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Its $n$ disjoint triples give a product of degree-three multilinear polynomials, with all-variable coefficient $(-2{)}^n$. Hence its degree is $3n$ and its exact quantum query complexity is at least $\lceil 3n/2\rceil$. At the input consisting of repeated $110$ triples, each of the $2n$ one bits is a disjoint sensitive singleton. Thus block sensitivity is at least $2n$, implying a bounded-error quantum query complexity lower bound $\Omega (\sqrt{n})$.

Replace each positive power $x_i^d$ by $x_i$ in a polynomial. This gives a multilinear polynomial of no larger polynomial degree with the same values on $\{0,1{\}}^n$. In the polynomial method in combinatorics, these functions lie in a vector space with a basis consisting of the square-free monomials of the required polynomial degrees.

One exact parity query determines whether the first two bits agree. If they agree, a second query reads one of them; otherwise it reads the third bit. Those values respectively determine the three-bit majority function. The matching lower bound follows from its degree-three multilinear polynomial.

On the uniform layer of the Boolean cube ${\Omega }_r$, every multilinear polynomial of polynomial degree at most $s\le r$ is in the span of the degree-$s$ square-free monomials. For $T\subseteq [n]$, $|T|=j\le s$, and $x_T={\prod }_{i\in T}{x}_i$, the identity isAt the characteristic vector of a set $A$ of size $r$, both sides vanish if $T⊈A$. Otherwise exactly $\left(\genfrac{}{}{0ex}{}{r-j}{s-j}\right)$ summands are $1$. Hence the dimension of the restricted polynomial space is at most $\left(\genfrac{}{}{0ex}{}{n}{s}\right)$. No assertion of independence of the spanning monomials is needed, so no condition $r+s\le n$ is required. Unlike ordinary homogenization, this operation preserves degree bounds by using the fixed-weight evaluation domain.

A majority Boolean function outputs one when more than half its input bits are one. An odd number of inputs avoids a tie convention. For three bits its unique multilinear polynomial is $x_1{x}_2+x_1{x}_3+x_2{x}_3-2x_1{x}_2{x}_3$, so the polynomial method for quantum query lower bounds requires at least two exact queries.

Let $p$ be a prime number, $0\le a<p$, $1\le s<p$, and $n\ge a+s$. A multilinear polynomial over ${\mathbb{F}}_p$ of degree less than $s$ that vanishes on every Boolean vertex whose weight is not congruent to $a$ modulo $p$ vanishes everywhere. Alternating sums over intervals of $s$ free coordinates eliminate the possible nonzero weight levels one at a time. This proves independence of the auxiliary functions used for the uniform Frankl-Wilson theorem bound.

Replace each positive power $x_i^a$ in a monomial by $x_i$ and combine equal monomials. The result is a multilinear polynomial agreeing with the original polynomial at every point of $\{0,1{\}}^n$, because $x_i^a=x_i$ there for $a\ge 1$. Its polynomial degree does not increase. This reduction identifies polynomial functions on the Boolean lattice with their unique square-free monomial representations: uniqueness follows by successively evaluating at characteristic vectors of sets in increasing order of size.

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.

There is a genuine qualification missing from the printed bound. With $n=3,r=1,m=4$, the family of three singletons has distinct intersections of size zero, which is not congruent to $r$ modulo $m$. Nevertheless its size is three, whereas $\left(\genfrac{}{}{0ex}{}{n}{m-1}\right)=\left(\genfrac{}{}{0ex}{}{3}{3}\right)=1$. Thus that bound cannot hold without a restriction on the parameters. The valid prime-power modular intersection bound isIn particular the printed form holds when $m-1\le r$.

