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Here graphs are finite and simple. To prove Dirac theorem, take a longest path $v_1,\dots ,v_{\ell }$. All neighbours of either endpoint lie on the path. Among indices $1\le i<\ell$, let $S=\{i:v_1{v}_{i+1}\text{ is an edge}\}$ and $T=\{i:v_i{v}_{\ell }\text{ is an edge}\}$. Since $|S|+|T|=d(v_1)+d(v_{\ell })\ge n>\ell -1$, some $i$ lies in both. Following the path forward to $v_i$, jumping to $v_{\ell }$, and following it backwards to $v_{i+1}$ closes a cycle containing every vertex of the path. The degree condition makes the graph connected: two components would each have at least $\delta +1>n/2$ vertices. If $\ell <n$, connectedness gives an edge from an outside vertex to the cycle, and breaking the cycle there makes a longer path. This contradiction proves a Hamiltonian cycle.

For even $n=2m$, the complete bipartite graph $K_{m-1,m+1}$ has minimum degree $m-1$ and no Hamiltonian cycle. For odd $n=2m+1$, $K_{m,m+1}$ has minimum degree $m$ and likewise fails: a bipartite cycle uses equal numbers from its two parts. These examples include the smallest applicable $n$.

Adding one universal vertex gives $n+1$ vertices and minimum degree at least $(n+1)/2$ when the original minimum degree is at least $(n-1)/2$. Apply the proved theorem and remove the universal vertex from its cycle. The remaining sequence is a Hamiltonian path in the original graph.

A necessary condition for a Hamiltonian cycle is that deleting a nonempty vertex set $S$ leaves at most $|S|$ components, since deleting those vertices breaks a spanning cycle into at most that many path pieces. For any $k\ge 1$, take the connected star $G=K_{1,k+2}$. In $G_k$, deleting its center and the $k$ new vertices leaves $k+2$ components, more than $k+1$. Even two-connectivity does not suffice: take $G=K_{2,k+3}$, which is two-connected. Deleting its two-vertex part and the $k$ new vertices from $G_k$ leaves $k+3$ components, more than $k+2$. Both connectivity requirements admit counterexamples for every $k$.

Write $q=m/s$, an integer under the stated divisibility assumption. The degree relation gives $n=rm/s=qr$. Take the disjoint union of graphs of $q$ copies of the complete bipartite graph $K_{s,r}$, placing its $s$-vertex part in $U$ and its $r$-vertex part in $W$. The total part sizes are then $qs=m$ and $qr=n$. Each left vertex has vertex degree $r$, and each right vertex has vertex degree $s$, so the graph has exactly the required biregular graph parameters.

An independent set in one component can be any subset of its left part or any subset of its right part. It cannot contain a vertex from both parts, because all cross-pairs are edges. The two families share only the empty set, so the component has $2^s+2^r-1$ independent sets. Choices in different connected components of a graph are independent combinatorial choices, and their counts multiply. HenceThis attains equality in part (i). It also explains the entropy weight $2^r$ there: the empty selected left neighbourhood permits all $2^r$ subsets of the opposite part.

Write $\alpha =1-1/r$. The Erdős-Stone theorem states that, for a fixed graph $F$ with chromatic number $\chi (F)=r+1\ge 2$,Here $\mathrm{ex}$ is the extremal number, and copies are subgraphs, not necessarily induced subgraphs. We write $K_a(b)$ for the balanced complete multipartite blow-up with $a$ classes of $b$ vertices each. All asymptotic errors below concern $n\to \infty$ with the forbidden graphs fixed.

The stability subgraph. We prove the high-minimum-degree multipartite stability subgraph assertion directly from the Erdős-Stone theorem. For $r=1$, the edgeless spanning subgraph suffices. Suppose $r\ge 2$.

