178,340 research outputs found
Minimum Cycle Basis and All-Pairs Min Cut of a Planar Graph in Subquadratic Time
A minimum cycle basis of a weighted undirected graph is a basis of the
cycle space of such that the total weight of the cycles in this basis is
minimized. If is a planar graph with non-negative edge weights, such a
basis can be found in time and space, where is the size of . We
show that this is optimal if an explicit representation of the basis is
required. We then present an time and space
algorithm that computes a minimum cycle basis \emph{implicitly}. From this
result, we obtain an output-sensitive algorithm that explicitly computes a
minimum cycle basis in time and space,
where is the total size (number of edges and vertices) of the cycles in the
basis. These bounds reduce to and ,
respectively, when is unweighted. We get similar results for the all-pairs
min cut problem since it is dual equivalent to the minimum cycle basis problem
for planar graphs. We also obtain time and
space algorithms for finding, respectively, the weight vector and a Gomory-Hu
tree of . The previous best time and space bound for these two problems was
quadratic. From our Gomory-Hu tree algorithm, we obtain the following result:
with time and space for preprocessing, the
weight of a min cut between any two given vertices of can be reported in
constant time. Previously, such an oracle required quadratic time and space for
preprocessing. The oracle can also be extended to report the actual cut in time
proportional to its size
Algorithmic Applications of Baur-Strassen's Theorem: Shortest Cycles, Diameter and Matchings
Consider a directed or an undirected graph with integral edge weights from
the set [-W, W], that does not contain negative weight cycles. In this paper,
we introduce a general framework for solving problems on such graphs using
matrix multiplication. The framework is based on the usage of Baur-Strassen's
theorem and of Strojohann's determinant algorithm. It allows us to give new and
simple solutions to the following problems:
* Finding Shortest Cycles -- We give a simple \tilde{O}(Wn^{\omega}) time
algorithm for finding shortest cycles in undirected and directed graphs. For
directed graphs (and undirected graphs with non-negative weights) this matches
the time bounds obtained in 2011 by Roditty and Vassilevska-Williams. On the
other hand, no algorithm working in \tilde{O}(Wn^{\omega}) time was previously
known for undirected graphs with negative weights. Furthermore our algorithm
for a given directed or undirected graph detects whether it contains a negative
weight cycle within the same running time.
* Computing Diameter and Radius -- We give a simple \tilde{O}(Wn^{\omega})
time algorithm for computing a diameter and radius of an undirected or directed
graphs. To the best of our knowledge no algorithm with this running time was
known for undirected graphs with negative weights.
* Finding Minimum Weight Perfect Matchings -- We present an
\tilde{O}(Wn^{\omega}) time algorithm for finding minimum weight perfect
matchings in undirected graphs. This resolves an open problem posted by
Sankowski in 2006, who presented such an algorithm but only in the case of
bipartite graphs.
In order to solve minimum weight perfect matching problem we develop a novel
combinatorial interpretation of the dual solution which sheds new light on this
problem. Such a combinatorial interpretation was not know previously, and is of
independent interest.Comment: To appear in FOCS 201
Shortest Odd Paths in Undirected Graphs with Conservative Weight Functions
We consider the Shortest Odd Path problem, where given an undirected graph
, a weight function on its edges, and two vertices and in , the
aim is to find an -path with odd length and, among all such paths, of
minimum weight. For the case when the weight function is conservative, i.e.,
when every cycle has non-negative total weight, the complexity of the Shortest
Odd Path problem had been open for 20 years, and was recently shown to be
NP-hard. We give a polynomial-time algorithm for the special case when the
weight function is conservative and the set of negative-weight edges
forms a single tree. Our algorithm exploits the strong connection between
Shortest Odd Path and the problem of finding two internally vertex-disjoint
paths between two terminals in an undirected edge-weighted graph. It also
relies on solving an intermediary problem variant called Shortest
Parity-Constrained Odd Path where for certain edges we have parity constraints
on their position along the path. Also, we exhibit two FPT algorithms for
solving Shortest Odd Path in graphs with conservative weight functions. The
first FPT algorithm is parameterized by , the number of negative edges,
or more generally, by the maximum size of a matching in the subgraph of
spanned by . Our second FPT algorithm is parameterized by the treewidth of
- …