Put $m=p^a$ with $p$ a prime number, and $d=m-1$. If $r<d$, the corrected bound is simply the total number $\left(\genfrac{}{}{0ex}{}{n}{r}\right)$ of $r$-sets. Assume henceforth $d\le r$. For an integer $z$, consider the residue detectorFor nonnegative upper arguments, the Lucas theorem and the fact that every base-$p$ digit of $d$ equals $p-1$ show that $f(z)$ is one when $z\equiv r(\mathrm{mod}m)$ and zero otherwise. The assertion also holds for negative upper arguments, using integer-valued generalized binomial coefficients. Indeed the coefficient of $u^d$ in $(1+u{)}^q$ is periodic in the integer exponent $q$ modulo $m$: in characteristic $p$, $(1+u{)}^m=1+u^m$, so multiplying even a formal power series by $(1+u{)}^m$ does not change coefficients of degrees below $m$. Reduce any exponent modulo $m$ to obtain the stated detector.

For each $A\in \mathcal{F}$, apply that detector to $|A\cap B|$. Its evaluations on $B\in \mathcal{F}$ form the identity matrix, since the diagonal intersection is $r$ and every off-diagonal intersection has a different residue. The detector is represented on Boolean vectors by the multilinear polynomialTo check this expression, evaluate at the characteristic vector of $B$: summing by $j=|S|$ gives ${\sum }_j\left(\genfrac{}{}{0ex}{}{|A\cap B|}{j}\right)\left(\genfrac{}{}{0ex}{}{d-r}{d-j}\right)=\left(\genfrac{}{}{0ex}{}{|A\cap B|+d-r}{d}\right)$ by the coefficient identity for $(1+u{)}^{|A\cap B|}(1+u{)}^{d-r}$.

Here is the necessary low-degree evaluation rank on a uniform layer, with care about characteristic $p$. Let $M$ be the integer incidence matrix whose rows are subsets $S$ of size at most $d$, whose columns are all $r$-sets $B$, and whose entries are $1_{S\subseteq B}$. Over the rational numbers, for $|S|=j\le d$ its row satisfiesThus its rational matrix rank is at most $\left(\genfrac{}{}{0ex}{}{n}{d}\right)$. Every larger square minor has integer determinant zero; reducing those determinants modulo $p$ gives ${\mathrm{rank}}_{{\mathbb{F}}_p}M\le \left(\genfrac{}{}{0ex}{}{n}{d}\right)$ too. This argument does not divide by a potentially zero element of the finite field. The identity evaluation matrix $(f_A(1_B){)}_{A,B\in \mathcal{F}}$ factors through these incidence rows, so its rank $|\mathcal{F}|$ is at most $\left(\genfrac{}{}{0ex}{}{n}{d}\right)$. This proves the qualified bound.

Choose the two-applications alternative. First, the polynomial method in combinatorics yields a constructive lower bound for a diagonal Ramsey number. Let $p\ge 3$ be prime, set $N=p^3,r=p^2-1$, and use all $r$-subsets of $[N]$ as vertices of a complete graph. Color a pair red when its intersection size is $-1$ modulo $p$, and blue otherwise. A blue clique has size at most $D=\left(\genfrac{}{}{0ex}{}{N}{p-1}\right)$ by the proved bound with modulus $p$. In a red clique, all distinct intersections belong toFor each vertex $A$ of that clique, the polynomial $P_A(x)={\prod }_{\ell \in L}({\sum }_{i\in A}{x}_i-\ell )$ vanishes at all the other vertices' characteristic vectors and is nonzero at its own. Replace repeated powers $x_i^j$ by $x_i$ on Boolean vectors. Its degree is at most $p-1$, so the rational version of the same incidence-rank argument bounds a red clique by $D$ as well. Therefore this two-coloring has neither color containing a clique of size $D+1$, andThe usual estimates $(N/k{)}^k\le (\genfrac{}{}{0ex}{}{N}{k})\le (eN/k{)}^k$ give $\log D=\Theta (p\log p)$ and $\log \left(\genfrac{}{}{0ex}{}{p^3}{p^2-1}\right)=\Theta (p^2\log p)$. Thus along this explicit sequence the diagonal Ramsey number exceeds $\exp (c(\log s{)}^2/\log \log s)$ for some absolute $c>0$. This is substantially larger than any fixed power of $s$.

