A Riemannian isometry $F:(M,g)\to (N,h)$ is a diffeomorphism satisfying $F^{\ast }h=g$. A local isometry is a local diffeomorphism with the same pullback identity; equivalently $d{F}_p$ is an isometric linear isomorphism for every $p$. An isometric immersion into a higher-dimensional manifold does not satisfy this local-diffeomorphism requirement.

Let ${\varphi }_t$ be the local flow of the generating vector field $K$. The identity ${\varphi }_t^{\ast }g=g$ differentiates to ${\mathcal{L}}_{K}g=0$, where $\mathcal{L}$ is the Lie derivative of a tensor field. For arbitrary vector fields $X,Y$, metric compatibility and the torsion-free connection giveThis proves the Killing equation. Conversely, a smooth Killing field has a local flow, andSince ${\varphi }_0$ is the identity, ${\varphi }_t^{\ast }g=g$ wherever the flow is defined. Its inverse is ${\varphi }_{-t}$ locally, so the local flow consists of local isometries. Neither direction assumes that $K$ is complete.

Put $H(X,Y)={\nabla }_X({\nabla }_{Y}K)-{\nabla }_{{\nabla }_{X}Y}K$ and $B(X,Y,Z)=⟨H(X,Y),Z⟩$. These expressions are tensorial in $X,Y,Z$. Take the covariant derivative in direction $X$ of the Killing equation, subtracting the terms from differentiating $Y$ and $Z$. It follows thatWith the curvature convention $\mathcal{R}$ of Solution 1, the torsion-free connection also givesDefine $C(X,Y,Z)=⟨\mathcal{R}(X,K)Y,Z⟩$. It is skew in $Y,Z$ by skew-adjointness of the Riemann curvature tensor. The first Bianchi identity givesso $C$ has the same antisymmetrization in $X,Y$ as $B$. Consequently $D=B-C$ is symmetric in its first two slots and skew in its last two. These symmetries force it to vanish:We have proved the second covariant derivative of a Killing vector identity, including its sign:The printed identity uses the opposite curvature-sign convention in Killing derivative identities. If $R=-\mathcal{R}$, namely $R(X,Y)Z={\nabla }_Y{\nabla }_{X}Z-{\nabla }_X{\nabla }_{Y}Z+{\nabla }_{[X,Y]}Z$, the same result reads ${\nabla }_{X,Y}^{2}K=R(K,X)Y$, exactly as printed. The convention must change with the sign; under $\mathcal{R}$, writing $\mathcal{R}(K,X)Y$ would be incorrect.

Finally let $H_0=K-\tilde{K}$ have zero value and zero first covariant derivative at $p$. Along any geodesic issuing from $p$, the identity just proved saysThus $H_0$ is a Jacobi field with zero initial value and derivative. Uniqueness for this linear ordinary differential equation implies $H_0=0$ on each such geodesic, hence on a convex normal neighborhood of $p$. Consider the set of points where both $H_0$ and $\nabla H_0$ vanish. It is closed by continuity and open by this same local argument; on the resulting neighborhood $H_0$ vanishes identically, so its derivative does too. It is nonempty, and $M$ is connected, therefore it is all of $M$. This proves $K=\tilde{K}$ everywhere and the general statement that a Killing field is determined by its value and first covariant derivative.

Use the Levi-Civita connection and the Riemann curvature tensor conventionfor orthonormal $T,E$. Thus the round sphere has positive sectional curvature. Work on a fixed compact parameter interval $[a,b]$ inside the given open interval; this keeps all differentiations and endpoint evaluations well-defined. The base geodesic is regular and has constant speed, so a constant rescaling of $t$ makes it unit-speed. Put $T={\partial }_t\varphi$, $J={\partial }_s\varphi$, $D_t={\nabla }_T$, $D_s={\nabla }_J$ and evaluate at $s=0$. The torsion-free connection gives $D_{s}T=D_{t}J$ because the two parameter derivatives commute. The geodesic equation is $D_{t}T=0$.

