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In a bipartite graph with parts of sizes $m,n$ and density $\delta >0$, a neighbourhood $V^{\prime }$ of size at least $\delta m/2$ can be chosen so that at least a proportion $1-2ϵ/{\delta }^2$ of its ordered pairs have at least $ϵn$ common neighbours. Choose a random vertex on the other side, use the second moment of its degree, and penalize pairs with few common neighbours. This is a simple dependent random choice tool for controlling restricted sumsets.

For fixed $0<p<1$, the missing common-neighbour count in a binomial random graph has expectation tending to zero. The Markov inequality therefore shows that every pair has a common neighbour with probability tending to one. On that event every graph distance is at most two, so the graph is connected and its graph diameter is at most two.

An edge contraction merges the two endpoints of an existing edge. For a finite simple graph $G$ and $e=uv$, replace $u,v$ by a new vertex $w$. Retain every edge with neither endpoint in $\{u,v\}$, and join $w$ to every member ofHere $N_G(u)$ and $N_G(v)$ denote the original open graph neighbourhoods, and $N_{G/e}(w)$ is the new graph neighbourhood. Remove the self-loop arising from $uv$ and merge duplicate edges, so the result $G/e$ is again a simple graph. This is not deletion of $uv$, which keeps both original vertices.^[ref]

The left example contracts $uv$ in the cycle graph $C_4$ to give $\{wa,ab,bw\}$. Its endpoints have no common neighbours, so four edges become three. The right example contracts $uv$ in the triangle in a graph with edges $uv,ua,va$. Its endpoints have the single common neighbour $a$, so the two edges $ua,va$ become one edge $wa$: three edges become one.

For any such edge contraction, the exact counts areThe contracted edge accounts for one loss. Each common neighbour $z$ contributes exactly one further loss, since $uz,vz$ become a single edge $wz$. All other edges correspond one-to-one to surviving edges. In particular the new degree of a vertex isThese formulas depend on simplifying to a simple graph; a multigraph convention that retains duplicate edges has different counts. In the six-vertex branch set of a graph minor diagram, contracting $12$ loses one edge, contracting the resulting $34$ loses two because of its common neighbour $A$, and contracting $56$ loses one. Hence its seven edges become the three edges of $K_3$: $7-1-2-1=3$.

An edge contraction can increase a degree of a vertex even while decreasing both total counts. For example, contracting $uv$ in the tree with edges $uv,ua,ub,vc,vd$ merges two vertices of degree of a vertex three into one of degree of a vertex four. This is the mechanism behind the distinction between a graph minor and a topological minor.

A fixed positive excess over the Turan theorem threshold forces logarithmic balanced complete multipartite graphs. There is an elementary induction using common neighbourhood from bipartite density: first obtain a logarithmic $r$-partite subgraph from the induction hypothesis, and select disjoint transversal $r$-cliques in it. Each such clique has at least $r\epsilon n$ common neighbours, by the union bound on non-neighbour sets. Apply the bipartite common-neighbour count to these cliques as left-side objects. Their selected union and a large common neighbourhood form the extra part.

The complete bipartite graph $K_{3,3}$ has vertex sets $A=\{a_1,a_2,a_3\}$ and $B=\{b_1,b_2,b_3\}$, with every edge between $A$ and $B$ and none inside either part. Its six vertices support $3\cdot 3=9$ edges and no triangles in a graph: among any three vertices, two belong to the same independent set and have no joining edge.

Add the single edge $a_1{a}_2$. Each $b_j$ is a common neighbour of its endpoints, producing the triangle in a graph $a_1{a}_2{b}_j$. These are exactly the three new triangles in a graph, because every triangle in a graph must use the only edge inside a part. The new count is ten edges; nine was the last possible count without a triangle in a graph on six vertices.

In general, every simple graph with a finite set of $n\ge 0$ vertices that is triangle-free has at mostedges. This is the $r=2$ case of Turán's theorem, with forbidden clique $K_3$. Equality holds exactly for the balanced complete bipartite graph $K_{\lfloor n/2\rfloor ,\lceil n/2\rceil }$, up to graph isomorphism; empty parts are allowed for $n<2$.^[ref]

The floor function gives the exact integer bound. Splitting $n$ vertices into two independent sets of sizes $a$ and $n-a$, and putting in every cross edge, givesThe count is largest when $a$ is an integer nearest $n/2$. For $n=2k$ it is $k^2$; for $n=2k+1$ it is $k(k+1)$. Both equal $\lfloor n^2/4\rfloor$. This proves attainability for every $n$, including the empty graph.

