86 research outputs found
Degree-3 Treewidth Sparsifiers
We study treewidth sparsifiers. Informally, given a graph of treewidth
, a treewidth sparsifier is a minor of , whose treewidth is close to
, is small, and the maximum vertex degree in is bounded.
Treewidth sparsifiers of degree are of particular interest, as routing on
node-disjoint paths, and computing minors seems easier in sub-cubic graphs than
in general graphs.
In this paper we describe an algorithm that, given a graph of treewidth
, computes a topological minor of such that (i) the treewidth of
is ; (ii) ; and (iii) the maximum
vertex degree in is . The running time of the algorithm is polynomial in
and . Our result is in contrast to the known fact that unless , treewidth does not admit polynomial-size kernels.
One of our key technical tools, which is of independent interest, is a
construction of a small minor that preserves node-disjoint routability between
two pairs of vertex subsets. This is closely related to the open question of
computing small good-quality vertex-cut sparsifiers that are also minors of the
original graph.Comment: Extended abstract to appear in Proceedings of ACM-SIAM SODA 201
An Algorithm for the Graph Crossing Number Problem
We study the Minimum Crossing Number problem: given an -vertex graph ,
the goal is to find a drawing of in the plane with minimum number of edge
crossings. This is one of the central problems in topological graph theory,
that has been studied extensively over the past three decades. The first
non-trivial efficient algorithm for the problem, due to Leighton and Rao,
achieved an -approximation for bounded degree graphs. This
algorithm has since been improved by poly-logarithmic factors, with the best
current approximation ratio standing on O(n \poly(d) \log^{3/2}n) for graphs
with maximum degree . In contrast, only APX-hardness is known on the
negative side.
In this paper we present an efficient randomized algorithm to find a drawing
of any -vertex graph in the plane with O(OPT^{10}\cdot \poly(d \log
n)) crossings, where is the number of crossings in the optimal solution,
and is the maximum vertex degree in . This result implies an
\tilde{O}(n^{9/10} \poly(d))-approximation for Minimum Crossing Number, thus
breaking the long-standing -approximation barrier for
bounded-degree graphs
Improved Bounds for the Flat Wall Theorem
The Flat Wall Theorem of Robertson and Seymour states that there is some
function , such that for all integers , every graph containing a
wall of size , must contain either (i) a -minor; or (ii) a small
subset of vertices, and a flat wall of size in . Kawarabayashi, Thomas and Wollan recently showed a self-contained proof of
this theorem with the following two sets of parameters: (1)
with , and (2)
with . The latter result gives the
best possible bound on . In this paper we improve their bounds to
with . For the special case where the
maximum vertex degree in is bounded by , we show that, if contains a
wall of size , then either contains a -minor, or
there is a flat wall of size in . This setting naturally arises in
algorithms for the Edge-Disjoint Paths problem, with . Like the proof
of Kawarabayashi et al., our proof is self-contained, except for using a
well-known theorem on routing pairs of disjoint paths. We also provide
efficient algorithms that return either a model of the -minor, or a vertex
set and a flat wall of size in .
We complement our result for the low-degree scenario by proving an almost
matching lower bound: namely, for all integers , there is a graph ,
containing a wall of size , such that the maximum vertex degree in
is 5, and contains no flat wall of size , and no -minor
On Graph Crossing Number and Edge Planarization
Given an n-vertex graph G, a drawing of G in the plane is a mapping of its
vertices into points of the plane, and its edges into continuous curves,
connecting the images of their endpoints. A crossing in such a drawing is a
point where two such curves intersect. In the Minimum Crossing Number problem,
the goal is to find a drawing of G with minimum number of crossings. The value
of the optimal solution, denoted by OPT, is called the graph's crossing number.
This is a very basic problem in topological graph theory, that has received a
significant amount of attention, but is still poorly understood
algorithmically. The best currently known efficient algorithm produces drawings
with crossings on bounded-degree graphs, while only a
constant factor hardness of approximation is known. A closely related problem
is Minimum Edge Planarization, in which the goal is to remove a
minimum-cardinality subset of edges from G, such that the remaining graph is
planar. Our main technical result establishes the following connection between
the two problems: if we are given a solution of cost k to the Minimum Edge
Planarization problem on graph G, then we can efficiently find a drawing of G
with at most \poly(d)\cdot k\cdot (k+OPT) crossings, where is the maximum
degree in G. This result implies an O(n\cdot \poly(d)\cdot
\log^{3/2}n)-approximation for Minimum Crossing Number, as well as improved
algorithms for special cases of the problem, such as, for example, k-apex and
bounded-genus graphs
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