Second, obtain an exponential lower bound for the chromatic number of Euclidean space. Let $N=4p-1,r=2p-1$, and join two $r$-subsets exactly when their intersection has size $p-1$. An independent set in this graph avoids that intersection. Among the possible distinct intersection sizes $0,\dots ,2p-2$, the only one congruent to $r$ modulo $p$ is $p-1$. Hence every independent set has size at most $\left(\genfrac{}{}{0ex}{}{4p-1}{p-1}\right)$. Embed each vertex as $v_A=1_A/\sqrt{2p}$ in Euclidean space. Thenso the graph's edges have exactly Euclidean distance one. Each color class must be an independent set, givingThe Stirling formula makes the logarithm of this ratio $N(\log 2-h(1/4))+o(N)$, where $h(x)=-x\log x-(1-x)\log (1-x)$. Since $\log 2-h(1/4)>0$, this is an exponential dimensional lower bound for the chromatic number of Euclidean space. Both applications lie in the valid parameter range of the proved modular bound.

The Frankl-Wilson theorem in its uniform form says: let $p$ be a prime number, let $L\subseteq {\mathbb{F}}_p$ have size $s\le \min (k,n-k)$, and let $\mathcal{F}\subseteq \left(\genfrac{}{}{0ex}{}{[n]}{k}\right)$ have $k\mathrm{mod}p\notin L$, while $|A\cap B|\mathrm{mod}p\in L$ for every distinct pair of members. Then

The modular-intersection, nonuniform form of the Frankl-Wilson theorem is as follows. Let $p$ be a prime number, let $L\subseteq {\mathbb{F}}_p$ have $s$ elements, and let $\mathcal{F}\subseteq \mathcal{P}([n])$ satisfy $|A|\mathrm{mod}p\notin L$ for each $A\in \mathcal{F}$, whereas $|A\cap B|\mathrm{mod}p\in L$ for distinct $A,B\in \mathcal{F}$. ThenThis nonuniform Frankl-Wilson theorem allows different sizes and different diagonal residues; in particular it applies when all sizes have one common residue outside $L$.

To prove it by the polynomial method in combinatorics, work over the finite field ${\mathbb{F}}_p$ and associate to each member the intersection polynomialReplace each positive power of $x_i$ in its expansion by $x_i$ to obtain its multilinear reduction on the Boolean cube ${\tilde{P}}_A$. This preserves evaluation on every characteristic vector, whose coordinates are zero or one, and leaves degree at most $s$. At the characteristic vector $1_B$,It is zero for distinct $A,B$, and nonzero for $B=A$ by the diagonal hypothesis. If ${\sum }_{A\in \mathcal{F}}{c}_A{\tilde{P}}_A=0$, evaluating at each $1_B$ forces $c_B=0$. Thus the multilinear polynomials are linearly independent. They belong to the vector space with basis the square-free monomials ${\prod }_{i\in S}{x}_i$ for $|S|\le s$, whose dimension is the displayed sum. This proves the nonuniform form, including $s=0$, where distinct members are impossible and the empty product is one.

For the sharp uniform form, we need the low-degree evaluation rank on a uniform layer. Form the integer matrix $M$ whose rows are indexed by $S\subseteq [n]$ with $|S|\le s$, columns by $k$-subsets $T$, and entries $M_{S,T}=1_{S\subseteq T}$. These are evaluations of the square-free monomials. Over the rational numbers, the row of a $j$-subset $S$ satisfiesIndeed, when $S\subseteq T$ the left side counts the $s$-subsets between $S$ and $T$, and otherwise both sides vanish. Since $s\le k$, the coefficient is a positive integer. Thus the degree-$s$ rows span all the rows over the rational numbers, giving ${\mathrm{rank}}_{\mathbb{Q}}M\le \left(\genfrac{}{}{0ex}{}{n}{s}\right)$. Every square submatrix of larger size has integer determinant zero, so its determinant remains zero modulo $p$. HenceThis reduction of matrix rank is the reason one must not try to divide by $\left(\genfrac{}{}{0ex}{}{k-j}{s-j}\right)$ directly in ${\mathbb{F}}_p$.