A short proof of the upper bound uses degrees of vertices. In a triangle-free graph, the endpoints $u,v$ of an edge have disjoint vertex neighbourhoods: a common neighbour would complete a triangle in a graph. Thus $d(u)+d(v)\le n$. Summing over edges counts $d(v)$ once for each of the $d(v)$ edges incident to $v$, givingFor $n>0$, the Cauchy-Schwarz inequality and handshaking lemma yieldIf $m>0$, division gives $m\le n^2/4$; $m=0$ is immediate. Since $m$ is an integer, apply the floor function. The case $n=0$ is immediate too. This proves the bound; the full equality characterization follows from Turán's theorem.

The useful reversal is that more than $\lfloor n^2/4\rfloor$ edges force a triangle in a graph, whatever their placement. A global count certifies a local pattern. The extremizer is bipartite, but a triangle-free graph need not be bipartite: a five-vertex graph cycle has five edges, below the bound of six. Historically, Willem Mantel posed the triangle-exclusion question in 1907.^[ref]

If a fixed graph $F$ has chromatic number $r+1$, every extremal $F$-free graph $G$ on $n$ vertices has minimum degree of a graph $(1-1/r+o(1))n$. Use a high-minimum-degree multipartite stability subgraph $H$: replacing any vertex by one adjacent to all but one class of $H$ preserves $F$-freeness. Any supposed new copy of $F$ can replace the new vertex by an unused common neighbour in the omitted class. Extremality therefore gives the lower bound on every degree of a vertex; the Erdős-Stone theorem gives the upper bound on the average degree of a vertex.

Let $X$ count unordered vertex pairs with no common neighbour in a binomial random graph. Each other vertex provides the required pair of edges independently, with success probability $p^2$. A fixed pair has no common neighbour with probability $(1-p^2{)}^{n-2}$. Summing its indicators gives the displayed expectation.

Write $K_s(t)$ for a balanced complete multipartite blow-up with $s$ classes of size $t$. In the nonvacuous range $0<\epsilon <1/r$, the answer isWe prove both bounds, including the quantitative lower bound.

First, suppose a bipartite graph with parts $A,B$, of sizes $m,N$, has at least $pmN$ edges. For any integer $s\le pm/2$, counting pairs consisting of an $s$-subset of $A$ and a common neighbour in $B$ givesThe inequality follows from discrete convexity: $\left(\genfrac{}{}{0ex}{}{x+1}{s}\right)-\left(\genfrac{}{}{0ex}{}{x}{s}\right)=\left(\genfrac{}{}{0ex}{}{x}{s-1}\right)$ is nondecreasing, so balancing integer degrees of vertices minimizes their sum. Consequently some $S$ hasThe product estimate uses $\lfloor pm\rfloor -j\ge pm-s$ for $0\le j<s$. This is a common neighbourhood from bipartite density bound.

We next prove by induction on $q\ge 1$ that, for every fixed $\alpha >0$, a graph $J$ of order $N$ with minimum degree at least $(1-1/q+\alpha )N$ contains $K_{q+1}(\lfloor c\log N\rfloor )$, for some $c=c(q,\alpha )>0$ and all sufficiently large $N$. Impossible minimum-vertex degree parameters need no argument. For $q=1$, take two copies of $V(J)$ with adjacency given by $J$. The preceding count with $p=\alpha$ and $s=\lfloor c\log N\rfloor$, where $c\log (2/\alpha )<1/2$, gives at least $\sqrt{N}$ common neighbours. The selected vertices and their common neighbours are disjoint in $J$, since a vertex is not its own neighbour. Selecting $s$ common neighbours gives $K_2(s)$.

For $q\ge 2$, the minimum degree hypothesis implies the induction hypothesis for $q-1$, for example with excess $1/[q(q-1)]$. Thus $J$ contains $K_q(m)$ with $m=\lfloor a\log N\rfloor$ for a positive constant $a$. Pair the vertices in its classes into $m$ disjoint transversal cliques $C_1,\dots ,C_m$, each of order $q$. By the union bound, every $C_i$ has at leastcommon neighbours. Form an auxiliary bipartite graph between these $m$ cliques and the $N$ vertices, using common-neighbour incidence, and put $p=q\alpha$. Choose $c>0$ small enough that $c<pa/3$ and $c\log (2/p)<1/2$. The count above, with $s=\lfloor c\log N\rfloor$, gives $s$ cliques with at least $\sqrt{N}$ simultaneous common neighbours. Their vertices form $q$ classes of size $s$, and $s$ of those common neighbours form the last class. None of the common neighbours belongs to a selected clique, because that would require a loop. This proves the logarithmic clique blow-up from minimum degree assertion.

