QSW_MPI: A framework for parallel simulation of quantum stochastic walks

Edric Matwiejew, Jingbo Wang

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

QSW_MPI is a Python package developed for time-series simulation of continuous-time quantum stochastic walks. This model allows for the study of Markovian open quantum systems in the Lindblad formalism, including a generalisation of the continuous-time random walk and continuous-time quantum walk. Consisting of a Python interface accessing parallelised Fortran libraries utilising sparse data structures, QSW_MPI is scalable to massively parallel computers, which makes possible the simulation of a wide range of walk dynamics on directed and undirected graphs of arbitrary complexity. Program summary: Program Title: QSW_MPI CPC Library link to program files: http://dx.doi.org/10.17632/r8jsx4xxgv.1 Licensing provisions: GPLv3 Programming language: Python 3 + Fortran 2003 External routines/libraries: NumPy [1], SciPy [2], MPI for Python [3], h5py[4] Nature of problem: QSW_MPI provides a framework for the simulation of quantum stochastic walks on arbitrary graphs (directed/undirected, weighted/unweighted). Solution method: A parallel distributed-memory implementation of the matrix exponential via a truncated Taylor series expansion with scaling and squaring [5]. Additional comments including restrictions and unusual features: QSW_MPI will provide support for the simulation of multiple quantum walkers in a future version. References: [1] T. Oliphant, NumPy: A guide to NumPy, 2006, published: USA: Trelgol Publishing. [2] E. Jones, T. Oliphant, P. Peterson, SciPy: Open source scientific tools for Python (2001). [3] L. Dalcìn, R. Paz, M. Storti, J. D'Elia, MPI for Python: Performance improvements and MPI-2 extensions, Journal of Parallel and Distributed Computing 68 (5) (2008) 655–662. doi:10.1016/j.jpdc.2007.09. 005. [4] A. Collette, Python and HDF5, O'Reilly, 2013. [5] A. Al-Mohy, N. Higham, Computing the Action of the Matrix Exponential, with an Application to Exponential Integrators, SIAM Journal on Scientific Computing 33 (2) (2011) 488–511. doi:10.1137/100788860.

Original languageEnglish
Article number107724
JournalComputer Physics Communications
Volume260
DOIs
Publication statusPublished - Mar 2021

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