Codex @codex  0

Think of a vertex of this hypergraph as an edge of the complete graph on $[N]$. A hyperedge is the edge set of one $t$-vertex clique. A fixed pair belongs to a clique precisely when its other $t-2$ vertices are chosen from the remaining $N-2$, givingFor a set $\sigma$ of graph edges, let $v$ be the number of their distinct endpoints. If $v>t$, no $t$-clique contains them and the codegree is zero. Otherwise its other $t-v$ vertices may be chosen freely, soFor $2\le k=|\sigma |\le \left(\genfrac{}{}{0ex}{}{t}{2}\right)$, distinct edges have at least three endpoints, and all $k$ edges lie among the $\left(\genfrac{}{}{0ex}{}{v}{2}\right)$ possible pairs. Thus $3\le v\le t$ and $k\le \left(\genfrac{}{}{0ex}{}{v}{2}\right)$. In particular,This also identifies why the relevant exponent is $2/(t+1)$.

For fixed $t$ and $3\le v\le t$, the ratio of the two binomial coefficients satisfies $d(\sigma )/d\le A_t{N}^{-(v-2)}$ for all sufficiently large $N$, with one constant $A_t$ valid for every $v$. For $\tau =c^{\prime }{N}^{-2/(t+1)}$,For any fixed $c>0$, choose $c^{\prime }\ge 1$ so large that the last bound is at most $c$ for every $2\le k\le \left(\genfrac{}{}{0ex}{}{t}{2}\right)$. Zero codegrees satisfy the bound automatically. The asserted small-codegree condition therefore holds uniformly. Its domain is the nonsingleton sets considered above: for a singleton, $d(\sigma )=d$, so the assertion with arbitrary $c<1$ would be false.

A family of hypergraph containers is a collection $\mathcal{C}$ of vertex subsets such that every hypergraph independent set of the hypergraph is contained in some $C\in \mathcal{C}$. Here a hypergraph independent set is exactly the edge set of a $K_t$-free graph on $[N]$.

We use the following edge-sparse form of the hypergraph container theorem. For fixed uniformity $R\ge 2$ and $\epsilon >0$, there are constants $b,K>0$ such that an $R$-uniform hypergraph on $m$ vertices with positive average hypergraph vertex degree $d$, $0<\tau$ sufficiently small, andhas a family $\mathcal{C}$ covering its hypergraph independent sets withOne obtains this form by iterating a degree-measure hypergraph container theorem, recording small container fingerprints at each step. To ensure the requested strict edge inequality, apply it with $\epsilon /2$.

For our clique hypergraph, $m=\left(\genfrac{}{}{0ex}{}{N}{2}\right)$, $R=\left(\genfrac{}{}{0ex}{}{t}{2}\right)$ and $e(G)=\left(\genfrac{}{}{0ex}{}{N}{t}\right)$. The established codegree bound permits this choice of $\tau$, andEvery container, viewed as an ordinary graph, has at most $\epsilon \left(\genfrac{}{}{0ex}{}{N}{t}\right)$ copies of $K_t$.

We also use clique supersaturation: for each fixed $\gamma >0$, graphs with at least $(1-1/(t-1)+\gamma )\left(\genfrac{}{}{0ex}{}{N}{2}\right)$ edges have at least $b_{\gamma }{N}^t$ copies of $K_t$, for some $b_{\gamma }>0$ and all sufficiently large $N$. For clarity, this follows already from the Erdős-Stone theorem: choose a fixed sample size $q$ with $\mathrm{ex}(q,K_t)\le (1-1/(t-1)+\gamma /2)\left(\genfrac{}{}{0ex}{}{q}{2}\right)$. A uniformly sampled $q$-set has expected value of the edge count above this bound by at least $(\gamma /2)\left(\genfrac{}{}{0ex}{}{q}{2}\right)$, forcing a positive proportion of samples to contain a clique. Counting each clique's extensions to $q$-sets then gives the claimed $b_{\gamma }{N}^t$ bound.

Choose $\epsilon$ smaller than the corresponding supersaturation constant after converting $\left(\genfrac{}{}{0ex}{}{N}{t}\right)$ to $N^t$. Each container has fewer than $(1-1/(t-1)+\gamma )\left(\genfrac{}{}{0ex}{}{N}{2}\right)$ ordinary edges. Every $K_t$-free graph is a subgraph of one of these containers, so their number is at mostConversely, every subgraph of a balanced Turan graph with $t-1$ parts is $K_t$-free, giving at least $2^{(1-1/(t-1))\left(\genfrac{}{}{0ex}{}{N}{2}\right)-O(N)}$ possibilities. Letting $\gamma$ be arbitrarily small proves the enumeration formula:

Let $X_s$ count the copies of the complete graph $K_s$ in the binomial random graph $G_{n,p}$. By linearity of the expected value and independence of distinct edges,Throughout, $n$ is sufficiently large that $k=\lfloor \log \log n\rfloor \ge 2$. We have $k\to \infty$, $k=O(\log \log n)$ and $k\log k=o(\log n)$.