To pass from an edge count to minimum degree, put $b=1-1/r+\epsilon$ and $a=b-\epsilon /2$. Repeatedly remove a vertex whose current degree of a vertex is below $a$ times the current order. If the process reaches order $m$, its deleted edges and remaining edges giveThus $(1-a)m^2\ge (\epsilon /2)n^2-O(n)$. In particular, for a fixed sufficiently small $\gamma >0$, the process cannot reach $m=\lfloor \gamma n\rfloor$: the displayed inequality would fail. It stops earlier with a subgraph of order $N\ge \gamma n$ and minimum degree at least $(1-1/r+\epsilon /2)N$. The induction just proved supplies $K_{r+1}(\lfloor c\log N\rfloor )$, hence a lower bound $c^{\prime }\log n$ on $t(r,\epsilon ,n)$. In particular, the guaranteed part size tends to infinity.

For the upper bound, choose a fixed $p$ with $b<p<1$ and take a binomial random graph $G(n,p)$. Its edge count has expectation $p\left(\genfrac{}{}{0ex}{}{n}{2}\right)$ and variance $p(1-p)\left(\genfrac{}{}{0ex}{}{n}{2}\right)$. The Chebyshev inequality shows that $e(G)\ge b\left(\genfrac{}{}{0ex}{}{n}{2}\right)$ with probability tending to one. The expected number of labeled copies of $K_{r+1}(t)$ is at mostFor $t=\lceil C\log n\rceil$ and $C>2/[r\log (1/p)]$, this tends to zero. The Markov inequality therefore shows that with positive probability both the required edge density holds and there is no such copy. This proves $t(r,\epsilon ,n)=O(\log n)$ and completes the random obstruction to larger clique blow-ups argument.

There is a necessary qualification to the density parameter. If $\epsilon =1/r$, the only eligible graph is the complete graph, and $t(r,1/r,n)=\lfloor n/(r+1)\rfloor$. If $\epsilon >1/r$ and $n\ge 2$, there are no eligible simple graphs; the universal assertion is vacuous for every $t$, so the printed maximum has no finite value in that range.

Write $K_j(t)$ for a balanced complete multipartite blow-up, with $j$ parts each containing $t$ vertices. Its occurrence is a subgraph condition, so additional internal edges in the host are harmless. The coefficient multiplying $\log n$ is essential: the PDF has $t=\lfloor d\log n\rfloor$, although it is lost in the converted TeX.

First prove the common neighbourhood from bipartite density estimate. Suppose a bipartite graph has parts of sizes $m,N$ and at least $\beta mN$ edges. For an integer $s\le \beta m/2$, count incidences between $s$-subsets of the first part and their common neighbours in the second. The discrete convexity of $k\mapsto \left(\genfrac{}{}{0ex}{}{k}{s}\right)$, with value zero for $k<s$, givesThe convexity assertion follows directly from $\left(\genfrac{}{}{0ex}{}{k+1}{s}\right)-\left(\genfrac{}{}{0ex}{}{k}{s}\right)=\left(\genfrac{}{}{0ex}{}{k}{s-1}\right)$, which is increasing in $k$; smoothing two unequal degrees cannot increase the sum. In the binomial ratio every factor is at least $\beta /2$, because $\lfloor \beta m\rfloor -s+1\ge \beta m-s\ge \beta m/2$. Consequently some $S$ satisfies

We prove the logarithmic clique blow-up from minimum degree by induction on $r$. When $\epsilon \ge 1/r$, the degree hypothesis is impossible for a loopless graph, so any positive $d$ works vacuously. Assume $0<\epsilon <1/r$. For $r=1$, take two copies of the vertex set and join the copies of adjacent vertices. This bipartite graph has edge density of a bipartite graph at least $\epsilon$. ChooseFor sufficiently large $n$, $t=\lfloor d\log n\rfloor \le \epsilon n/2$, and the estimate supplies at least $\sqrt{n}$ common neighbours. Choose $t$ of them. The two selected sets are disjoint in the original graph, since a selected vertex cannot be adjacent to itself. They give $K_2(t)$.