Differentiating the length of a curve once and twice, using metric compatibility, givesandLet $A=D_{s}J$. The curvature commutator gives $D_s{D}_{t}J=D_{t}A+\mathcal{R}(J,T)J$, and the skew-adjoint curvature symmetry gives $⟨\mathcal{R}(J,T)J,T⟩=-⟨\mathcal{R}(J,T)T,J⟩$. Integration by parts therefore proves the moving-endpoint second variation of Riemannian arc length:Equivalently, with $W=J-⟨J,T⟩T$, the integral is $I(W,W)$, the Riemannian index form. The endpoints of this geodesic variation generally move, so the displayed boundary term must be retained. For a base speed $c$ instead of one, the boundary and integral have an overall factor $1/c$, and the subtracted square inside the integral is $⟨D_{t}J,T{⟩}^2/c^2$. Returning to the original parameter, every ruling has constant speed, so $L_{[a,b]}(s)=(b-a)|{\partial }_t\varphi (0,s)|$ and the full open-interval length is $2\delta |{\partial }_t\varphi (0,s)|$. ConsequentlyThe preceding curvature formula, with the base-speed factor $1/c$ when necessary, therefore evaluates the original full length derivative using any compact subinterval. No extension to the missing endpoints is required.

Differentiating $D_{t}T=0$ in $s$ yields the Jacobi field equationThe same ruling curves are geodesics of the surface with its induced metric, because the tangential part of their ambient acceleration is zero. Write its second fundamental form as $II$ and its induced Levi-Civita connection as $D^N$. In particular $II(T,T)=0$. The scalar $f=⟨J,T⟩$ satisfies $f^{\prime \prime }=0$, by the Jacobi field equation, so $W=J-fT$ is a Jacobi field both intrinsically and in the ambient manifold. In a regular surface chart $h=|W|>0$, and $E=W/h$ is the perpendicular unit tangent. Along a two-dimensional geodesic, $D_t^{N}E=0$: its derivative is orthogonal to both $E$ and the parallel field $T$. The intrinsic Jacobi field equation consequently givesFor the ambient derivative, the Gauss formula gives $D_{t}W=h^{\prime }E+hII(T,E)$. Applying the same norm differentiation used above to $h=|W|$ givesComparing these identities proves the curvature comparison for a geodesically ruled surface:This is also the Gauss equation in a curved ambient manifold with $II(T,T)=0$. It applies locally to each regular patch of the surface.

For strict inequality, take the Euclidean embedded submanifold parametrized by $\varphi (t,s)=(t,s,ts)$. Each $t$-curve is a straight-line geodesic. Its first fundamental form has coefficients $E_0=1+s^2$, $F_0=st$, $G_0=1+t^2$; the normal $(-s,-t,1)/\sqrt{1+t^2+s^2}$ gives second fundamental form coefficients $e=0$, $f_0=1/\sqrt{1+t^2+s^2}$, $g_0=0$. HenceThus equality can fail everywhere, although every ruling is an ambient geodesic.

The length differentiation requires a nonconstant base ruling; a regular parametrized surface patch guarantees this. If “image of a smooth map” is read literally without a rank assumption, a degenerate member can fail even to have a first length derivative. For example, in the flat cylinder $\mathbb{R}\times S^1$, the map $\varphi (t,s)=(st,e^{is})$ for $|t|<\delta$, $|s|<4\pi$ has geodesic rulings and a two-dimensional open image: every nonzero-$s$ point has full-rank parametrization, and the sole zero-$s$ image point also has a full-rank preimage at $s=2\pi ,t=0$. Yet $L({\gamma }_s)=2\delta |s|$ is not differentiable at zero. The variation formula therefore applies to nonconstant members, as usual. The curvature inequality still holds on the whole image: regular values are dense by Sard theorem, and both curvatures extend continuously to the remaining points.