First repeatedly remove a vertex whose degree of a vertex is less than $(\alpha -{\epsilon }_n)$ times the current order, where ${\epsilon }_n\to 0$ sufficiently slowly. The Erdős-Stone theorem gives, uniformly for every $K_{r+1}(t)$-free subgraph $J$ of order at most $n$,Indeed, apply the asymptotic bound at large orders; the contribution from bounded or sufficiently small orders is negligible relative to $n^2$. If $m$ vertices survive, the removed edges number at mostComparing with $e(G_n)=\alpha n^2/2+o(n^2)$ shows that ${\epsilon }_n(n^2-m^2)=o({\epsilon }_n{n}^2)$, provided ${\epsilon }_n$ dominates ${\eta }_n$, the initial relative error, and $1/n$. Consequently $m=n-o(n)$. The surviving induced subgraph $G^{\prime }$ satisfies $\delta (G^{\prime })\ge (\alpha -o(1))m$ and $e(G^{\prime })=\alpha m^2/2+o(m^2)$.

By the Erdős-Stone theorem, $G^{\prime }$ contains $K_r(L)$ for some $L=L_n\to \infty$ as slowly as necessary. This follows because $\alpha$ exceeds the extremal number density for each fixed $K_r(L)$ by the positive gap $1/(r(r-1))$. Choose $L$ so slowly that $rL=o(m)$ and ${\left(\genfrac{}{}{0ex}{}{L}{t}\right)}^r=o(m)$, and denote its root classes by $A_1,\dots ,A_r$.

An outside vertex having at least $t$ neighbours of a vertex in every $A_i$ determines one choice of a $t$-subset in each $A_i$. At most $t-1$ outside vertices can determine any fixed choice, since otherwise these vertices and the chosen root sets form $K_{r+1}(t)$. Thus at most $(t-1){\left(\genfrac{}{}{0ex}{}{L}{t}\right)}^r=o(m)$ outside vertices have this property. Exclude those vertices and the root classes; put each remaining vertex in a class $C_i$ for which it has fewer than $t$ neighbours of a vertex in $A_i$.

Write $\delta (G^{\prime })\ge (\alpha -{\gamma }_n)m$, with ${\gamma }_n\to 0$. Counting missing incidences with $A_i$ givesSince ${\sum }_i|C_i|=m-o(m)$, it follows that $|C_i|=m/r+o(m)$ for every $i$. The total missing incidences from all root vertices to assigned vertices are at most $(1+r{\gamma }_n)Lm$. At least $(L-t+1)(m-o(m))$ of them are incidences with a vertex's own assigned root class. Hence only $o(Lm)$ missing incidences go to other root classes.

Choose ${\rho }_n\to 0$ slowly and discard the $o(m)$ assigned vertices with more than ${\rho }_{n}L$ missing incidences to other root classes. Each remaining vertex of $C_i$ is adjacent to all but at most ${\rho }_{n}L$ vertices of every $A_j$, $j\ne i$. If its class contained a complete bipartite graph $K_{t,t}$, the $2t$ vertices of this copy would have at least $L-2t{\rho }_{n}L\ge t$ common neighbours of a vertex in each other root class. These sets extend the copy to $K_{r+1}(t)$, a contradiction. By the bipartite case of the Erdős-Stone theorem, the number of internal edges in each surviving class is $o(m^2)$.

The surviving graph still has $\alpha m^2/2+o(m^2)$ edges, whereas the total possible cross-class edges, with these balanced classes, is $\alpha m^2/2+o(m^2)$. Thus only $o(m^2)$ cross-class edges are missing. Discard the $o(m)$ vertices missing more than ${\sigma }_{n}m$ cross-class edges, with ${\sigma }_n\to 0$ slowly, and delete all internal edges. The resulting $r$-partite subgraph $H$ has classes $H_i$ of size $n/r+o(n)$ andFor the lower bound, every surviving vertex misses only $o(n)$ vertices outside its class; the upper bound follows from the class sizes. This also records the uniform cross-class error that we need next.

Minimum degree in an extremal graph. Fix $F$ with $\chi (F)=r+1$. Choose $t$ large enough that $F$ embeds in $K_{r+1}(t)$. An extremal $F$-free graph $G$ is therefore $K_{r+1}(t)$-free, and its edge count has the required asymptotics by the Erdős-Stone theorem. For $r\ge 2$ take $H$ as above.