For $r\ge 2$, put ${\epsilon }^{\prime }=\epsilon +1/(r-1)-1/r$. The same minimum degree of a graph exceeds $(1-1/(r-1)+{\epsilon }^{\prime })n$. By induction there is a $K_r(m)$ with $m=\lfloor d^{\prime }\log n\rfloor$, where $d^{\prime }=d(r-1,{\epsilon }^{\prime })>0$. Pair the vertices of its $r$ parts into $m$ disjoint transversal cliques $C_1,\dots ,C_m$. Each has at leastcommon neighbours, by bounding the union of the non-neighbour sets of its $r$ vertices. Set $\beta =\min \{r\epsilon ,1/2\}$. Form the bipartite graph whose first part is these $m$ cliques, with $C_i$ joined to a vertex when that vertex is a common neighbour of all of $C_i$. It has density at least $\beta$. ChooseFor large $n$, $m\ge d^{\prime }\log n/2$ and $t=\lfloor d\log n\rfloor \le \beta m/2$. The estimate gives $t$ selected cliques and at least $\sqrt{n}\ge t$ common vertices. The selected cliques supply $t$ vertices in each of the original $r$ parts, and their common vertices supply the final part. No common vertex belongs to a selected clique, again because there are no loops. All required cross-part edges are present. Increasing $n_0(r,\epsilon )$ to satisfy these finitely many inequalities completes the induction:

The Erdős-Stone theorem states that for a fixed graph $H$ with chromatic number $r+1\ge 2$,The lower bound comes from the Turán graph $T_r(n)$, which cannot contain an $(r+1)$-chromatic subgraph. To obtain the upper bound from our minimum-degree result, suppose $e(G)\ge (a+\eta )n^2/2$, where $a=1-1/r$ and $0<\eta <1-a$. Repeatedly delete a vertex of degree less than $b$ times the current order, where $b=a+\eta /2$, until no such vertex remains. If the remaining order is $m$, thenThus $m\ge c_{\eta }n$ for large $n$, with $c_{\eta }>0$, and the remaining subgraph has minimum degree of a graph at least $(a+\eta /2)m$. It contains $K_{r+1}(\lfloor d\log m\rfloor )$. A proper graph colouring of $H$ places its vertices in the $r+1$ parts once their size exceeds $|V(H)|$. This contradicts $H$-freeness. Adjusting a fixed positive density margin absorbs the difference between $n^2/2$ and $\left(\genfrac{}{}{0ex}{}{n}{2}\right)$, proving the upper bound.

The six-vertex forbidden graph is the octahedral graph $K_{2,2,2}$: the deleted matching in a graph gives its three independent pairs. Its chromatic number is three, soThe printed notation uses $H$ for the extremal-number argument while its defining condition forbids $F$; the answer uses that explicitly defined forbidden graph. For the strict finite inequality, take $T_2(n)$ and add one edge inside its larger part, which has at least two vertices for $n\ge 3$. Every triangle in a graph then uses this added edge. However, $K_{2,2,2}$ contains two vertex-disjoint triangles in a graph, obtained by taking one vertex from each pair and then the other three. It therefore cannot occur in the constructed graph. Hence

If $X=0$, every pair of vertices has a common neighbour, so every pair has graph distance at most two. In particular the graph is connected and its graph diameter is at most two. By the Markov inequality and part (ii),We include disconnected graphs among those with diameter greater than two. Thereforeby diameter bound for a fixed-density binomial random graph.

Let $I_{ij}$ be the indicator random variable that the unordered vertex pair $\{i,j\}$ has no common neighbour. For each of the other $n-2$ vertices, the two required edges are both present with probability $p^2$. The edge pairs for different candidate neighbours are disjoint sets of independent random choices. Thus $\mathbb{E}{I}_{ij}=(1-p^2{)}^{n-2}$. Linearity of expectation yieldsthe missing common-neighbour count in a binomial random graph.

For a finite nonempty set $A$, its additive energy iswhere $r_{A+A}(s)$ counts ordered representations. Since ${\sum }_s{r}_{A+A}(s)=|A{|}^2$, Cauchy-Schwarz givesThus $|A+A|\le K|A|$ implies $E(A,A)\ge |A{|}^3/K$: a small doubling constant forces many additive quadruples.