We prove both inequalities, including the BK inequality, for the inhomogeneous product measure in the question. Identify a configuration with its set of coordinates equal to one. An up-set is then an increasing event. For an increasing event $A$, a set $S$ of open coordinates is a witness if the configuration with precisely $S$ open belongs to $A$: upward closure ensures that those coordinates alone force $A$, whatever the remaining coordinates do. The event $A\square B$ means that there are disjoint open witnesses $S,T$ for $A,B$ respectively.

First prove the Harris' inequality by induction on the number of coordinates. For the last coordinate, of parameter $p$, write $A_0\subseteq A_1$ and $B_0\subseteq B_1$ for the two sections in the remaining coordinates, and put $a_i=\mathbb{P}(A_i)$, $b_i=\mathbb{P}(B_i)$. Induction applied to each section givesSubtract the product of the marginal probabilities from the right-hand side:The base case of zero coordinates is immediate. Thus

For disjoint occurrence, first assume every coordinate parameter is at most $1/2$, and again use induction. Put $c_{ij}=\mathbb{P}(A_i\square B_j)$ on the remaining coordinates. The zero-section of $A\square B$ is exactly $A_0\square B_0$. The one-section is exactlyIndeed, the last open coordinate can belong to at most one of two disjoint witnesses. Assigning it to the $A$ witness leaves a witness for $A_1$ and a witness for $B_0$; assigning it to the $B$ witness gives the other event. If neither witness uses it, both descriptions still hold. Conversely, witnesses for either displayed event lift to disjoint witnesses by adding the last coordinate only to the appropriate one.

The intersection of the two displayed events contains $A_0\square B_0$, because the sections are increasing. ThereforeThe coefficient $1-2p$ is nonnegative. Applying the induction hypothesis to each term givesThe product of the marginal probabilities is exactly this last expression plusThis proves the desired inequality whenever every parameter is at most $1/2$.

To remove that restriction, suppose first $p_i<1$ for every coordinate. Replace coordinate $i$ by the logical disjunction of $m_i$ independent Bernoulli bits, each with parameterChoose $m_i$ large enough that $q_i\le 1/2$. Different blocks are independent, and their OR values have exactly the original distribution. Let $\tilde{A},\tilde{B}$ be the inverse images of $A,B$ under this block-OR map; they are increasing events. If the OR configuration has disjoint witnesses $S,T$, choose one open bit from each block indexed by $S$ or $T$. The bits chosen for $S$ force $\tilde{A}$, those for $T$ force $\tilde{B}$, and the two bit sets are disjoint. Thus the inverse image of $A\square B$ is contained in $\tilde{A}\square \tilde{B}$. The small-parameter result provesParameters equal to one follow by a limit: probabilities of any fixed event on a finite cube are polynomials in the coordinate parameters, hence continuous. Zero parameters already cause no difficulty. We have obtained

For the graph application, take coordinates to be the edges of the complete graph. Let $A$ be the increasing event that $x$ is connected by a graph path to $U$, and $B$ the corresponding event for $W$. Their probabilities are $\alpha ,\beta$. A simple graph path from $U$ to $W$ through $x$ splits at $x$ into two graph paths with disjoint edge sets. Those sets witness $A$ and $B$, so this graph path event is contained in $A\square B$. The BK inequality givesOn the other hand, if both $A$ and $B$ occur, concatenate an $x$-to-$U$ graph path and an $x$-to-$W$ graph path to obtain a walk from $U$ to $W$. Removing loops yields a simple graph path, although it need not pass through $x$. Thus $A\cap B$ is contained in the unrestricted connection event, and the Harris' inequality givesThe distinction between a simple graph path through $x$ and an unrestricted connection is essential: a walk may revisit an edge, so a through-$x$ walk would not in general provide disjoint witnesses.

