Split graph

A split graph, partitioned into a clique and an independent set.

In graph theory, a branch of mathematics, a split graph is a graph in which the vertices can be partitioned into a clique and an independent set. Split graphs were first studied by Template:Harvs, and independently introduced by Template:Harvs, where they called these graphs "polar graphs" (Template:Langx).

A split graph may have more than one partition into a clique and an independent set; for instance, the path Template:Math is a split graph, the vertices of which can be partitioned in three different ways:

1. the clique Template:Math and the independent set Template:Math
2. the clique Template:Math and the independent set Template:Math
3. the clique Template:Math and the independent set Template:Math

Split graphs can be characterized in terms of their forbidden induced subgraphs: a graph is split if and only if no induced subgraph is a cycle on four or five vertices, or a pair of disjoint edges (the complement of a 4-cycle).

Relation to other graph families

From the definition, split graphs are clearly closed under complementation. Another characterization of split graphs involves complementation: they are chordal graphs the complements of which are also chordal. Just as chordal graphs are the intersection graphs of subtrees of trees, split graphs are the intersection graphs of distinct substars of star graphs. Almost all chordal graphs are split graphs; that is, in the limit as n goes to infinity, the fraction of n-vertex chordal graphs that are split approaches one.

Because chordal graphs are perfect, so are the split graphs. The double split graphs, a family of graphs derived from split graphs by doubling every vertex (so the clique comes to induce an antimatching and the independent set comes to induce a matching), figure prominently as one of five basic classes of perfect graphs from which all others can be formed in the proof by Template:Harvtxt of the Strong Perfect Graph Theorem.

If a graph is both a split graph and an interval graph, then its complement is both a split graph and a comparability graph, and vice versa. The split comparability graphs, and therefore also the split interval graphs, can be characterized in terms of a set of three forbidden induced subgraphs. The split cographs are exactly the threshold graphs. The split permutation graphs are exactly the interval graphs that have interval graph complements; these are the permutation graphs of skew-merged permutations.Template:Sfnp Split graphs have cochromatic number 2.

Algorithmic problems

Let Template:Mvar be a split graph, partitioned into a clique Template:Mvar and an independent set Template:Mvar. Then every maximal clique in a split graph is either Template:Mvar itself, or the neighborhood of a vertex in Template:Mvar. Thus, it is easy to identify the maximum clique, and complementarily the maximum independent set in a split graph. In any split graph, one of the following three possibilities must be true:

1. There exists a vertex Template:Mvar in Template:Mvar such that Template:Math is complete. In this case, Template:Math is a maximum clique and Template:Mvar is a maximum independent set.
2. There exists a vertex Template:Mvar in Template:Mvar such that Template:Math is independent. In this case, Template:Math is a maximum independent set and Template:Mvar is a maximum clique.
3. Template:Mvar is a maximal clique and Template:Mvar is a maximal independent set. In this case, Template:Mvar has a unique partition Template:Math into a clique and an independent set, Template:Mvar is the maximum clique, and Template:Mvar is the maximum independent set.

Some other optimization problems that are NP-complete on more general graph families, including graph coloring, are similarly straightforward on split graphs. Finding a Hamiltonian cycle remains NP-complete even for split graphs which are strongly chordal graphs. It is also well known that the Minimum Dominating Set problem remains NP-complete for split graphs.

Degree sequences

One remarkable property of split graphs is that they can be recognized solely from their degree sequences. Let the degree sequence of a graph Template:Mvar be Template:Math, and let Template:Mvar be the largest value of Template:Mvar such that Template:Math. Then Template:Mvar is a split graph if and only if

$\sum _{i=1}^m{d}_i=m(m-1)+\sum _{i=m+1}^n{d}_i.$

If this is the case, then the Template:Mvar vertices with the largest degrees form a maximum clique in Template:Mvar, and the remaining vertices constitute an independent set.

The splittance of an arbitrary graph measures the extent to which this inequality fails to be true. If a graph is not a split graph, then the smallest sequence of edge insertions and removals that make it into a split graph can be obtained by adding all missing edges between the Template:Mvar vertices with the largest degrees, and removing all edges between pairs of the remaining vertices; the splittance counts the number of operations in this sequence.Template:Sfnp

Counting split graphs

Template:Harvtxt showed that (unlabeled) n-vertex split graphs are in one-to-one correspondence with certain Sperner families. Using this fact, he determined a formula for the number of nonisomorphic split graphs on n vertices. For small values of n, starting from n = 1, these numbers are

1, 2, 4, 9, 21, 56, 164, 557, 2223, 10766, 64956, 501696, ... Template:OEIS.

This enumerative result was also proved earlier by Template:Harvtxt.

References

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• Template:Citation. Translated as "Yet another method of enumerating unmarked combinatorial objects" (1990), Mathematical notes of the Academy of Sciences of the USSR 48 (6): 1239–1245, Template:Doi.
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Further reading

• A chapter on split graphs appears in the book by Martin Charles Golumbic, "Algorithmic Graph Theory and Perfect Graphs".