A polynomial form of the Balog-Szemerédi-Gowers theorem gives the converse after passing to a subset. There are absolute constants $c,C>0$ such that if $E(A,A)\ge \eta |A{|}^3$, $0<\eta \le 1$, then some $A^{\prime }\subseteq A$ satisfiesThe exponent and constants here need not be optimal.

Precisely, a graph form of the Balog-Szemerédi-Gowers theorem states the following. If $A,B$ are finite sets of size $n$ in an abelian group, $\Gamma \subseteq A\times B$ has at least $\delta n^2$ edges, and its restricted sumsethas size at most $Kn$, then there are $A^{\prime }\subseteq A$, $B^{\prime }\subseteq B$ with $|A^{\prime }|,|B^{\prime }|\ge c{\delta }^{C}n$ andThese are uniform absolute constants, valid for $0<\delta \le 1$ and $K\ge 1$.

To apply this theorem to additive energy, let $n=|A|$ and retain the sums with $r_{A+A}(s)\ge \eta n/2$. The discarded sums contribute at most $(\eta n/2){\sum }_{s}r(s)=\eta n^3/2$ to the additive energy. Since $r(s)\le n$, the retained pairs number at least $\eta n^2/2$. There are at most $2n/\eta$ retained sums. They therefore define a bipartite graph of density at least $\eta /2$ with restricted sumset size at most $2n/\eta$. The graph theorem supplies large subsets $A^{\prime },B^{\prime }$ with polynomially bounded $|A^{\prime }+B^{\prime }|$.

For completeness, turn this cross-sumset bound into a doubling constant bound. The Ruzsa triangle inequality gives $|A^{\prime }-A^{\prime }|\le |A^{\prime }+B^{\prime }{|}^2/|B^{\prime }|$. If $D=|A^{\prime }-A^{\prime }|/|A^{\prime }|$, the Plünnecke inequality, applied to the pair $A^{\prime },-A^{\prime }$, gives $|A^{\prime }+A^{\prime }|\le D^2|A^{\prime }|$. The minimal-growth proof below in Question 5 applies to arbitrary finite pairs and proves this particular expansion estimate as well. All losses are fixed powers of ${\eta }^{-1}$, proving the displayed converse after increasing $C$.

The requested dense bipartite common-neighbour lemma is a dependent random choice assertion. Call an ordered pair in $V^2$ bad when it has fewer than $ϵn$ common neighbours. Choose $w\in W$ uniformly, and put $S=N(w)\subseteq V$. ThenFor each bad pair, the probability that both endpoints lie in $S$ is its number of common neighbours divided by $n$, which is less than $ϵ$. Thus the expected number $b(S)$ of bad ordered pairs in $S^2$ is at most $ϵm^2$. ConsequentlyChoose a neighbourhood $V^{\prime }=S$ attaining at least this expectation. It has $|V^{\prime }|\ge \delta m/\sqrt{2}\ge \delta m/2$, andHence at least the proportion $1-2ϵ/{\delta }^2$ of its ordered pairs have at least $ϵn$ two-edge connections. As usual these connections are counted by common neighbours, including a return walk for a diagonal ordered pair; assume $\delta >0$, as the formula requires.

The relevance to the graph theorem is that many two-edge connections turn a sparse collection of permitted sums into additive control on a large vertex subset. On a connection $a\to b\to a^{\prime }$, $a-a^{\prime }=(a+b)-(a^{\prime }+b)$ expresses a difference using two elements of the restricted sumset. The abundance of connections, followed by standard cleaning and further path counting, bounds the number of differences without throwing away most vertices. This is the role of dependent random choice in obtaining polynomial losses in the graph form of the Balog-Szemerédi-Gowers theorem.

The Erdős-Stone theorem says that, for a fixed graph $F$ with chromatic number $q\ge 2$,The lower bound comes from the balanced Turán graph with $q-1$ parts; the theorem supplies the matching asymptotic upper bound. Here and below, all forbidden graphs and blow-up parameters are fixed as $n\to \infty$.

First obtain an almost spanning, almost complete multipartite core. Put ${\alpha }_r=1-1/r$. We give the stability argument, rather than infer pointwise degree bounds by differentiating an asymptotic edge-count formula. Suppose first $r\ge 2$.