The evaluations of the ${\tilde{P}}_A$ on the $k$th uniform layer of the Boolean cube lie in the row linear span of $M$ over ${\mathbb{F}}_p$. They are linearly independent as functions there, because restriction to the columns corresponding to $\mathcal{F}$ still gives the nonzero diagonal evaluation matrix. Their number is consequently at most $\left(\genfrac{}{}{0ex}{}{n}{s}\right)$. This completes the proof of the uniform Frankl-Wilson theorem as well.

For the odd-cardinality problem the sharper Oddtown theorem follows directly from linear algebra. Let $v_A=1_A\in {\mathbb{F}}_2^n$ be the characteristic vector. The parity conditions sayFor any linear combination ${\sum }_A{c}_A{v}_A=0$, take its dot product with $v_B$. All off-diagonal terms vanish, leaving $c_B=0$. Hence these vectors are linearly independent in an $n$-dimensional vector space, givingThe singleton sets show that the bound can be attained. Notice why the constant term in the general nonuniform Frankl-Wilson theorem is unnecessary here: these dot products already give a diagonal evaluation matrix using only the $n$ coordinate functions.

For even $n$, partition $[n]$ into the pairs $\{1,2\},\{3,4\},\dots ,\{n-1,n\}$ and take every union of a selection of these pairs. This gives exactly $2^{n/2}$ distinct sets, including the empty set. Each has even size; every pairwise intersection is again a union of entire pairs and therefore has even size. This attains the proposed bound.

For any set family satisfying the even-cardinality conditions, let $W$ be the linear span of its characteristic vectors over ${\mathbb{F}}_2$. Now the self-dot products vanish as well as the off-diagonal ones. By bilinearity, $u\cdot v=0$ for all $u,v\in W$, so $W\subseteq W^{\perp }$: it is a self-orthogonal binary subspace.

For completeness the standard bilinear form on ${\mathbb{F}}_2^n$ is nondegenerate, because a vector orthogonal to every coordinate vector has every coordinate zero. Thus the map $v\mapsto (w\mapsto v\cdot w)$ from ${\mathbb{F}}_2^n$ onto the dual space $W^{\ast }$ is surjective: every linear functional on $W$ extends to the whole vector space by extending a basis, and every such functional on ${\mathbb{F}}_2^n$ is a dot product with a vector. Its kernel is $W^{\perp }$. The rank-nullity theorem consequently gives $\dim W^{\perp }=n-\dim W$. The inclusion $W\subseteq W^{\perp }$ implies $\dim W\le n/2$. Finally, distinct members have distinct characteristic vectors, all in $W$, and a $k$-dimensional vector space over ${\mathbb{F}}_2$ has exactly $2^k$ elements. ThereforeThis proves the Eventown theorem and also explains the suggested dimension contradiction if the set family had more than $2^{n/2}$ members.

Work over the finite field ${\mathbb{F}}_p$. For each set family member form the intersection polynomialAt the characteristic vector of a set $B$, its value is ${\prod }_i(|A\cap B|-{\ell }_i)$. The given restrictions make $f_A({\chi }_B)=0$ for $A\ne B$ and $f_A({\chi }_A)\ne 0$. Hence these functions are linearly independent: evaluate a purported relation at each set family member to eliminate its coefficient.