Colour every vertex independently red or blue, each with probability $1/2$. A fixed $r$-element hypergraph edge is monochromatic with probability $2^{1-r}$. If there are $m<2^{r-1}$ hypergraph edges, the expected number of monochromatic hypergraph edges is $m{2}^{1-r}<1$. Equivalently, the union bound says that the probability of even one monochromatic hypergraph edge is less than one. A proper two-colouring therefore exists.

For the converse, suppose $r\ge 2$, put $N=2r^2$, and sample $m$ independent uniformly random $r$-subsets of an $N$-vertex set. Initially this is a multihypergraph. For a fixed two-colouring with $a$ red vertices, a sampled hypergraph edge is monochromatic with probabilityThe numerator is minimized by $a=N/2=r^2$. To see this discretely, use $\left(\genfrac{}{}{0ex}{}{a+1}{r}\right)-\left(\genfrac{}{}{0ex}{}{a}{r}\right)=\left(\genfrac{}{}{0ex}{}{a}{r-1}\right)$: the successive difference of the numerator is $\left(\genfrac{}{}{0ex}{}{a}{r-1}\right)-\left(\genfrac{}{}{0ex}{}{N-a-1}{r-1}\right)$, negative up to the middle and positive afterwards. Binomial coefficients with an upper index below $r$ are understood as zero.

For this balanced colouring,The elementary inequality ${\prod }_j(1-u_j)\ge 1-{\sum }_j{u}_j$, valid for $0\le u_j\le 1$, givesThus any fixed colouring is proper for all the sampled hypergraph edges with probability at most $e^{-m{2}^{-r}}$. There are $2^N$ colourings, so chooseA union bound makes the probability that any proper colouring exists at most $2^N{e}^{-m{2}^{-r}}\le e^{-1}<1$. Some sampled multihypergraph is consequently not two-colourable. Remove repeated copies of its hypergraph edges: this changes neither which colourings are proper nor non-two-colourability, and leaves at most $m$ distinct hypergraph edges. We have provedFor $r=1$, one singleton hypergraph edge is already not two-colourable, so that endpoint causes no exception.

Expose the vertices in order, revealing at step $i$ every edge from vertex $i$ to an earlier vertex. With the resulting filtration ${\mathcal{F}}_i$, putThis is the vertex exposure for chromatic number martingale. Its increments $D_i=M_i-M_{i-1}$ have conditional mean zero and satisfy $|D_i|\le 1$, by the permitted Lipschitz condition.

Here is the required exponential-moment proof of the Azuma-Hoeffding inequality. More generally, suppose $|D_i|\le c_i$ for deterministic $c_i$. Convexity of the exponential function gives, for $-c_i\le d\le c_i$,Taking conditional expectation and using the zero conditional mean yieldsFor the last inequality, integrate $(\log \cosh u{)}^{\prime }=\tanh u\le u$ for $u\ge 0$, and use evenness. A zero $c_i$ simply means a zero increment. Iterated conditional expectation now givesFor $s,t>0$, the strict Markov bound on the event $M_n-M_0>s$ givesThe strict inequality follows directly by integrating $e^{t(M_n-M_0)}>e^{ts}$ on that event; it is also immediate if the event is empty. Optimize at $t=s/{\sum }_i{c}_i^2$ and apply the same argument to the negative increments. For $c_i=1$ and $s=\lambda \sqrt{n}$, the union bound proves, for every $\lambda >0$,At $\lambda =0$ the displayed strict bound is trivial.

For the second conclusion write $a_n=n/\log n$ and choose a fixed $C>\sqrt{2\log 10}$. If $\mu \ge a_n+C\sqrt{n}$, then $\{\chi (G)<a_n\}\subseteq \{\chi (G)-\mu <-C\sqrt{n}\}$, whose probability is less than $e^{-C^2/2}<1/10$. Thus the given positive probability forces $\mu <a_n+C\sqrt{n}$. For sufficiently large $n$,Here the non-strict one-sided bound follows by the usual non-strict Markov inequality. Consequently the asserted upper bound holds with high probability, uniformly over any sequence $p=p(n)$ satisfying the stated assumption.

