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Minimum flow decomposition (MFD) is the NP-hard problem of finding a smallest decomposition of a network flow/circulationXon a directed graphGinto weighted source-to-sink paths whose weighted sum equalsX. We show that, for acyclic graphs, considering thewidthof the graph (the minimum number of paths needed to cover all of its edges) yields advances in our understanding of its approximability. For the version of the problem that uses only non-negative weights, we identify and characterise a new class ofwidth-stablegraphs, for which a popular heuristic is aO(logVal(X))-approximation (Val(X) being the total flow ofX), and strengthen its worst-case approximation ratio from\(\Omega (\sqrt {m})\)to Ω (m/logm) for sparse graphs, wheremis the number of edges in the graph. We also study a new problem on graphs with cycles, Minimum Cost Circulation Decomposition (MCCD), and show that it generalises MFD through a simple reduction. For the version allowing also negative weights, we give a (⌈ log ‖ X ‖ ⌉ +1)-approximation (‖X‖ being the maximum absolute value ofXon any edge) using a power-of-two approach, combined with parity fixing arguments and a decomposition of unitary circulations (‖X‖ ≤ 1), using a generalised notion of width for this problem. Finally, we disprove a conjecture about the linear independence of minimum (non-negative) flow decompositions posed by Kloster et al. [2018], but show that its useful implication (polynomial-time assignments of weights to a given set of paths to decompose a flow) holds for the negative version.more » « less
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Topological Data Analysis (TDA) studies the “shape” of data. A common topological descriptor is the persistence diagram, which encodes topological features in a topological space at different scales. Turner, Mukherjee, and Boyer showed that one can reconstruct a simplicial complex embedded in R^3 using persistence diagrams generated from all possible height filtrations (an uncountably infinite number of directions). In this paper, we present an algorithm for reconstructing plane graphs K = (V, E) in R^2, i.e., a planar graph with vertices in general position and a straight-line embedding, from a quadratic number height filtrations and their respective persistence diagrams.more » « less
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