Use multilinear reduction on the Boolean cube, replacing every positive power of $x_i$ by $x_i$. This preserves all evaluations on $\{0,1{\}}^n$ and cannot increase degree. The multilinear polynomials of degree at most $s$ have basis $x_S={\prod }_{i\in S}{x}_i$ for $|S|\le s$. Their dimension is ${\sum }_{j=0}^{\min (s,n)}\left(\genfrac{}{}{0ex}{}{n}{j}\right)$, and thereforewhere $\left(\genfrac{}{}{0ex}{}{n}{j}\right)=0$ for $j>n$. The proof also covers a list whose distinct integers have repeated residues: no assumption of distinct residues is needed for this first bound.

To obtain the sharper conclusion, suppose the common size residue $r$ avoids $0,\dots ,s-1$. If $s>n$, no set on this ground set can have the required residue, so the set family is empty. Otherwise, add the modular-size auxiliary polynomialsagain understood as functions after multilinear reduction on the Boolean cube. They have degree at most $s$, and all vanish on the set family's characteristic vectors of sets.

The $q_S$ are linearly independent. Indeed, evaluate ${\sum }_S{c}_S{q}_S=0$ on ${\chi }_T$ with $|T|\le s-1$:The first factor is nonzero in the finite field. Starting with $T=\varnothing$ and proceeding in increasing cardinality shows $c_T=0$ for every such $T$.

Moreover, the combined list consisting of the $f_A$ and the $q_S$ is linearly independent. Evaluation at each ${\chi }_A$ first kills the coefficient of $f_A$; the preceding argument then kills all remaining coefficients. Comparing this list with the dimension of the degree-at-most-$s$ space yieldsThis is a nonuniform common-residue version of the Frankl-Wilson theorem; exact equality of all member sizes was never used.

The exclusion of the small residues is necessary. A concrete example with $s<n$ is $n=4$, $p=5$, $s=3$, the residue list $0,1,3$, and the set family of all two-element subsets. Every member has size residue $r=2$, outside that list, while distinct members intersect in zero or one element. ButHere the omitted condition fails at $j=2$. Thus the example satisfies all the other hypotheses, rather than relying on a vacuous $s>n$ case.

Use the bit-query Boolean quantum oracle $O_x|i,b,z⟩=|i,b\oplus x_i,z⟩$, where $z$ denotes workspace. Initially every probability amplitude is independent of $x$, hence is a constant polynomial. An input-independent unitary gate only forms linear combinations of probability amplitudes, so it does not increase their polynomial degree.

If $a_{i,b,z}(x)$ is an amplitude before a query, its new value isOne query increases polynomial degree by at most one. Inductively, after $T$ queries each amplitude has polynomial degree at most $T$. The acceptance probability is a sum of squared absolute values of the accepting amplitudes, so it is a real polynomial of degree at most $2T$. Intermediate quantum measurements and classical adaptation can be retained coherently, or handled by summing unnormalized branch probabilities; either approach yields the same degree bound.

An exact algorithm has acceptance probability precisely $f(x)$ at every Boolean input. The multilinear reduction on the Boolean cube replaces positive powers of each $x_i$ by $x_i$, preserving these values without increasing polynomial degree. Therefore the polynomial method for quantum query lower bounds givesHere $\mathrm{deg}(f)$ is the degree of the unique multilinear polynomial representing the Boolean function, and $Q_E$ is its exact quantum query complexity. Uniqueness follows, for example, by evaluating successively on the indicator vectors of subsets: the value on a subset determines its coefficient once all smaller-subset coefficients are known.

For the three-bit majority function, the pair products count how many pairs of input bits are both one. Their sum is zero at Hamming weights zero and one, one at weight two, and three at weight three. Subtracting twice the triple product corrects the last value. HenceThis is a multilinear polynomial of degree three, and its top coefficient is nonzero. Uniqueness of the Boolean multilinear polynomial excludes a degree-two alternative. The polynomial method for quantum query lower bounds therefore yields $T\ge 3/2$, and the integer number of queries gives

Boolean conjunction is multiplication on zero-one inputs. The block conjunction of three-bit majorities therefore has the multilinear polynomialThe factors use disjoint variables, so their product remains a multilinear polynomial. Its monomial containing all $3n$ variables has coefficient $(-2{)}^n\ne 0$; no term has higher degree. By uniqueness, the representing multilinear polynomial has degree exactly $3n$. Applying the polynomial method for quantum query lower bounds givesThis argument concerns exact quantum query complexity; the analogous claim for bounded error does not follow from exact polynomial degree.