We prove a weighted version of the Szemerédi regularity lemma, which is sufficient for the grid application. For disjoint nonempty vertex sets $U,W$ in a graph, write $d(U,W)=e(U,W)/(|U||W|)$ for their edge density of a bipartite graph. Call the pair $\epsilon$-regular if every $U^{\prime }\subseteq U$, $W^{\prime }\subseteq W$ with $|U^{\prime }|\ge \epsilon |U|$ and $|W^{\prime }|\ge \epsilon |W|$ satisfies $|d(U^{\prime },W^{\prime })-d(U,W)|\le \epsilon$.

The weighted Szemerédi regularity lemma states that, for every $0<\epsilon <1$, there are integers $M,v_0$ such that every graph on $v\ge v_0$ vertices has a set partition into at most $M$ nonempty cells $V_1,\dots ,V_k$, each of size at most $\epsilon v$, for whichThe sum is ordered. The cells need not have equal sizes; their weights replace the usual unweighted count of bad pairs.

To prove it, start with $k_0=\lceil 2/\epsilon \rceil$ nearly equal cells, taking $v\ge k_0$. Each has size at most $v/k_0+1\le \epsilon v$. Define the regularity energyHere even diagonal rectangles use the mean adjacency indicator, counting ordered pairs of vertices. Thus $0\le q\le 1$. Under a refinement, the old rectangle density is the weighted mean of the new ones, and the refinement variance identity for regularity energy givesIn particular refinement cannot decrease energy.

If the irregular-pair weight exceeds $\epsilon v^2$, choose witness subsets $U^{\prime }\subseteq U$, $W^{\prime }\subseteq W$ for every irregular unordered pair, and split each cell simultaneously by all its witnesses. There are at most $k-1$ such subsets in any one cell, so the new number of cells is at most $k{2}^k$. In an irregular rectangle, its witness has relative area at least ${\epsilon }^2$ and density discrepancy greater than $\epsilon$. Since the witness rectangle is now a union of refined rectangles, the Cauchy-Schwarz inequality applied to their weighted density discrepancies bounds the variance contribution from below bySumming over both orientations of all irregular pairs raises $q$ by more than ${\epsilon }^5$. Since $q\le 1$, after at most $\lceil {\epsilon }^{-5}\rceil$ rounds the required weight bound must hold. The finite recurrence $k\mapsto k{2}^k$, starting at $k_0$, supplies $M(\epsilon )$; all cells remain small because we only refine. This proves the stated weighted Szemerédi regularity lemma.

We next derive the triangle removal lemma from this version. First, three disjoint classes $U,W,Z$ whose pairs are $\epsilon$-regular pairs of density at least $d$ have many triangles if $\epsilon \le d/2$ and $\epsilon \le 1/4$. Fewer than $\epsilon |U|$ vertices of $U$ have fewer than $(d-\epsilon )|W|$ neighbours in $W$: otherwise that set of vertices, paired with all of $W$, would violate regularity. The same holds for $Z$. For each of the at least $(1-2\epsilon )|U|$ remaining vertices, both neighbour sets have relative size at least $d-\epsilon \ge \epsilon$. Regularity of $(W,Z)$ then supplies at least $(d-\epsilon )$ times the product of those two neighbour-set sizes edges. Thus the regular triangle counting lemma, also for unequal class sizes, givesFor a desired deletion tolerance $0<\eta <1$, take $\epsilon =\eta /100$, $d=\eta /4$, and a weighted regularity partition with at most $M=M(\epsilon )$ cells. Put $\tau =\epsilon /M$. Delete edges inside cells, between irregular pairs, between regular pairs of density less than $d$, and incident to cells smaller than $\tau v$. The first two deletions each cost at most $\epsilon v^2/2$. The sparse-pair deletion costs at most $d{v}^2/2$. For the last deletion, small-cell deletion in weighted regularity removes at most $M\tau v=\epsilon v$ vertices and at most $\epsilon v^2$ incident edges. The total is bounded byA triangle surviving these deletions would lie in three distinct cells, all of size at least $\tau v$, with all their pairs regular and of density at least $d$. The original graph would then have at least $d^3{\tau }^3{v}^3/16$ triangles. Therefore, witha graph on sufficiently many vertices with at most $\kappa v^3$ triangles can be made triangle-free by deleting fewer than $\eta v^2$ edges. This establishes the triangle removal lemma with every parameter depending only on $\eta$.