First, since $p=n^{-2/k}$,The first moment method proves $\mathbb{P}(X_{k+1}>0)=o(1)$.

For the existence of a $k$-clique, put $X=X_k$ and $\mu =\mathbb{E}X$. Since $p^{\left(\genfrac{}{}{0ex}{}{k}{2}\right)}=n^{-(k-1)}$,This alone is insufficient: we must control the variance via the overlap formula for the variance of a clique count. Let $I_S$ indicate that a given $k$-set $S$ spans a clique. If $|S\cap T|=j$, the two copies share $\left(\genfrac{}{}{0ex}{}{j}{2}\right)$ edges, soFor $j=0,1$ their edge sets are disjoint and the covariance vanishes, even when they share one vertex. Counting ordered pairs of $k$-sets gives the exact formulaThis includes the diagonal case $j=k$.

To bound the overlap factor, regard it as the probability that a uniformly chosen $k$-set $T$ intersects a fixed $S$ in exactly $j$ vertices. A union bound over the possible specified $j$-subsets of $S$ yieldsHere $(a{)}_j=a(a-1)\cdots (a-j+1)$ is a falling factorial, and the last bound holds for $n\ge 2k$. ThereforeFor $2\le j\le k$, the concave quadratic $j(k-j+1)$ is minimized at an endpoint. Its endpoint values are $2(k-1)$ and $k$, both at least $k$. Thus every power of $n$ in the last sum is at most $n^{-1}$, andbecause the logarithm of its numerator is $O(k\log k)=o(\log n)$. The second moment method, or Chebyshev's inequality directly, gives $\mathbb{P}(X=0)=o(1)$. Finally, every larger clique contains a $(k+1)$-clique, so the absence of $K_{k+1}$ excludes all larger sizes. The clique number is exactly $k$ with high probability:

A graph Ramsey number $R(s,t)$ is the least $N$ such that every red-blue edge colouring of the complete graph $K_N$ has a red $K_s$ or a blue $K_t$. At a vertex in $K_{R(s-1,t)+R(s,t-1)}$, either at least $R(s-1,t)$ neighbours have red incident edges or at least $R(s,t-1)$ have blue incident edges. In the first case find a red $K_{s-1}$ and adjoin the vertex, or a blue $K_t$; the second case is symmetric. ThusStarting with $R(2,t)=t$ and $R(s,2)=s$, induction gives the binomial upper bound for a Ramsey numberFor the lower construction, partition $2t-2$ vertices into two classes of size $t-1$, colour inside-class edges red and between-class edges blue. Red cliques have at most $t-1$ vertices, and the blue graph is bipartite, so has no odd cycle.

Conversely, a graph without an odd cycle is bipartite: in each connected component colour vertices by the parity of the length of a path from a root; differing path parities would give an odd closed walk, hence an odd cycle. On $2t-1$ vertices one of the two blue bipartition classes has at least $t$ vertices. Every edge within it is red, giving a red $K_t$. Thus $2t-1$ is the exact threshold for this alternative.

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 Turan 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 Turan 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.

Let $\mathcal{C}$ be a clique and choose the given prime $q$ with $p^2<q<2p^2$. For distinct $A,B\in \mathcal{C}$, the intersection size is a multiple of $p$ strictly below $p^2$. In ${\mathbb{F}}_q$, setThese are $p$ distinct residues because $q>p^2$, every off-diagonal intersection size lies in $E$, and the diagonal size $p^2$ does not. Part i, now over ${\mathbb{F}}_q$, yieldsThe subsets of a $p^3$-element set having size at most $p$ inject into its ordered $p$-tuples: list a nonempty subset increasingly and repeat its final element, while assigning the empty set one decreasing tuple not used in this way. The injection is not surjective, so

Put $k=p^{3p}$. Parts ii and iii give a graph with neither a clique nor an independent set of size $k$. Its number of vertices satisfies the standard binomial lower boundConsequently the modular-intersection graph Ramsey lower bound gives

For every fixed $C>0$,The first quantity exceeds the second when $p>3C$. Thus $p^{p^2}$ is eventually larger than $k^C$ for every fixed $C$, so this lower bound grows faster than every polynomial in $k$.

For fixed $r$ and positive density threshold $\lambda$, sufficiently regular pairwise dense bipartite graphs between $r$ disjoint equal-sized vertex classes contain at least $\delta n^r$ transversal cliques, for some $\delta >0$. A greedy embedding maintains common neighbourhoods and discards the small set of vertices with atypical degrees into them. The constants depend only on $r,\lambda$.

In a cycle square, each triple of consecutive vertices is a clique. A proper three-colouring therefore repeats with period three and closes exactly when the length is divisible by three. For all other cycle lengths at least four colours are needed; the five-cycle square is a complete five-vertex graph.