The general modular form, the nonuniform Frankl-Wilson theorem, can be stated as follows. Let $p$ be a prime number, and let $L\subseteq {\mathbb{F}}_p$ have $s$ elements. Suppose $\mathcal{F}\subseteq \mathcal{P}([n])$ has $|A|\mathrm{mod}p\notin L$ for every member, while $|A\cap B|\mathrm{mod}p\in L$ for any distinct members. ThenThe uniform Frankl-Wilson theorem sharpens this to $|\mathcal{F}|\le \left(\genfrac{}{}{0ex}{}{n}{s}\right)$ when all members have size $k$ and $0\le s\le \min \{k,n-k\}$. Both forms require a prime modulus and exclusion of the self-intersection residue.

For the general proof, work over the finite field ${\mathbb{F}}_p$. Associate to each member $A$ the intersection polynomialAt the characteristic vectors of sets $1_B$, this is zero if $B\ne A$, and nonzero if $B=A$. Thus these polynomials, regarded as functions on the Boolean hypercube, are linearly independent: evaluating any relation at $1_A$ isolates its coefficient. Apply multilinear reduction on the Boolean cube, replacing every positive power of a variable by that variable. Values on the Boolean hypercube remain unchanged, and the resulting multilinear polynomials have degree at most $s$. Their ambient space has a monomial basis consisting of $x_S={\prod }_{i\in S}{x}_i$ for $|S|\le s$, with dimension ${\sum }_{j=0}^{\min (s,n)}\left(\genfrac{}{}{0ex}{}{n}{j}\right)$. This proves the general bound, including $s=0$.

For completeness, obtain the uniform sharpening without dividing by factorials in a finite field. For $s\ge 1$ put $a=k\mathrm{mod}p$ and $g(x)={\sum }_i{x}_i-a$. The functions $x_{S}g$ with $|S|<s$ are linearly independent. Indeed, a relation gives $gh=0$ with $\mathrm{deg}h<s$, so $h$ is supported only on weights in $H=\{j\in [0,n]:j\equiv a(\mathrm{mod}p)\}$. With boundary weights $-1,n+1$, this set has a gap of at least $s+1$: either consecutive allowed weights differ by $p\ge s+1$, or its terminal gap does, since $n\ge k+s\ge a+s$. The alternating sum of $h$ over any interval of $s$ free coordinates vanishes by its degree. Across that gap only one endpoint level can contribute, forcing $h$ to vanish there. Delete that level and repeat across the enlarged gap until $H$ is empty. Hence $h=0$, and independence of the square-free monomials gives the claim. Adjoin these functions to the $f_A$. Evaluation at each family vector eliminates the coefficients of $f_A$, since $g$ vanishes there; the claim eliminates all remaining coefficients. Counting dimensions yieldsThe case $s=0$ permits at most one member directly. The gap argument is an instance of the modular layer vanishing lemma.

For the final application, enumerate the distinct sets as $A_1,\dots ,A_m$ and let $v_i=1_{A_i}\in {\mathbb{R}}^n$ be their characteristic vectors of sets. If $m\le 1$, the desired bound is immediate for $n\ge 1$. Otherwise $|A_i|\ge k$, because $A_i$ intersects another member in $k$ points. At most one member can have size $k$: two distinct $k$-sets cannot have intersection size $k$. The Gram matrix of these vectors isFor real coefficients $c_i$,All terms are nonnegative, with $k>0$. If the expression vanishes, every coefficient corresponding to a set of size greater than $k$ is zero. At most one coefficient remains, and the first term forces it to be zero as well. Thus the characteristic vectors of sets are linearly independent in ${\mathbb{R}}^n$, proving the constant-intersection family boundThis proof explicitly covers the possible member of size exactly $k$; assuming all diagonal corrections were strictly positive would miss that case. Positivity of $k$ is essential: when $k=0$, the empty set and all $n$ singleton sets give $n+1$ members.

