After earlier
polynomial time algorithms, presented an algorithm for recognizing circular graphs in near-linear time. Their method is slower than linear by a factor of the
inverse Ackermann function, and is based on
lexicographic breadth-first search. The running time comes from a method for maintaining the
split decomposition of a graph incrementally, as vertices are added, used as a subroutine in the algorithm. More recent work has shown that circle graphs can be recognized in
linear time. A number of other problems that are
NP-complete on general graphs have polynomial time algorithms when restricted to circle graphs. For instance, showed that the
treewidth of a circle graph can be determined, and an optimal tree decomposition constructed, in O(
n3) time. Additionally, a minimum fill-in (that is, a
chordal graph with as few edges as possible that contains the given circle graph as a subgraph) may be found in O(
n3) time. has shown that a
maximum clique of a circle graph can be found in O(
n log2
n) time, while have shown that a
maximum independent set of an unweighted circle graph can be found in O(
n min{
d,
α}) time, where
d is a parameter of the graph known as its density, and
α is the independence number of the circle graph. However, there are also problems that remain NP-complete when restricted to circle graphs. These include the
minimum dominating set, minimum connected dominating set, and minimum total dominating set problems. ==Chromatic number==