For any vertex $v$, remove $v$ and introduce a new vertex $v^{\ast }$ whose vertex neighbourhood consists precisely of the vertices in $H_2\cup \cdots \cup H_r$ other than $v$. The new degree of a vertex is $\alpha n-o(n)$. This new graph remains $F$-free. Indeed, a new copy of $F$ must use $v^{\ast }$, and all its neighbours of a vertex in that copy lie in the other classes of $H$. There are only boundedly many of them. Each misses only $o(n)$ vertices in $H_1$, so an unused vertex $w\in H_1$ is adjacent to all of them. Replacing $v^{\ast }$ by $w$ would give $F$ in $G-v$, which is impossible.

Extremality now forces $d_G(v)\ge \alpha n-o(n)$, uniformly in $v$. The upper bound for the minimum degree of a graph follows from $\delta (G)\le 2e(G)/n$. For $r=1$, $e(G)=o(n^2)$ already gives $0\le \delta (G)=o(n)$. ThusThis is the minimum degree of an extremal forbidden-subgraph graph principle.

The exact extremal graph for disjoint cliques. DefineThe plus sign denotes the join of graphs. The Turán graph contains no $K_{r+1}$, so every such clique in $J_s(n)$ uses a vertex of $K_{s-1}$. Therefore $J_s(n)$ contains no $s$ vertex-disjoint such cliques, and the extremal number is at least $b_s(n)$.

Induct on $s$, with $s=1$ supplied by the Turan theorem, including its equality characterization. Let $s\ge 2$ and let $G$ be extremal for $s{K}_{r+1}$. The preceding results give $\delta (G)\ge \alpha n-o(n)$ and the $r$-partite subgraph $H$. Keep its classes $H_i$ fixed and assign each of the remaining $o(n)$ vertices to a class in which it has fewest neighbours of a vertex in $H$. Write the resulting classes as $C_i$; all have size $n/r+o(n)$. Choose a positive ${\tau }_n\to 0$ so slowly that ${\tau }_{n}n$ dominates the outside count, every cross-class error in $H$, and every error in the minimum degree of a graph bound.

Suppose some vertex $x\in C_i$ has at least ${\tau }_{n}n$ internal neighbours of a vertex. If $x\notin H$, the assignment rule shows that $x$ has at least ${\tau }_{n}n-o(n)$ neighbours of a vertex in every $H_j$. If $x\in H_i$, it has this many in $H_i$ and $n/r-o(n)$ in the other $H_j$. If $G-x$ contained $s-1$ disjoint $K_{r+1}$, we could choose one vertex in each $N(x)\cap H_j$, successively avoiding those copies and the $o(n)$ missing cross-neighbours of the already chosen vertices. This produces a further $K_{r+1}$ through $x$. For $r=1$, this just chooses an unused neighbour of $x$. Hence $G-x$ is $(s-1)K_{r+1}$-free, and induction givesSince the candidate attains $b_s(n)$, equality holds throughout: $x$ is a universal vertex and $G-x$ is the inductively unique extremal graph. Thus $G$ is isomorphic to $J_s(n)$.

It remains to show that this case must occur. Otherwise all internal vertex degrees are less than ${\tau }_{n}n=o(n)$. Together with the lower bound on $\delta (G)$ and $|C_i|=n/r+o(n)$, this implies that every vertex misses only $o(n)$ vertices outside its own class. If some $C_i$ contains a matching in a graph of $s$ edges, extend its edges one by one to $K_{r+1}$, choosing one vertex from each other class. At every step only $o(n)$ cross-neighbours and boundedly many used vertices are excluded. This gives $s$ disjoint forbidden cliques, a contradiction.

A maximal matching in each class therefore has at most $s-1$ edges, and its at most $2(s-1)$ endpoints form a vertex cover of the internal edges. Their internal vertex degrees are all $o(n)$, so the total internal edge count is $o(n)$. The cross-class edge count is at most $e(T_r(n))$, whenceBut the balanced part sizes of the Turán graph givecontradicting extremality for $s\ge 2$. This argument also works for $r=1$. Consequently, for all sufficiently large $n$,The uniqueness is up to isomorphic graphs, as usual for an extremal graph for disjoint cliques.