The Frankl-Wilson theorem. Let $p$ be a prime number, let $L\subseteq {\mathbb{F}}_p$ have $s$ elements, and let $\mathcal{F}\subseteq \mathcal{P}([n])$. Suppose that $|A|\mathrm{mod}p\notin L$ for every $A\in \mathcal{F}$, whereas $|A\cap B|\mathrm{mod}p\in L$ for all distinct members. Thenwith terms beyond $n$ understood as zero.

Work over the finite field ${\mathbb{F}}_p$. For each member define its intersection polynomialReplace every positive power $x_i^d$ by $x_i$ to obtain a multilinear polynomial ${\tilde{f}}_A$ of polynomial degree at most $s$. This Boolean multilinearization preserves its values at every characteristic vector of a set. At the characteristic vector of a set $B$,It is zero if $A\ne B$ and nonzero if $A=B$. Evaluating a proposed linear relation at each $1_B$ therefore establishes linear independence of the ${\tilde{f}}_A$. The vector space of multilinear polynomials of polynomial degree at most $s$ has the basis of monomials ${\prod }_{i\in T}{x}_i$, $|T|\le s$, of size ${\sum }_{j=0}^s\left(\genfrac{}{}{0ex}{}{n}{j}\right)$. This proves the Frankl-Wilson theorem by the polynomial method in combinatorics. The empty product for $s=0$ is $1$, and the argument still applies.

The constant-intersection family bound, directly. Write $\mathcal{F}=\{F_1,\dots ,F_q\}$ and assume $n\ge 1$. The cases $q\le 1$ are immediate. If $\lambda =0$, the nonempty members are pairwise disjoint and there can also be the empty set, givingFor $\lambda >0$, every member has size at least $\lambda$. If every member has size strictly greater than $\lambda$, form the real matrix $X$ whose rows are their characteristic vectors of sets. Its Gram matrix satisfiesFor any nonzero real vector $z$,Thus the rows are linearly independent and $q\le n$. If a member $F_1$ has size $\lambda$, it lies inside every other member. The sets $F_i\setminus F_1$, $i>1$, are nonempty and pairwise disjoint, so $q-1\le n-\lambda$. This also givesThese bounds are sharp: the singletons together with $\varnothing$ attain $n+1$ at $\lambda =0$, while all complements of singletons attain $n$ at $\lambda =n-2>0$ when $n\ge 3$.

The constant t-wise intersection dichotomy. In its substantive form the last argument requires $m\ge t$. The printed statement does not explicitly impose this. Without it the $t$-fold condition can be vacuous and the claimed dichotomy is false: take $t=3$, $m=2$, $n=1$, $A_1=\varnothing$, $A_2=\{1\}$ and $\lambda =1$. There is no $3$-tuple to test, no common $1$-set, and $k=0$, so $m=2>k+t-2=1$. We therefore prove the intended assertion for $m\ge t$ and record this necessary qualification.

If $\lambda =0$, the first alternative always holds with $S=\varnothing$. Suppose $\lambda >0$. Choose $t-2$ indices attaining the minimum intersection size $k$, and writeFor each of the $q=m-t+2\ge 2$ remaining indices put $B_j=K\cap A_j$. The hypothesis gives $|B_j\cap B_{\ell }|=\lambda$ for distinct remaining indices. This reduces the constant t-wise intersection dichotomy to a constant-intersection family bound on the $k$-element set $K$. The two possibilities are treated below.