We need two elementary ingredients. First, positive homomorphism density of $K_{r+1}$ forces a fixed complete multipartite graph $K_{r+1}(t)$. To see this, perform vertex cloning in a graph, replacing one vertex by $t$ independent twins. Conditional on the images of the other vertices, its contribution to the homomorphism density changes from a number $p$ to $p^t$; Jensen inequality gives $\mathbb{E}{p}^t\ge (\mathbb{E}p{)}^t$. Duplicating each original vertex therefore givesA positive lower bound on the right supplies a positive proportion of all maps of the blow-up. Only $O(n^{(r+1)t-1})$ maps fail to be injective, so for large $n$ at least one map is an embedding. Consequently a $K_{r+1}(t)$-free sequence has $o(n^{r+1})$ copies of $K_{r+1}$. The clique removal lemma, proved in the next solution, then deletes $o(n^2)$ edges to give a $K_{r+1}$-free graph $J_n$ with $e(J_n)={\alpha }_r{n}^2/2-o(n^2)$.

Second, we prove the required stability for $K_{r+1}$-free graphs by induction on $r$. For $r=1$ such a graph is edgeless. In an $m$-vertex $K_{r+1}$-free graph $J$, take a vertex of maximum vertex degree $D$, put $A=N(v)$ and $B=V(J)\setminus A$, and note that $J[A]$ is $K_r$-free. The Turan theorem and the maximum-degree bound giveIf $e(J)={\alpha }_r{m}^2/2-o(m^2)$, both nonnegative error terms are $o(m^2)$: $D={\alpha }_{r}m+o(m)$ and $e(J[B])=o(m^2)$. The deficit in the bound for $e(J[A])$ is likewise $o(m^2)$. Induction partitions $A$ into $r-1$ classes with a total of $o(m^2)$ internal edges; adjoining $B$ gives an $r$-class partition with the same property. Applying this to $J_n$ and restoring the removed edges gives such a partition $V_1,\dots ,V_r$ of $G_n$.

The number of possible crossing edges is $\frac{1}{2}(n^2-{\sum }_i|V_i{|}^2)\le {\alpha }_r{n}^2/2$. Since the actual crossing-edge count is within $o(n^2)$ of this maximum, $|V_i|=n/r+o(n)$ for every $i$, and there are $o(n^2)$ missing crossing edges. Choose $a_n\to 0$ so slowly that the number of vertices missing more than $a_{n}n$ neighbours in other classes is $o(n)$. Delete those vertices and all internal edges. The remaining r-partite graph $Q_n$ has $n-o(n)$ vertices and every vertex has crossing vertex degree at least ${\alpha }_{r}n-o(n)$. The Turan theorem, or the size of a largest part, supplies the matching upper bound for its minimum vertex degree. ThusThis is a high-minimum-degree multipartite stability subgraph. The subgraph need not be spanning; deleting the exceptional $o(n)$ vertices is essential. For $r=1$, the spanning edgeless subgraph already proves the assertion.

Extremality forces the minimum degree. Choose $t\ge |V(F)|$. A proper $(r+1)$-graph colouring embeds $F$ in $K_{r+1}(t)$, so every $F$-free $H_n$ is also $K_{r+1}(t)$-free. By the Erdős-Stone theorem, its extremal edge count has the needed asymptotic size. The preceding proof supplies core classes $W_1,\dots ,W_r$ of size $n/r+o(n)$ in which every vertex misses only $o(n)$ crossing neighbours, uniformly over the core.

Delete an arbitrary vertex $x$ from $H_n$ and introduce a new vertex $z$ adjacent precisely to $W_2\cup \cdots \cup W_r$ with $x$ removed if necessary. The new graph is still $F$-free. Indeed any new copy would use $z$, all its neighbours in that copy would be in the specified core classes, and their set of common neighbours in $W_1$ has size $n/r-o(n)$. A vertex of this common neighbourhood outside the bounded vertex set of the copy replaces $z$, producing an existing copy of $F$ in $H_n$, a contradiction. For $r=1$ the new vertex is isolated and the same conclusion is immediate.

The replacement adds ${\alpha }_{r}n-o(n)$ edges. Since $H_n$ has the maximum possible number of edges, $d_{H_n}(x)\ge {\alpha }_{r}n-o(n)$. As $x$ was arbitrary and the minimum vertex degree is at most the average vertex degree,This proves the minimum degree of an extremal forbidden-subgraph graph. The replacement argument avoids the invalid implication $\mathrm{ex}(n,F)-\mathrm{ex}(n-1,F)={\alpha }_{r}n+o(n)$ based solely on the asymptotic formula.