Symmetrization for an arbitrary real coefficient. Among graphs maximizing $f(G)=e(G)-c{k}_3(G)$, choose one maximizingFor a vertex $x$, put $L(x)=d(x)-ce(G[N(x)])$. This is the contribution of edges and triangles in a graph containing $x$. If $u,v$ are nonadjacent, Zykov symmetrization replacing $u$ by a clone of $v$ changes $f$ by $L(v)-L(u)$; the opposite replacement changes it by $L(u)-L(v)$. Maximality implies $L(u)=L(v)$, so both changes preserve $f$.

Let $S=N(v)\setminus N(u)$ and $T=N(u)\setminus N(v)$. In the first replacement the vertex degrees in $S$ increase by one and those in $T$ decrease by one; in the opposite replacement these changes reverse. The changes to $d(u{)}^2+d(v{)}^2$ cancel when the two replacements are added. Since $(d+1{)}^2+(d-1{)}^2-2d^2=2$,If the two vertex neighbourhoods differ, one replacement increases $Q$, a contradiction. Thus every pair of nonadjacent vertices has the same vertex neighbourhood. Nonadjacency, with equality allowed, is an equivalence relation: if $u$ and $v$ are nonadjacent and $v$ and $w$ are nonadjacent, their identical vertex neighbourhoods forbid $uw$ as well. Its classes are independent sets and every cross-class edge is present. ThereforeThis edge-triangle symmetrization works for either sign of $c$.

The exact supporting line. For $n\ge 3$, writeWe prove the triangle support line between bipartite and tripartite Turan graphs by maximizing $e-c_{\ast }{k}_3$. First $c_{\ast }\ge 2/n$. For $n=3,4,5$, its values are respectively $1,1/2,1/2$. For $n\ge 6$, the exact balancing of the Turán graph gives $e_3\ge n^2/3-1/3$, while $e_2\le n^2/4$ and the arithmetic-geometric mean inequality gives $t_3\le n^3/27$. Hence

By edge-triangle symmetrization a maximizing graph can be taken complete multipartite graph; among such maximizers use one with the fewest nonempty parts. If there are at least four parts, let $a,b$ be the two smallest sizes. Then $a+b\le n/2$. Merging them loses $ab$ edges and $ab(n-a-b)$ triangles in a graph, so the objective changes byThis contradicts the choice of the number of parts. Thus at most three parts remain.

For three part sizes $a\ge b\ge d>0$, the objective isIf $1-c_{\ast }b\le 0$, merging the parts of sizes $a,d$ does not decrease it, again contradicting minimality. If $1-c_{\ast }b>0$ and $a-d\ge 2$, transferring one vertex from the largest to the smallest part raises $ad$ by $a-d-1>0$ and strictly increases the objective. Thus a three-part maximizer has all sizes differing by at most one, and is $T_3(n)$. A maximizer with at most two parts has objective at most $e_2$, since it has no triangles in a graph and the Mantel theorem bounds its edges. Finally,Therefore every graph satisfies $e(G)-c_{\ast }{k}_3(G)\le e_2$. At the prescribed edge count this givesFor $n\le 2$, the conclusion is simply the nonnegative lower bound zero. All rounding in the Turán graphs has been retained.

One edge above the bipartite threshold. Write $n=2m$. We prove the Triangle lower bound one edge above the Mantel threshold by induction on $m\ge 2$, allowing at least $m^2+1$ edges. For $m=2$, five edges on four vertices give two triangles in a graph, and adding edges preserves this bound.

We will also use the following consequence of an inductive bound: on $2a$ vertices, at least $a^2+q$ edges, for an integer $q\ge 1$, force at least $a+q-1$ triangles in a graph. Delete surplus edges first to leave exactly $a^2+q$. Repeatedly delete an edge in a triangle in a graph until $a^2+1$ edges remain. The Mantel theorem guarantees such a triangle in a graph at every step; each deletion destroys at least one distinct triangle in a graph. Apply the inductive bound to the remaining graph.

Now take exactly $m^2+1$ edges. If every edge lies in a triangle in a graph, the edge-triangle incidence bound gives $3k_3(G)\ge m^2+1$. This is at least $3m$ for $m\ge 3$; the base case was handled separately.