Now apply a tripartite graph encoding of a grid. Take separate vertex classes $X=[N]$, $Y=[N]$, $Z=\{2,\dots ,2N\}$. For each grid point $(x,y)$ in the given set, put in the three edgeswhere their endpoints belong respectively to $X\times Y$, $X\times Z$, and $Y\times Z$. Each point supplies a triangle. These $|A|$ triangles are edge-disjoint triangles, since any one of the three edge types uniquely determines the point that supplied it.

Conversely, any triangle with vertices $x\in X$, $y\in Y$, $z\in Z$ forces the three pointsto belong to $A$. Put $d=z-x-y$. For $d\ne 0$ these form a corner in an integer grid; for $d=0$ they all arise from the same grid point. Thus if there is no corner, the graph has exactly $|A|\le N^2$ triangles, yet destroying all triangles requires at least $|A|\ge \delta N^2$ edge deletions.

We may suppose $0<\delta \le 1$, since larger densities make the request vacuous. Use the triangle removal lemma with $\eta =\delta /32$. Our graph has $v=4N-1$ vertices, so, for sufficiently large $N$, its bound $N^2$ on the number of triangles is at most $\kappa v^3$. The lemma would delete fewer thanedges to destroy all triangles. This contradicts the lower bound $\delta N^2$ from the edge-disjoint family. Hence every sufficiently large positive-density square grid contains a nondegenerate corner, proving the requested corners theorem and in particular the existence of a suitable $N$.

The uniform modular Frankl-Wilson theorem states the following. Let $p$ be prime, let $L\subseteq {\mathbb{F}}_p$ have size $s$, and let $\mathcal{F}$ be a rank-$k$ family on $[N]$, with $0\le s\le \min \{k,N-k\}$. Assume $k\mathrm{mod}p\notin L$ and $|A\cap B|\mathrm{mod}p\in L$ for every distinct $A,B\in \mathcal{F}$. ThenThe restrictions concern distinct pairs; the diagonal size residue is explicitly excluded from $L$.

For each member $A$, over ${\mathbb{F}}_p$ form the intersection polynomialAt the characteristic vector $1_B$, its value vanishes when $B\ne A$ and is nonzero when $B=A$. Thus these functions are linearly independent on the whole rank-$k$ layer: evaluate any linear relation at each family member in turn. Replacing every positive power of $z_i$ by $z_i$ preserves all Boolean evaluations, so the functions are restrictions of multilinear polynomials of degree at most $s$.

We need the sharp low-degree evaluation rank on a uniform layer, not the larger whole-cube dimension ${\sum }_{j\le s}\left(\genfrac{}{}{0ex}{}{N}{j}\right)$. Let $M$ be the integer incidence matrix with rows indexed by subsets $S$ of size at most $s$, columns by rank-$k$ sets $B$, and entries $1_{S\subseteq B}$. Over the rationals, if $|S|=j\le s$, thenThis coefficient counts the possible $T$ inside each containing column set and is positive because $s\le k$. Consequently the degree-$s$ rows span all rows over $\mathbb{Q}$, giving rank at most $\left(\genfrac{}{}{0ex}{}{N}{s}\right)$. Every larger square minor is therefore the integer zero. Reducing those minors modulo $p$ shows the rank over ${\mathbb{F}}_p$ is also at most $\left(\genfrac{}{}{0ex}{}{N}{s}\right)$. This transfer avoids dividing by a binomial coefficient that might vanish modulo $p$. The independent functions $f_A$ lie in this row space, so their number is at most its rank. This proves the theorem in full.

