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Computing Persistent Homology of Directed Flag Complexes
Version 1
: Received: 27 November 2019 / Approved: 29 November 2019 / Online: 29 November 2019 (03:03:36 CET)
A peer-reviewed article of this Preprint also exists.
Lütgehetmann, D.; Govc, D.; Smith, J.P.; Levi, R. Computing Persistent Homology of Directed Flag Complexes. Algorithms 2020, 13, 19. Lütgehetmann, D.; Govc, D.; Smith, J.P.; Levi, R. Computing Persistent Homology of Directed Flag Complexes. Algorithms 2020, 13, 19.
Abstract
We present a new computing package Flagser, designed to construct the directed flag complex of a finite directed graph, and compute persistent homology for flexibly defined filtrations on the graph and the resulting complex. The persistent homology computation part of Flagser is based on the program Ripser [2], but is optimised specifically for large computations. The construction of the directed flag complex is done in a way that allows easy parallelisation by arbitrarily many cores. Flagser also has the option of working with undirected graphs. For homology computations Flagser has an Approximate option, which shortens compute time with remarkable accuracy. We demonstrate the power of Flagser by applying it to the construction of the directed flag complex of digital reconstructions of brain microcircuitry by the Blue Brain Project and several other examples. In some instances we perform computation of homology. For a more complete performance analysis, we also apply Flagser to some other data collections. In all cases the hardware used in the computation, the use of memory and the compute time are recorded.
Keywords
neural networks; topology; directed graphs; directed flag complexes; persistent homology; computaional software
Subject
Computer Science and Mathematics, Computational Mathematics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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