A colour-critical vertex also bounds the maximum degree. Suppose a vertex $x$ of $H_n$ has $d(x)\ge {\alpha }_{r}n+\epsilon n$ for some fixed $\epsilon >0$. Since the core omits only $o(n)$ vertices and all its classes have size $n/r+o(n)$, $x$ has at least $\epsilon n-o(n)$ neighbours in each $W_i$. Otherwise, even counting every vertex in all other classes and outside the core would give too small a vertex degree.

Inside these $r$ neighbourhood sets, greedily choose a fixed number $t\ge |V(F)|$ of vertices in each class. Every previously chosen vertex excludes only $o(n)$ crossing nonneighbours, so each next candidate set still has positive linear size. This produces $K_r(t)$ inside $N(x)$. A proper $r$-graph colouring of $F-v$ embeds it in that complete multipartite graph; map $v$ to $x$. All required incident edges exist, so this embeds $F$, a contradiction. The case $r=1$ simply uses enough neighbours to embed the edgeless $F-v$. Hence $\Delta (H_n)\le {\alpha }_{r}n+o(n)$, and the average-degree lower bound completes the answer:

For the Petersen graph, each vertex has three neighbours, adjacent vertices have no common neighbour, and distinct nonadjacent vertices have exactly one common neighbour. The entries of $A^2$ count length-two walks, so diagonal entries are three, adjacent entries zero, and other off-diagonal entries one. HenceThe connected graph has the simple eigenvalue three with eigenvector $1$. On its orthogonal complement $J=0$, so the remaining eigenvalues satisfy ${\lambda }^2+\lambda -2=0$ and are one or minus two. If their multiplicities are $r,s$, then $r+s=9$ and $\mathrm{tr}A=3+r-2s=0$. Thus

Use natural logarithms. A $K_t$ graph minor is represented by $t$ disjoint nonempty branch sets of a graph minor, each inducing a connected graph, with an edge between every pair. The complete graph minor density threshold is defined over nonempty finite graphs byIt uses $e(G)/|G|$, half the average degree of a vertex; the nonempty convention excludes the vacuous density inequality for the empty graph. The PDF has the intended definition with a universal implication over $G$; the TeX transcription corrupts that definition.

Probabilistic lower bound. Put $N=\lfloor t\sqrt{\log t}/4\rfloor$ and take the binomial random graph $G(N,1/2)$. Its edge count has mean $N(N-1)/4$. The Chernoff bound impliesWe show that the probability of a $K_t$ graph minor tends to zero. Ignore connectedness, which only enlarges the set of possible models, and assign each of the $N$ vertices one of $t$ branch labels or an unused label. There are at most $(t+1{)}^N$ assignments.

For any assignment with $t$ nonempty branch sets, at least $t/2$ of them have size at most $2N/t\le \sqrt{\log t}/2$. Between any two such small sets $A,B$, the probability of no edge isThe absence or presence of edges between different pairs of branch sets depends on disjoint sets of random edges, so these events are independent. For this assignment the probability that all small pairs are adjacent is at mostThe union bound over assignments is therefore at mostsince the positive term is $O(t(\log t{)}^{3/2})$ and the negative term has order $t^{7/4}$. There is consequently a graph with no $K_t$ graph minor and with $e(G)/N\ge N/8$. Any constant having the universal forcing property must exceed this ratio. Since $N/8\ge t\sqrt{\log t}/64$ for large $t$,

The auxiliary density lemma contains a typo. Both the original PDF and the TeX print $e(G)\le 11k|G|$ in the hint. This cannot imply its conclusion: for $k\ge 1$, an edgeless graph has only edgeless graph minors, and none satisfies $2\delta (H)\ge |H|+4k-1$. We use the intended dense minor with bounded order and high minimum degree lemma with the hypothesis $e(G)\ge 11k|G|$ for nonempty $G$. The upper-bound argument below depends on that corrected supplied lemma; the literal printed hint is false.