Otherwise choose an edge $uv$ in no triangle in a graph. Its endpoints have disjoint vertex neighbourhoods, so $d(u)+d(v)\le 2m$. Deleting $u,v$ removes exactly $d(u)+d(v)-1$ edges and leaves at least $(m-1{)}^2+1$ edges. If $d(u)+d(v)\le 2m-1$, it leaves at least $(m-1{)}^2+2$ edges, and the strengthened inductive bound gives at least $m$ triangles in a graph already.

If $d(u)+d(v)=2m$, induction gives at least $m-1$ triangles in a graph after deletion. There must be an additional triangle in a graph containing $u$ or $v$. Otherwise both $N(u)$ and $N(v)$ are independent sets; since they are disjoint and cover all vertices, $G$ would be bipartite graph, contradicting $e(G)>m^2$ by the Mantel theorem. HenceThe bound is sharp: add one internal edge to one class of the complete bipartite graph $K_{m,m}$. Its triangles in a graph are precisely that edge together with each of the $m$ vertices in the other class.

First consider a $K_{t,t}$-free bipartite graph with parts $X,Y$, each of size at most $n$, and $m$ edges. Count pairs $(S,y)$ in which $S$ is a $t$-element subset of the graph neighbourhood of $y\in Y$. Any $t$ vertices of $X$ have at most $t-1$ common neighbours, since $t$ common neighbours would form the complete bipartite graph $K_{t,t}$. ConsequentlyIf the average degree of a vertex is bounded in terms of $t$, then $m=O(n)$ and the required result is immediate. Otherwise, convexity of $x\mapsto \left(\genfrac{}{}{0ex}{}{x}{t}\right)$ and the preceding inequality giveand hence $m=O(n^{2-1/t})$. Every graph has a bipartite spanning subgraph containing at least half its edges, obtained by choosing a random bipartition. Applying the bipartite estimate to that subgraph proves the Kővári–Sós–Turán theorem in the required form:

The stated "nice" subsets of the finite cyclic group ${\mathbb{Z}}_n$ are Sidon sets. Ifthen $a+d=c+b$. Niceness forces $(a,b)=(c,d)$; the alternative pairing would force $a=b$. Thus the $|A|(|A|-1)$ ordered nonzero differences are distinct elements of the $n-1$ nonzero residue classes. Thereforeso

We first prove the required case of Menger's theorem directly. Split each vertex $v$ into $v_{min}$ and $v_{mout}$ joined by a directed edge of capacity one. Replace every graph edge $uv$ by the two directed edges $u_{mout}{v}_{min}$ and $v_{mout}{u}_{min}$ of capacity $k$, add a source joined to every $a_{\mathrm{in}}$ for $a\in A$, and join every $b_{\mathrm{out}}$ for $b\in B$ to a sink, using unit capacities at the ends.

Starting with zero integral flow, repeatedly augment by one along a source-to-sink path in the residual directed graph. If fewer than $k$ augmentations have occurred and no augmenting path remains, let $R$ be the residual-reachable vertices. The capacity from $R$ to its complement equals the current flow: every forward edge in this cut is saturated and every reverse edge carries zero flow, by residual reachability. Since the cut has capacity below $k$, it uses no capacity-$k$ graph edge. The original vertices whose unit-capacity split or endpoint edges cross the cut form an $AB$-separator of size below $k$, contrary to the hypothesis. Hence at least $k$ augmentations occur. The resulting integral flow decomposes into $k$ source-to-sink paths, and the unit split capacities make their corresponding $AB$ paths vertex-disjoint. This proves

The same augmenting-path proof, with the source vertex given capacity $k$, yields the fan lemma: from a vertex $x$ to any set of at least $k$ vertices in a k-connected graph, there is a $k$-fan with distinct endpoints.