For the requested forbidden-intersection application, split $\mathcal{A}$ into sets containing coordinate one and sets avoiding it. In the first part, delete one. Distinct original sets have intersection size between one and $2p-1$, excluding $p$. Their reduced intersections therefore lie between zero and $2p-2$, excluding $p-1$, so their residues belong to $L=\{0,\dots ,p-2\}$. The reduced set size is $2p-1$, whose residue is $p-1\notin L$. Frankl-Wilson on the ground set of size $4p-1$ bounds this part by $\left(\genfrac{}{}{0ex}{}{4p-1}{p-1}\right)$.

For the avoiding part, first complement every set. The complements contain one, retain size $2p$, and satisfyDelete one and apply the same argument. The complement splitting for forbidden midpoint intersections yields the stronger boundThe split is essential: a family may contain complementary pairs with intersection zero, preventing direct use of $L=\{1,\dots ,p-1\}$ on the original layer.

The Borsuk conjecture asserted that a bounded subset of ${\mathbb{R}}^d$ of positive diameter can be partitioned into $d+1$ subsets of strictly smaller diameter. Here is the Kahn-Kalai counterexample to the Borsuk conjecture, implemented by balanced cut vectors. For each $X\in [4p{]}^{(2p)}$, define $v_X\in {\mathbb{R}}^{\left(\genfrac{}{}{0ex}{}{4p}{2}\right)}$ whose coordinate indexed by an unordered pair $\{i,j\}$ is one when exactly one endpoint lies in $X$, and zero otherwise. Complementary sets give the same cut. Choose the representative with $1\in X$, obtaining exactlydistinct points: a cut determines its two parts, and fixing the side containing one removes its only ambiguity. Every cut has $(2p{)}^2=4p^2$ occupied coordinates, so all points lie in the affine hyperplane with coordinate sum $4p^2$. Its dimension isWe can identify this hyperplane isometrically with ${\mathbb{R}}^d$; no claim of full affine span is needed.

For two side sets with $t=|X\cap Y|$, their symmetric difference has $4p-2t$ points. The two cuts disagree exactly on pairs with one endpoint in that symmetric difference, giving the balanced cut-vector distance formulaThe diameter is $2p$, attained exactly when $t=p$; such pairs exist even among representatives containing one. Thus a smaller-diameter part contains no pair with side intersection $p$. Since all representative sets already contain one, deleting that common coordinate and applying the preceding Frankl-Wilson argument bounds each part by $\left(\genfrac{}{}{0ex}{}{4p-1}{p-1}\right)$. There is no extra factor two at this step. This is the cut construction described in the original Kahn-Kalai paper; the distance and part-size calculations above give the required justification directly.

An explicit choice is $p=13$. The point set lies in dimensionThe exact counts areTheir ratio requires at least $\lceil M/B\rceil =1562$ smaller-diameter parts, exceeding $d+1=1326$. In particular,Rescaling the point set to diameter one changes none of these partition counts. Therefore the Borsuk counterexample in dimension 1325 is fully explicit. This is a concrete dimension, not a claim that it is the smallest possible counterexample dimension.

Use binary encoding $b(S)={\sum }_{i\in S}{2}^{i-1}$ for vertices of the hypercube graph, and write $I_m=\{S:b(S)<m\}$. Let $e(\mathcal{A})$ count edges with both endpoints in a family. The exact edge-isoperimetric theorem for binary initial segments, due to Harper, Lindsey, Bernstein and Hart, iswhere $s_2(j)$ is the number of ones in the binary expansion. Equivalently,The equality for $I_m$ follows by assigning each internal edge to its larger endpoint: each one-bit of that endpoint can be cleared, giving an earlier endpoint still in $I_m$. This is the exact extremal statement, stronger than the logarithmic entropy bound.

