11,801 research outputs found
Split decomposition and graph-labelled trees: characterizations and fully-dynamic algorithms for totally decomposable graphs
In this paper, we revisit the split decomposition of graphs and give new
combinatorial and algorithmic results for the class of totally decomposable
graphs, also known as the distance hereditary graphs, and for two non-trivial
subclasses, namely the cographs and the 3-leaf power graphs. Precisely, we give
strutural and incremental characterizations, leading to optimal fully-dynamic
recognition algorithms for vertex and edge modifications, for each of these
classes. These results rely on a new framework to represent the split
decomposition, namely the graph-labelled trees, which also captures the modular
decomposition of graphs and thereby unify these two decompositions techniques.
The point of the paper is to use bijections between these graph classes and
trees whose nodes are labelled by cliques and stars. Doing so, we are also able
to derive an intersection model for distance hereditary graphs, which answers
an open problem.Comment: extended abstract appeared in ISAAC 2007: Dynamic distance hereditary
graphs using split decompositon. In International Symposium on Algorithms and
Computation - ISAAC. Number 4835 in Lecture Notes, pages 41-51, 200
Limits of Ordered Graphs and their Applications
The emerging theory of graph limits exhibits an analytic perspective on
graphs, showing that many important concepts and tools in graph theory and its
applications can be described more naturally (and sometimes proved more easily)
in analytic language. We extend the theory of graph limits to the ordered
setting, presenting a limit object for dense vertex-ordered graphs, which we
call an \emph{orderon}. As a special case, this yields limit objects for
matrices whose rows and columns are ordered, and for dynamic graphs that expand
(via vertex insertions) over time. Along the way, we devise an ordered
locality-preserving variant of the cut distance between ordered graphs, showing
that two graphs are close with respect to this distance if and only if they are
similar in terms of their ordered subgraph frequencies. We show that the space
of orderons is compact with respect to this distance notion, which is key to a
successful analysis of combinatorial objects through their limits.
We derive several applications of the ordered limit theory in extremal
combinatorics, sampling, and property testing in ordered graphs. In particular,
we prove a new ordered analogue of the well-known result by Alon and Stav
[RS\&A'08] on the furthest graph from a hereditary property; this is the first
known result of this type in the ordered setting. Unlike the unordered regime,
here the random graph model with an ordering over the vertices is
\emph{not} always asymptotically the furthest from the property for some .
However, using our ordered limit theory, we show that random graphs generated
by a stochastic block model, where the blocks are consecutive in the vertex
ordering, are (approximately) the furthest. Additionally, we describe an
alternative analytic proof of the ordered graph removal lemma [Alon et al.,
FOCS'17].Comment: Added a new application: An Alon-Stav type result on the furthest
ordered graph from a hereditary property; Fixed and extended proof sketch of
the removal lemma applicatio
The b-Matching Problem in Distance-Hereditary Graphs and Beyond
We make progress on the fine-grained complexity of Maximum-Cardinality Matching on graphs of bounded clique-width. Quasi linear-time algorithms for this problem have been recently proposed for the important subclasses of bounded-treewidth graphs (Fomin et al., SODA\u2717) and graphs of bounded modular-width (Coudert et al., SODA\u2718). We present such algorithm for bounded split-width graphs - a broad generalization of graphs of bounded modular-width, of which an interesting subclass are the distance-hereditary graphs. Specifically, we solve Maximum-Cardinality Matching in O((k log^2{k})*(m+n) * log{n})-time on graphs with split-width at most k. We stress that the existence of such algorithm was not even known for distance-hereditary graphs until our work. Doing so, we improve the state of the art (Dragan, WG\u2797) and we answer an open question of (Coudert et al., SODA\u2718). Our work brings more insights on the relationships between matchings and splits, a.k.a., join operations between two vertex-subsets in different connected components. Furthermore, our analysis can be extended to the more general (unit cost) b-Matching problem. On the way, we introduce new tools for b-Matching and dynamic programming over split decompositions, that can be of independent interest
A Single-Exponential Fixed-Parameter Algorithm for Distance-Hereditary Vertex Deletion
Vertex deletion problems ask whether it is possible to delete at most
vertices from a graph so that the resulting graph belongs to a specified graph
class. Over the past years, the parameterized complexity of vertex deletion to
a plethora of graph classes has been systematically researched. Here we present
the first single-exponential fixed-parameter tractable algorithm for vertex
deletion to distance-hereditary graphs, a well-studied graph class which is
particularly important in the context of vertex deletion due to its connection
to the graph parameter rank-width. We complement our result with matching
asymptotic lower bounds based on the exponential time hypothesis. As an
application of our algorithm, we show that a vertex deletion set to
distance-hereditary graphs can be used as a parameter which allows
single-exponential fixed-parameter tractable algorithms for classical NP-hard
problems.Comment: 43 pages, 9 figures (revised journal version; an extended abstract
appeared in the proceedings of MFCS 2016
Hamilton cycles in almost distance-hereditary graphs
Let be a graph on vertices. A graph is almost
distance-hereditary if each connected induced subgraph of has the
property for any pair of vertices .
A graph is called 1-heavy (2-heavy) if at least one (two) of the end
vertices of each induced subgraph of isomorphic to (a claw) has
(have) degree at least , and called claw-heavy if each claw of has a
pair of end vertices with degree sum at least . Thus every 2-heavy graph is
claw-heavy. In this paper we prove the following two results: (1) Every
2-connected, claw-heavy and almost distance-hereditary graph is Hamiltonian.
(2) Every 3-connected, 1-heavy and almost distance-hereditary graph is
Hamiltonian. In particular, the first result improves a previous theorem of
Feng and Guo. Both results are sharp in some sense.Comment: 14 pages; 1 figure; a new theorem is adde
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