pyCTQW dev

An MPI enabled CTQW simulator

Fortran library and Python module to calculate continuous-time quantum walks

This is intended to provide a framework to quickly and easily work with quantum walkers, take advantage of high performance computing, and allow easy visualisation.

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

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

Note

The current development version pyCTQW-dev can also be installed using pip:

$ pip install --allow-unverified pyCTQW pyCTQW==dev

Documentation

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