We prove it by induction on $n$. The case $n=1$ follows by checking sizes zero, one and two. Fix a coordinate $i$ and delete it from the two sections ${\mathcal{A}}_0,{\mathcal{A}}_1$. The edge count splits asReplace each section by a binary initial segment of the same size. By induction its internal edges cannot decrease. The two replacement segments are nested, so their intersection size is the smaller section size, at least the previous intersection size. Thus this section compression in binary order cannot decrease $e(\mathcal{A})$.

Repeatedly perform any nontrivial section compression. The sum ${\sum }_{S\in \mathcal{A}}b(S)$ strictly decreases each time: in a fixed section, the original numerical order is exactly the numerical order after deleting its fixed coordinate. This nonnegative integer potential ensures termination at a family compressed in every coordinate section.

Classify such a terminal family. If an absent vertex $S$ precedes a present vertex $T$, they cannot agree in any coordinate, because their common section is compressed and its earlier vertex would then have to be present. Hence $T=[n]\setminus S$. There can be no vertex strictly between them: if present, it would also have to be the complement of $S$; if absent, it would have to be the complement of $T$. Thus they are consecutive complementary binary integers, forcingNo other inversion is possible for the same reason. Therefore a terminal family is either a binary initial segment or the sole exceptional formThis exception has size $2^{n-1}$. For $n\ge 2$, compared with the half-cube $I_{2^{n-1}}$, it removes a vertex of internal degree $n-1$ and adds a vertex joined only to the retained empty set. Its edge count is thus $e(I_{2^{n-1}})-(n-1)+1\le e(I_{2^{n-1}})$. The $n=1$ case was already handled. Since compression never decreased edges, every original family has at most the initial segment's edge count. This proves the theorem, including the exceptional terminal configuration rather than assuming all compressed families are initial segments.

For the remaining requests it is useful to obtain the entropy proof of cube edge-isoperimetry, including its equality cases. Inductively a family of size $m$ satisfiesIndeed let the two sections have sizes $a\ge b\ge 0$, $m=a+b>0$. Their internal edges are bounded inductively and the crossing edges are at most $b$, soHere $0{\log }_{2}0=0$ and $H_2(t)=-t{\log }_{2}t-(1-t){\log }_2(1-t)$ is the binary entropy function. Its concavity and its endpoint values at zero and one-half give $H_2(t)\ge 2t$ for $0\le t\le 1/2$. This proves the bound, starting from the zero-dimensional cube.

Define the isoperimetric number of a graph bySince every cube vertex has degree $n$, the internal-edge bound giveswhen $|A|\le 2^{n-1}$. A coordinate half-cube has one crossing edge per vertex, attaining ratio one. Hence, for $n\ge 1$,

Now establish the equality cases of entropy cube edge-isoperimetry. Strict concavity of $H_2$ makes $H_2(t)>2t$ for $0<t<1/2$. Equality in the internal-edge bound therefore requires either one section to be empty, or two equal-size sections. In the equal-size case equality in the crossing bound forces the sections to coincide; each section must also attain its inductive internal-edge bound. Induction gives exactly coordinate subcubes: the empty-section case fixes the coordinate, and the coincident-section case frees it. Conversely every coordinate subcube attains that bound.

At size $m=2^{n-1}$, an edge boundary of size $m$ means $e(A)=\frac{1}{2}m(n-1)=\frac{1}{2}m{\log }_{2}m$, so these equality cases apply. The subcube has dimension $n-1$ and fixes precisely one coordinate. ThereforeThese $2n$ coordinate half-cubes are the only extremizers of the requested size.