Probabilistic upper bound and the constant seven. Suppose $G$ is nonempty and $e(G)\ge 7t\sqrt{\log t}|G|$, and setThe corrected lemma gives a graph minor $H$ of order $N\le 11k+2$ with $2\delta (H)\ge N+4k-1$. Since $\delta (H)\le N-1$, we also have $N\ge 4k+1$. For large $k$, every vertex has at most $N/3$ nonneighbours, counting itself, becausethe last inequality uses $N\le 11k+2\le 12k-3$. Moreover any two distinct vertices have at leastcommon neighbours.

Choose $2t$ disjoint random $\ell$-sets $A_1,\dots ,A_{2t}$ from $V(H)$, uniformly, which is possible since $2t\ell <4k-1\le N$ for sufficiently large $t$. For a set $A$, let $U(A)$ be the set of vertices having no neighbour in $A$. For each vertex, the probability that all members of a uniformly sampled $\ell$-set are its nonneighbours is at most $3^{-\ell }$, even when sampling without replacement. By linearity of expected value,Call $A$ good if $|U(A)|\le N{3}^{-19\ell /20}$. The Markov inequality shows that a random set is bad with probability at most $3^{-\ell /20}=o(1)$. Thus the expected number of bad sets among our $2t$ samples is $o(t)$.

Conditional on a fixed good $A_i$, the marginal distribution of $A_j$ is uniform among $\ell$-sets outside $A_i$. For there to be no edge between them, all its members must lie in $U(A_i)$. HenceHere $(N/(N-\ell ){)}^{\ell }=\exp (O({\ell }^2/N))=1+o(1)$. Consequently the expected number of nonadjacent pairs of good sets is at mostsince $(19/20)\log 3>1$. Applying the Markov inequality to both counts shows that there exists a choice with fewer than $t$ bad sets and at most $t$ nonadjacent pairs of good sets. Select $t$ of the good sets; they still have at most $t$ missing adjacencies.

Make each selected set connected by fixing one of its vertices as a root and, for each of its other members, adding one unused common neighbour of that member and the root. This uses at most $t(\ell -1)$ additional vertices. Then for each pair with no original edge, choose one vertex in each set and add an unused common neighbour to one of the sets. The added vertex is joined to that set and to the other set, so it preserves connectedness and repairs their adjacency. At most $t$ such repairs are required.

Throughout this process the total number of occupied vertices is at mostSince every pair has at least $4k-1$ common neighbours, an unused choice always exists. The final sets are disjoint connected branch sets of a graph minor with every pair adjacent. They represent $K_t$ in $H$, and hence in $G$, by transitivity of graph minors. This random branch-set construction of a complete graph minor proves

The sharp linear threshold for a four-vertex complete minor. We prove by induction that a graph on $n\ge 4$ vertices with at least $2n-2$ edges has a $K_4$ graph minor. The case $n=4$ is $K_4$ itself. If some edge $uv$ has at most one common neighbour, an edge contraction reduces the order by one and removes exactly $1+|N(u)\cap N(v)|\le 2$ edges. The contracted graph has at least $2(n-1)-2$ edges, so induction applies.

Otherwise every edge is in at least two triangles in a graph. Choose a vertex $v$ incident with an edge. Each vertex $u\in N(v)$ has at least two neighbours of a vertex in $N(v)$, since these are the common neighbours of $u,v$. Thus $G[N(v)]$ has minimum degree of a graph at least two. A longest path in this finite graph has an endpoint adjacent to an earlier nonconsecutive path vertex, and hence contains a cycle in a graph. Together with $v$, this cycle in a graph gives a wheel graph as a subgraph. Divide its rim into three consecutive nonempty connected arcs; these arcs and $\{v\}$ form four pairwise adjacent branch sets of a graph minor. Therefore

With $2n-3$ edges the answer is no. Take the join of graphs of $K_2$ and an independent set of $n-2$ vertices. It has $1+2(n-2)=2n-3$ edges. Among four disjoint putative branch sets of a graph minor, at most two can contain the two vertices of $K_2$. Any connected branch set avoiding them is a singleton in the independent set. At least two such singleton sets would therefore have no edge between them. This excludes a $K_4$ graph minor for every $n\ge 4$ and proves sharpness.

In a dense graph with many common neighbours for every pair of vertices, choose disjoint random small sets. A set is good if few vertices have no neighbour in it. The Markov inequality controls the number of bad sets, and random sampling makes almost every pair of good sets adjacent. Add unused common neighbours to connect each set and to repair the remaining missing adjacencies. If the number of used vertices stays below every common-neighbour count, this constructs disjoint branch sets of a graph minor representing a large complete graph.