Now let $C$ be a longest cycle in a finite $k$-connected graph $G$. If $C$ is not Hamiltonian, choose $x\notin C$. A $k$-fan from $x$ to $C$ has $k$ distinct attachment vertices. If $|C|<2k$, two consecutive attachment vertices on $C$ are joined by an edge of $C$, because the $k$ cyclic gaps cannot all have length at least two. The two corresponding fan paths form, through $x$, an alternative path of length at least two between those adjacent vertices. Replacing their edge on $C$ by this path creates a longer cycle, a contradiction. ThereforeThis is the Dirac circumference theorem; in particular, a $k$-connected graph contains a cycle of length at least $k$, and when $|G|\ge 2k$ it must contain one of length at least $2k$.

For $k=3$, every 3-connected graph with at least six vertices consequently has a cycle of length at least six. This cannot be improved: the complete bipartite graph $K_{3,m}$ is 3-connected for $m\ge 3$, but every cycle alternates between its two parts and therefore has length at most six. Taking $m$ arbitrarily large defeats every proposed bound above six. Hence

Fix $k\ge 1$ and sample $G$ from the Erdős-Rényi model with $p=\frac{1}{2}{n}^{-2/3}$. Let $X$ count copies of the complete bipartite graph $K_{3,3}$. By the expected subgraph count in the Erdős-Rényi model,

Put $m=\lceil n/k\rceil$ and let $Z$ count independent set of size $m$. If the chromatic number satisfies $\chi (G)\le k$, some colour class has at least $m$ vertices, so $Z\ge 1$. Moreover,because the positive part of the exponent is $O(n)$ whereas $p\left(\genfrac{}{}{0ex}{}{m}{2}\right)$ has order $n^{4/3}$. The first moment method therefore gives $\mathbb{P}(\chi (G)\le k)\le \mathbb{E}Z=o(1)$.

Using Markov inequality for $X$ and the union bound,for all sufficiently large $n$. Hence at least one such $G$ contains no $K_{3,3}$ and has $\chi (G)>k$.

The complete bipartite graph $K_{3,3}$ is connected, simple, and has no triangles because all its cycles have even length. It has $n=6$ vertices and $m=9$ edges. A planar drawing would require $9\le 2\cdot 6-4=8$ by part (i), a contradiction. Therefore $K_{3,3}$ is nonplanar.

The complete bipartite graph $K_{3,3}$ is not a planar graph. For example, a simple connected triangle-free planar graph with six vertices has at most $2\cdot 6-4=8$ edges, by Euler formula for a connected planar graph and the fact that every face has boundary length at least four; $K_{3,3}$ has nine edges. At least one edge must therefore be deleted.

Delete $a_3{b}_3$ from the bipartition $\{a_1,a_2,a_3\}\bigsqcup \{b_1,b_2,b_3\}$. The left drawing below is a planar embedding of all eight remaining edges. It proves that the minimum is one edge.

The complete bipartite graph $K_{2,3}$ is connected and has five vertices and six edges. It is a planar graph, as in the right drawing above. Euler formula for a connected planar graph therefore givesThis includes the unbounded exterior face.

Take the complete bipartite graph $\boxed{K_{3,4}}$. Its seven vertices have degrees four on one side and three on the other. Deleting any two vertices leaves at least one vertex on each side, so the remaining complete bipartite graph is connected.

Every cycle in a bipartite graph alternates between its two parts, using equal numbers of vertices from each. A Hamilton cycle here would have to use three vertices from one part and four from the other, which is impossible. Thus three-vertex connectivity and minimum degree three do not suffice for Hamiltonicity in this seven-vertex example.

A perfect matching is a matching in a graph that covers every vertex exactly once. Its edges have no shared endpoints, and every vertex is an endpoint of one selected edge. It is useful when a collection must be divided into disjoint pairs with no element left over.

In a bipartite graph with equally many vertices on its two sides, a perfect matching can assign every person one allowed job and every job one person. The example under permanent of a matrix has three people and three jobs, with exactly three valid assignments. The blue edges below show those three perfect matchings; a crossing in the drawing is not an extra vertex.

Every selected edge covers two vertices, so a graph with an odd integer number of vertices has no perfect matching. An even integer number is necessary but does not guarantee existence: an isolated vertex cannot be covered. A perfect matching also need not be unique. For example, the complete bipartite graph $K_{2,2}$ has two perfect matchings, corresponding to the two ways of assigning two people to two jobs.

