pyCTQW dev

Features

• Fortran and Python bindings (in the form of a library and module respectively)

• Supports MPI through the use of the PETSc and SLEPc high-performance sparse matrix libraries (CUDA support planned)

• Has in-built support for infinite-line hamiltonians

• Import and export matrices/states in binary or text

• Can import custom adjancency matrices

• Supports both one and two walkers (non-interacting)

• Import and export matrices/states in binary, text or matlab format

• Python module supports plotting and visualisation using matplotlib and networkx

• Entanglement calculations

• Ability to place diagonal defects/barriers on graph vertices

• MPI graph isomorphism methods, for both 2 and 3 interacting particles

Dependencies

In addition to an MPI implementation (e.g. MPICH or Open MPI), the python pyCTQW.MPI module depends on the following components:

• Python >= 2.7

• NumPy >= 1.6.0

• PETSc >= 3.4.2

• SLEPc >= 3.4.1

• petsc4py 3.4 or petsc4py-dev

• mpi4py (recommended, used for some plotting)

• matplotlib (recommended, for node plotting and graph visualisation)

• SciPy (recommended, for some I/O operations)

• NetworkX (recommended, graph visualisation)

Installation

Once NumPy and petsc4py are installed, CTQW can be installed using pip:

$ pip install pyCTQW

Documentation

For more information on how to use this package, please see the online documentation