheels are available for the following platforms:

	macOS 10.6+	manylinux x86_64	Windows 64bit
Python 3.5	✅	✅	✅
Python 3.6	✅	✅	✅
Python 3.7	✅	✅	✅

These can be installed using pip:

pip install hafnian

Compiling from source

Hafnian depends on the following Python packages:

• Python >=3.5

• NumPy >=1.13.3

In addition, to compile the included Fortran and C++ extensions, the following dependencies are required:

• A Fortran compiler, such as gfortran

• The LINPACK_Q quadruple precision linear algebra library

• A C++11 compiler, such as g++ >= 4.8.1, clang >= 3.3, MSVC >= 14.0/2015

• Eigen3 - a C++ header library for linear algebra.

On Debian-based systems, these can be installed via apt and curl:

$ sudo apt install g++ gfortran libeigen3-dev
$ curl -sL -o src/linpack_q_complex.f90 https://raw.githubusercontent.com/josh146/linpack_q_complex/master/linpack_q_complex.f90

or using Homebrew on MacOS:

$ brew install gcc eigen
$ curl -sL -o src/linpack_q_complex.f90 https://raw.githubusercontent.com/josh146/linpack_q_complex/master/linpack_q_complex.f90

Alternatively, you can download the Eigen headers manually:

$ mkdir ~/.local/eigen3 && cd ~/.local/eigen3
$ wget http://bitbucket.org/eigen/eigen/get/3.3.7.tar.gz -O eigen3.tar.gz
$ tar xzf eigen3.tar.gz eigen-eigen-323c052e1731/Eigen --strip-components 1
$ export EIGEN_INCLUDE_DIR=$HOME/.local/eigen3

Note that we export the environment variable EIGEN_INCLUDE_DIR so that Hafnian can find the Eigen3 header files (if not provided, Hafnian will by default look in /use/include/eigen3 and /usr/local/include/eigen3).

Once all dependencies are installed, you can compile the latest stable version of the Hafnian library as follows:

$ python -m pip install hafnian --no-binary :all:

Alternatively, you can compile the latest development version by cloning the git repository, and installing using pip in development mode.

$ git clone https://github.com/XanaduAI/hafnian.git
$ cd hafnian && python -m pip install -e .

OpenMP

The Hafnian library uses OpenMP to parallelize both the permanent and the hafnian calculation. At the moment, this is only supported on Linux using the GNU g++ compiler, due to insufficient support using Windows/MSCV and MacOS/Clang.

Using LAPACK, OpenBLAS, or MKL

If you would like to take advantage of the highly optimized matrix routines of LAPACK, OpenBLAS, or MKL, you can optionally compile the Hafnian library such that Eigen uses these frameworks as backends. As a result, all calls in the Hafnian library to Eigen functions are silently substituted with calls to LAPACK/OpenBLAS/MKL.

For example, for LAPACK integration, make sure you have the lapacke C++ LAPACK bindings installed (sudo apt install liblapacke-dev in Ubuntu-based Linux distributions), and then compile with the environment variable USE_LAPACK=1:

$ USE_LAPACK=1 python -m pip install hafnian --no-binary :all:

Alternatively, you may pass USE_OPENBLAS=1 to use the OpenBLAS library.

Software tests

To ensure that the Hafnian library is working correctly after installation, the test suite can be run by navigating to the source code folder and running

$ make test

Documentation

The Hafnian+ documentation is currently not hosted online. To build it locally, you need to have the following packages installed:

• Sphinx >=1.5

• sphinxcontrib-bibtex >=0.3.6

• nbsphinx

• Pandoc

They can be installed via a combination of pip and apt if on a Debian-based system:

$ sudo apt install pandoc
$ pip3 install sphinx sphinxcontrib-bibtex nbsphinx --user

To build the HTML documentation, go to the top-level directory and run the command

$ make doc

The documentation can then be found in the docs/_build/html/ directory.

Authors

Nicolás Quesada, Brajesh Gupt, and Josh Izaac.

If you are doing research using Hafnian, please cite our paper:

Andreas Björklund, Brajesh Gupt, and Nicolás Quesada. A faster hafnian formula for complex matrices and its benchmarking on the Titan supercomputer arXiv, 2018. arxiv:1805.12498

Support

• Source Code: https://github.com/XanaduAI/hafnian

• Issue Tracker: https://github.com/XanaduAI/hafnian/issues

If you are having issues, please let us know by posting the issue on our Github issue tracker.

License

Hafnian is free and open source, released under the Apache License, Version 2.0.