Counting all perfect matchings is a different question from finding one. For a zero-one biadjacency matrix of a balanced bipartite graph, the count is its permanent of a matrix. The nonzero determinant criterion for a perfect matching supplies an existence test, but cancellation means that a zero determinant does not rule one out.

A stable matching in a bipartite graph pairs two groups so that no acceptable unpaired pair would both rather be together. Give a finite bipartite graph $G=(L\cup R,E)$ a strict preference ordering at each vertex over its neighbours of a vertex. An edge means that both endpoints regard the pair as acceptable; every acceptable partner ranks above being unmatched. Lists may be incomplete, and $L$ and $R$ may have unequal cardinalities. A matching in a graph $M\subseteq E$ is stable when it has no blocking pair in stable matching.

Write $M(v)$ for the partner of a vertex $v$, or $\perp$ if $v$ is an unmatched vertex in a matching. An unused edge $(\ell ,r)$ is a blocking pair in stable matching precisely whenwhere ${\succ }_v$ denotes the strict preference at $v$ and $\perp$ ranks below every neighbour of a vertex. Both inequalities matter: wanting a different partner alone cannot upset a stable matching. A stable matching need not be a perfect matching; the Gale-Shapley algorithm still finds one with incomplete lists and unequal sides.

Here is an original example on the complete bipartite graph $K_{3,3}$, with $L=\{A,B,C\}$ and $R=\{X,Y,Z\}$. Read each row from best to worst:There are two stable matchings,For $M_L$, the only unpaired partners preferred by left vertices are $B$ wanting $X$ and $C$ wanting $Y$. But $X$ prefers its partner $A$ to $B$, and $Y$ prefers its partner $B$ to $C$. Hence neither is a blocking pair in stable matching. For $M_R$, the left vertices want $A$ with $X$, $B$ with $X$ or $Y$, and $C$ with $Y$ or $Z$. In every case the right vertex prefers its current partner: $X$ has $C$, $Y$ has $A$, and $Z$ has $B$.

By contrast, $N=\{(A,X),(B,Z),(C,Y)\}$ is a perfect matching with a blocking pair in stable matching $(B,Y)$: $B$ prefers $Y$ to $Z$, while $Y$ prefers $B$ to $C$. The abandoned partners need not agree to the change; stability tests the incentives of the two endpoints of the unused edge.

There are $3!=6$ permutations of right partners. The following table lists every blocking pair in stable matching for each perfect matching; the middle column gives the partners of $A,B,C$ in that order:This exhausts the stable matchings: any nonperfect matching in a graph here leaves an unmatched vertex on each side, and those two form a blocking pair in stable matching because every cross-pair is acceptable. Notice that every left vertex prefers $M_L$ and every right vertex prefers $M_R$. Stability can accommodate opposing interests without selecting a single universally preferred outcome.

A stable matching addresses the possibility of mutually beneficial departures. Its definition contains no numerical total social benefit or maximum-weight matching objective. For example, assigning benefit $100$ to each edge of $N$ and zero to every other edge makes $N$ the unique maximum-weight matching, yet $(B,Y)$ still blocks it under the displayed preference relations. Such external benefits need not represent participants' rankings.

A star graph is the complete bipartite graph with one centre and $m$ leaves. Any pair of its edges meet at the centre.

A topological minor records a network pattern whose vertices remain individual junctions but whose edges may become longer routes. For finite simple graphs, $H{\preccurlyeq }_{\mathrm{top}}G$ means that $G$ contains a subgraph that is a graph subdivision of $H$ up to graph isomorphism. Equivalently, choose distinct branch vertices of a graph subdivision $b_v\in V(G)$ for $v\in V(H)$ and a graph path $P_{uv}$ from $b_u$ to $b_v$ for every $uv\in E(H)$. These are internally vertex-disjoint paths, and no internal vertex of any $P_{uv}$ is a branch vertex of a graph subdivision. Only endpoints corresponding to a shared target vertex may be shared.^[ref]

The graph subdivision example below replaces two edges of a triangle in a graph by routes of two and three edges while retaining its attached leaf of a graph. If the host graph also contains an extra edge $BD$, the same routes still witness a topological minor: delete $BD$ when selecting the subgraph. An induced subgraph is not required. However, routes that merely connect the right pairs are insufficient: using a branch vertex of a graph subdivision as an intermediate junction, or making two routes share an internal vertex, can change the local network structure.

