11 research outputs found
Sphericity, cubicity, and edge clique covers of graphs
AbstractThe sphericity sph(G) of a graph G is the minimum dimension d for which G is the intersection graph of a family of congruent spheres in Rd. The edge clique cover number θ(G) is the minimum cardinality of a set of cliques (complete subgraphs) that covers all edges of G. We prove that if G has at least one edge, then sph(G)⩽θ(G). Our upper bound remains valid for intersection graphs defined by balls in the Lp-norm for 1⩽p⩽∞
Cubicity of interval graphs and the claw number
Let be a simple, undirected graph where is the set of vertices
and is the set of edges. A -dimensional cube is a Cartesian product
, where each is a closed interval of
unit length on the real line. The \emph{cubicity} of , denoted by \cub(G)
is the minimum positive integer such that the vertices in can be mapped
to axis parallel -dimensional cubes in such a way that two vertices are
adjacent in if and only if their assigned cubes intersect. Suppose
denotes a star graph on nodes. We define \emph{claw number} of
the graph to be the largest positive integer such that is an induced
subgraph of . It can be easily shown that the cubicity of any graph is at
least \ceil{\log_2\psi(G)}.
In this paper, we show that, for an interval graph
\ceil{\log_2\psi(G)}\le\cub(G)\le\ceil{\log_2\psi(G)}+2. Till now we are
unable to find any interval graph with \cub(G)>\ceil{\log_2\psi(G)}. We also
show that, for an interval graph , \cub(G)\le\ceil{\log_2\alpha}, where
is the independence number of . Therefore, in the special case of
, \cub(G) is exactly \ceil{\log_2\alpha}.
The concept of cubicity can be generalized by considering boxes instead of
cubes. A -dimensional box is a Cartesian product , where each is a closed interval on the real
line. The \emph{boxicity} of a graph, denoted , is the minimum
such that is the intersection graph of -dimensional boxes. It is clear
that box(G)\le\cub(G). From the above result, it follows that for any graph
, \cub(G)\le box(G)\ceil{\log_2\alpha}
Cubicity, Degeneracy, and Crossing Number
A -box , where each is a closed interval on the
real line, is defined to be the Cartesian product . If each is a unit length interval, we call a
-cube. Boxicity of a graph , denoted as \boxi(G), is the minimum
integer such that is an intersection graph of -boxes. Similarly, the
cubicity of , denoted as \cubi(G), is the minimum integer such that
is an intersection graph of -cubes.
It was shown in [L. Sunil Chandran, Mathew C. Francis, and Naveen Sivadasan:
Representing graphs as the intersection of axis-parallel cubes. MCDES-2008,
IISc Centenary Conference, available at CoRR, abs/cs/ 0607092, 2006.] that, for
a graph with maximum degree , \cubi(G)\leq \lceil 4(\Delta +1)\log
n\rceil. In this paper, we show that, for a -degenerate graph ,
\cubi(G) \leq (k+2) \lceil 2e \log n \rceil. Since is at most
and can be much lower, this clearly is a stronger result. This bound is tight.
We also give an efficient deterministic algorithm that runs in time
to output a dimensional cube representation
for .
An important consequence of the above result is that if the crossing number
of a graph is , then \boxi(G) is . This bound is tight up to a factor of .
We also show that, if has vertices, then \cubi(G) is .
Using our bound for the cubicity of -degenerate graphs we show that
cubicity of almost all graphs in model is ,
where denotes the average degree of the graph under consideration.Comment: 21 page
OV Graphs Are (Probably) Hard Instances
© Josh Alman and Virginia Vassilevska Williams. A graph G on n nodes is an Orthogonal Vectors (OV) graph of dimension d if there are vectors v1, . . ., vn ∈ {0, 1}d such that nodes i and j are adjacent in G if and only if hvi, vji = 0 over Z. In this paper, we study a number of basic graph algorithm problems, except where one is given as input the vectors defining an OV graph instead of a general graph. We show that for each of the following problems, an algorithm solving it faster on such OV graphs G of dimension only d = O(log n) than in the general case would refute a plausible conjecture about the time required to solve sparse MAX-k-SAT instances: Determining whether G contains a triangle. More generally, determining whether G contains a directed k-cycle for any k ≥ 3. Computing the square of the adjacency matrix of G over Z or F2. Maintaining the shortest distance between two fixed nodes of G, or whether G has a perfect matching, when G is a dynamically updating OV graph. We also prove some complementary results about OV graphs. We show that any problem which is NP-hard on constant-degree graphs is also NP-hard on OV graphs of dimension O(log n), and we give two problems which can be solved faster on OV graphs than in general: Maximum Clique, and Online Matrix-Vector Multiplication
Edge Clique Cover of Claw-free Graphs
The smallest number of cliques, covering all edges of a graph , is
called the (edge) clique cover number of and is denoted by . It
is an easy observation that for every line graph with vertices,
. G. Chen et al. [Discrete Math. 219 (2000), no. 1--3, 17--26;
MR1761707] extended this observation to all quasi-line graphs and questioned if
the same assertion holds for all claw-free graphs. In this paper, using the
celebrated structure theorem of claw-free graphs due to Chudnovsky and Seymour,
we give an affirmative answer to this question for all claw-free graphs with
independence number at least three. In particular, we prove that if is a
connected claw-free graph on vertices with , then and equality holds if and only if is either the graph of
icosahedron, or the complement of a graph on vertices called twister or
the power of the cycle , for .Comment: 74 pages, 4 figure