Mimicking Networks and Succinct Representations of Terminal Cuts
Robert Krauthgamer, Inbal Rika

TL;DR
This paper advances the understanding of mimicking networks by establishing tighter bounds on their size for planar and general graphs, enabling more efficient storage and computation of terminal cut values.
Contribution
It provides new upper and lower bounds on the size of mimicking networks for planar and general graphs, improving previous exponential bounds to nearly tight bounds.
Findings
Planar networks have mimicking networks of size O(k^2 2^{2k})
Some planar networks require mimicking networks of size at least Ω(k^2)
General bipartite graphs need mimicking networks of size at least 2^{Ω(k)}
Abstract
Given a large edge-weighted network with terminal vertices, we wish to compress it and store, using little memory, the value of the minimum cut (or equivalently, maximum flow) between every bipartition of terminals. One appealing methodology to implement a compression of is to construct a \emph{mimicking network}: a small network with the same terminals, in which the minimum cut value between every bipartition of terminals is the same as in . This notion was introduced by Hagerup, Katajainen, Nishimura, and Ragde [JCSS '98], who proved that such of size at most always exists. Obviously, by having access to the smaller network , certain computations involving cuts can be carried out much more efficiently. We provide several new bounds, which together narrow the previously known gap from doubly-exponential to only singly-exponential, both for…
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Taxonomy
TopicsAlgorithms and Data Compression · semigroups and automata theory · Cellular Automata and Applications