Every topological minor is a graph minor. In each branch path of a graph subdivision, contract all but one edge; the disjoint interiors let this shorten each route without merging distinct branch vertices of a graph subdivision. This recovers $H$ after deleting unused vertices and edges.^[ref] The converse fails because an ordinary branch set of a graph minor can gather several junctions into one.

For the tree $T$ with vertices $u,v,a,b,c,d$ and edges $uv,ua,ub,vc,vd$, contracting $uv$ produces a star graph $K_{1,4}$: the branch sets of a graph minor are $\{u,v\},\{a\},\{b\},\{c\},\{d\}$. Both $u,v$ have degree of a vertex three; each of the other four vertices is a leaf of a graph with degree of a vertex one. The new centre $w$ has four distinct graph neighbours $a,b,c,d$; its degree of a vertex is $3+3-2=4$, in agreement with the edge contraction formula.

Yet $K_{1,4}$ is not a topological minor of $T$. In a graph subdivision of $K_{1,4}$, four branch paths of a graph subdivision must leave the centre through four different edges; sharing their first internal vertex would violate internal disjointness. Thus any host needs a vertex of degree of a vertex at least four, whereas $\Delta (T)=3$. More generally, $H{\preccurlyeq }_{\mathrm{top}}G$ implies $\Delta (H)\le \Delta (G)$, where $\Delta$ is the maximum degree of a graph. This bound concerns the host graph; extra unused edges may make its branch vertices of a graph subdivision have larger degrees of vertices than their target counterparts.

This distinction matters when a network's individual junctions have a limited number of connections: replacing a connection by a route preserves the number of routes meeting at each chosen junction, while contracting a connected region can combine connections from separate junctions. It also explains why a small nonplanar pattern can hide inside long routes. By Kuratowski's theorem, a finite simple graph is a planar graph exactly when it has neither the complete graph $K_5$ nor the complete bipartite graph $K_{3,3}$ as a topological minor. The obstruction is a graph subdivision inside the network, regardless of the number of intermediate vertices.

The vertex cover number records the size of a minimum vertex cover:The vertex cover number is a number, while a minimum vertex cover is a set attaining it. For the cycle graph $C_5$, the independence number is $2$, so the complement correspondence gives $\tau (C_5)=5-2=3$. The vertex cover $\{1,3,4\}$ above attains this size.

Every matching in a graph gives a lower bound on the vertex cover number. Its edges have no shared endpoints, so covering each selected edge requires a different vertex. Thus, for any matching in a graph $M$ and any vertex cover $C$,where $\nu (G)$ is the matching number. Exhibiting a matching in a graph and a vertex cover of the same size certifies that both are optimum. Kőnig's theorem for bipartite matching says that every finite bipartite graph admits this equality: $\nu (G)=\tau (G)$.^[ref]

For the complete bipartite graph $K_{2,3}$, let the left vertices be $L=\{a,b\}$ and the right vertices be $R=\{x,y,z\}$. All six edges join $L$ to $R$. Selecting $C=L$ covers every edge; selecting $M=\{ax,by\}$ gives a matching in a graph of size two. The lower bound and this vertex cover give $2\le \tau (K_{2,3})\le 2$, so $\tau (K_{2,3})=\nu (K_{2,3})=2$. The remaining vertices $R$ form a largest independent set of size three. Crossings of drawn edges are not extra vertices.

The bipartite graph hypothesis matters. In a triangle in a graph, any two vertices form a minimum vertex cover, while any two edges share an endpoint. Hence $\tau (K_3)=2$ and $\nu (K_3)=1$. Similarly, the cycle graph $C_5$ has $\tau (C_5)=3$ and $\nu (C_5)=2$. The inequality for the matching number remains valid, but equality can fail.