12 research outputs found
Two results on the digraph chromatic number
It is known (Bollob\'{a}s (1978); Kostochka and Mazurova (1977)) that there
exist graphs of maximum degree and of arbitrarily large girth whose
chromatic number is at least . We show an analogous
result for digraphs where the chromatic number of a digraph is defined as
the minimum integer so that can be partitioned into acyclic
sets, and the girth is the length of the shortest cycle in the corresponding
undirected graph. It is also shown, in the same vein as an old result of Erdos
(1962), that there are digraphs with arbitrarily large chromatic number where
every large subset of vertices is 2-colorable
Colouring Complete Multipartite and Kneser-type Digraphs
The dichromatic number of a digraph is the smallest such that can
be partitioned into acyclic subdigraphs, and the dichromatic number of an
undirected graph is the maximum dichromatic number over all its orientations.
Extending a well-known result of Lov\'{a}sz, we show that the dichromatic
number of the Kneser graph is and that the
dichromatic number of the Borsuk graph is if is large
enough. We then study the list version of the dichromatic number. We show that,
for any and , the list
dichromatic number of is . This extends a recent
result of Bulankina and Kupavskii on the list chromatic number of ,
where the same behaviour was observed. We also show that for any ,
and , the list dichromatic number of the complete
-partite graph with vertices in each part is , extending
a classical result of Alon. Finally, we give a directed analogue of Sabidussi's
theorem on the chromatic number of graph products.Comment: 15 page
All-Pairs LCA in DAGs: Breaking through the barrier
Let be an -vertex directed acyclic graph (DAG). A lowest common
ancestor (LCA) of two vertices and is a common ancestor of and
such that no descendant of has the same property. In this paper, we
consider the problem of computing an LCA, if any, for all pairs of vertices in
a DAG. The fastest known algorithms for this problem exploit fast matrix
multiplication subroutines and have running times ranging from
[Bender et al.~SODA'01] down to [Kowaluk and Lingas~ICALP'05]
and [Czumaj et al.~TCS'07]. Somewhat surprisingly, all those
bounds would still be even if matrix multiplication could be
solved optimally (i.e., ). This appears to be an inherent barrier for
all the currently known approaches, which raises the natural question on
whether one could break through the barrier for this problem.
In this paper, we answer this question affirmatively: in particular, we
present an ( for ) algorithm
for finding an LCA for all pairs of vertices in a DAG, which represents the
first improvement on the running times for this problem in the last 13 years. A
key tool in our approach is a fast algorithm to partition the vertex set of the
transitive closure of into a collection of chains and
antichains, for a given parameter . As usual, a chain is a path while an
antichain is an independent set. We then find, for all pairs of vertices, a
\emph{candidate} LCA among the chain and antichain vertices, separately. The
first set is obtained via a reduction to min-max matrix multiplication. The
computation of the second set can be reduced to Boolean matrix multiplication
similarly to previous results on this problem. We finally combine the two
solutions together in a careful (non-obvious) manner
Digraph Coloring Games and Game-Perfectness
In this thesis the game chromatic number of a digraph is introduced as a game-theoretic variant of the dichromatic number. This notion generalizes the well-known game chromatic number of a graph. An extended model also takes into account relaxed colorings and asymmetric move sequences. Game-perfectness is defined as a game-theoretic variant of perfectness of a graph, and is generalized to digraphs. We examine upper and lower bounds for the game chromatic number of several classes of digraphs. In the last part of the thesis, we characterize game-perfect digraphs with small clique number, and prove general results concerning game-perfectness. Some results are verified with the help of a computer program that is discussed in the appendix