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Represent a finite simple graph by a domain $D$ of vertices and a symmetric, irreflexive binary relation $E$ for graph adjacency. Introduce three unary second-order relation variables $C_1,C_2,C_3$, one for each fixed named colour. Define the following abbreviations for first-order formulas in this expanded first-order signature:Then the existential second-order logic sentenceasserts that every vertex receives exactly one of the three colours and adjacent vertices receive different colours. The first clause gives coverage and pairwise disjointness of the three subsets; the second makes each subset an independent set. Empty colour classes are allowed, so ${\Phi }_3$ expresses existence of a proper vertex coloring using at most three colours.

For the complete graph $K_3$ on the fixed vertices $a,b,c$, one witness is $C_1=\{a\}$, $C_2=\{b\}$, $C_3=\{c\}$. Each vertex satisfies exactly one predicate, and each of the three edges joins different predicates. Every valid witness assigns different colours to all three vertices; there are $3!=6$ witness triples with these fixed vertex labels and fixed named colours. We are counting assignments, without identifying them under colour permutations or graph isomorphisms. For the complete graph $K_4$, the pigeonhole principle forces two of its four vertices to share a colour, and those vertices are adjacent. Thus it has no witness triple. This calculation illustrates a complexity certificate without requiring the reader to reconstruct a machine computation.

Reproduce the diagram by running python ../second-order-coloring-witness.py from the repository's _media directory. The script checks all witness triples for these two complete graphs before drawing them.

Second-order logic extends first-order logic by allowing existential quantification and universal quantification over second-order relation variables, as well as over individual objects. In the relational presentation used here, an individual variable $x$ ranges over a domain $D$, while a second-order relation variable $R$ of arity $k$ denotes a subset of $D^k$. Unary second-order relation variables denote subsets of $D$; binary ones denote binary relations. Presentations with function variables can instead describe their graphs by second-order relation variables, with first-order formulas requiring a unique output for every input.

For a graph with vertices $D$ and fixed graph adjacency $E$, the first-order sentence $\forall x\exists yE(x,y)$ says that every vertex has a neighbour. It selects individual vertices while $E$ retains its given interpretation. By contrast,selects an entire subset $P$ and says that it is a nonempty independent set. Here $P$ is a unary second-order relation variable, rather than a symbol in the input first-order signature. This particular property also has a simple first-order sentence on simple graphs; the example illustrates the change in what can be selected, rather than proving a separation in expressive power.

The usefulness of second-order logic is that one can describe a whole proposed solution, such as a graph coloring, and then impose local constraints on it. Syntax alone does not specify which proposed relations are available: full semantics for second-order logic permits all external subsets of $D^k$, whereas Henkin semantics supplies designated ranges. The second-order encoding of three-colorability makes this distinction concrete.

Replacing an existentially quantified variable by a fresh Skolem function of the preceding universally quantified variables. A witness independent of all universal variables is represented by a fresh constant. The operation preserves satisfiability after expanding the first-order signature; it is not generally logical equivalence for arbitrary interpretations of the new symbols.

A first-order sentence consisting of a block of universal quantifiers followed by a quantifier-free formula, obtained by Skolemization in an expanded first-order signature. Its matrix can additionally be put into conjunctive normal form to obtain clausal form.