3 Intersecting Families

3.1 t-intersecting families

A⊂P(X) is called t-intersecting if |x∩y|≥t for all x,y∈A.

How large can a t-intersecting family be?

Example. t=2. Could take {x:1,2∈x} – has size 142n. Or {x:|x|≥n2+1} – has size ∼122n.

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Theorem 1 (Katona’s t-intersecting Theorem). Assuming that:

  • A⊂P(X) is t-intersecting

  • n+t even (to make the proof simpler – same proof works for odd)

Then |A|≤|X(≥n+t2)|.

Proof. For any x,y∈A: have |x∩y|≥t, so d(x,yc)≥t. So, writing A¯ for {yc:y∈A}, have d(A,A¯)≥t – i.e. A(t−1) disjoint from A¯. Suppose that |A|>|X(≥n+t2)|.

Then, by Harper’s Theorem, we have

|A(t−1)|≥|X(≥n+t2−(t−1))|=|X(≥n−t2+1)|.

But A(t−1) disjoint from A¯, which has size >|X(≤n−t2)| contradicting |A(t−1)|+|A¯|≤2n. □

What about t-intersecting A⊂X(r)?

Might guess: best is A0={x∈X(r):[t]⊂x}.

Could also try Aα={x∈X(r):|x∩[t+2α]|≥t+α}, for α=1,2,…,r−t.

Example. For 2-intersecting in:

  • [7](4): |A0|=52=10, |A1|=1+4331=13, |A2|=64=15.

  • [8](4): |A0|=62=15, |A1|=1+4341=17, |A2|=64=15.

  • [9](4): |A0|=72=21, |A1|=1+4351=21, |A2|=64=15.

Note that |A0| grows quadratically, |A1| linearly, and |A2| constant – so |A0| largest of these for n large.

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Theorem 2. Assuming that:

Then for n sufficiently large, we have |A|≤|A0|=n−tr−t.

Remark.

  • (1) Bound we get on n would be (16r)r (crude) or 2tr3 (careful).
  • (2) Often called the “second Erdős-Ko-Rado Theorem”.

Idea of proof: “A0 has r−t degrees of freedom”.

Proof. Extending A to a maximal t-intersecting family, we must have some x,y∈A with |x∩y|=t (if not, then by maximality have that ∀⁡x∈A, ∀⁡i∈x, ∀⁡j∉x, have x∪j−i∈A – whence A=X(r), contradiction).

May assume that there exists z∈A with x∩y⁄⊂z – otherwise all z∈A have x∩y⊂z. Whence |A|≤n−tr−t=|A0|.

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So each w∈A must meet x∪y∪z in ≥t+1 points. Thus

|A|≤23r⏟w on x∪y∪z(nr−t−1+nr−t−2+⋯+n0⏟w off x∪y∪z).

Note that the right hand side is a polynomial of degree r−t−1 – so eventually beaten by |A0|. □

3.2 Modular Intersections

For intersecting families, we ban |x∩y|=0.

What if we banned |x∩y|≡0(modsomething)?

Example. Want A⊂X(r) with |x∩y| odd for all distinct x,y∈A?

Try r odd: can achieve |A|=⌊n−12⌋r−12, by picture.

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What if, still for r odd, had |x∩y| even for all distinct x,y∈A? Can achieve n−r+1, by picture.

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This is only linear in n. Can we improve this?

Similarly if r even: For |x∩y| even for all x,y∈A, can achieve |A|=⌊n2⌋r2 – picture

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But for |x∩y| odd for all x,y∈A (distinct): can achieve n−r+1 (as above). Can we improve this?

Seems to be that banning |x∩y|=r(mod2) forces the family to be very small (polynomial in n, in fact a linear polynomial).

Remarkably, cannot beat linear.

Proposition 3. Assuming that:

  • r is odd

  • A⊂X(r) such that |x∩y| even for each distinct x,y∈A

Then |A|≤n.

Idea: Find |A| linearly independent vectors in a vector space of dimension n, namely Qn.

Proof. View P(X) as ℤ2n, the n-dimensional space over ℤ2 (the field of order 2). By identifying x with x¯, its characteristic sequence (e.g. 1011000… for {1,3,4}).

We have (x¯,x¯)≠0 for each x, as r is odd ((∙,∙) is the usual dot-product).

Also, (x¯,y¯)=0 for distinct x,y∈A (as |x∩y| even).

Hence the x¯, x∈A are linearly independent (if ∑⁡λixi¯=0, dot with xj¯ to get λj=0). □

Remark. Hence also if A⊂X(r), r even, with |x∩y| odd for all distinct x,y∈A, then |A|≤n+1 – just add n+1 to each x∈A and apply Proposition 3 with X=[n+1].

Does this modulo 2 behaviour generalise?

Now show: s allowed values for |x∩y| modulo p implies |A|≤ polynomial of degree s.

Theorem 4 (Frankl-Wilson Theorem). Assuming that:

  • p is prime

  • λ1,…,λs (s≤r)

  • λi⁄≡r(modp) for each i

  • A⊂X(r) such that for all distinct x,y∈A have |x∩y|≡λi(modp) for some i

Then |A|≤ns.

Remark.

  • (1) This bound is a polynomial in S (as r vares)!
  • (2) Bound is essentially best possible: can achieve |A|=nn−r+s∼ns (see picture).

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  • (3) Do need no λi≡r(modp). Indeed, if n=a+λp (0≤a≤p−1) then can have A⊂(a+kp) with |A|=λk (not a polynomial in n, as we can choose any k) and all |x∩y|≡a(modp).

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Idea: Try to find |A| linearly independent points in a vector space of dimension ns, by somehow “applying the polynomial (t−λ1)⋯(t−λs) to |x∩y|”.

Proof. For each i≤j, let M(i,j) be the ni×nj matrix, with rows indexed by X(i), columns indexed by X(j), with

M(i,j)xy={1if x⊂y0otherwise

for each x∈X(i), y∈X(j).

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Let V be the vector space (over ℝ) spanned by the rows of M(s,r). So dim⁡V≤ns.

For i≤s, consider M(i,s)M(s,r) (note each row belongs to V, as we premultiplied M(s,r) by a matrix). For x∈X(i), y∈X(r):

(M(i,s)M(s,r))xy=# of s-sets z with x⊂z and z⊂y={0if x⁄⊂yr−is−iif x⊂y

So

M(i,s)M(s,r)=r−is−iM(i,r)

so all rows of M(i,r) belong to V.

Let M(i)=M(i,r)⊤⁡M(i,r) (note each row is in V).

For x,y∈X(r), have

M(i)xy=#i-sets z with z⊂x, z⊂y=|x∩y|i

Write the integer polynomial (t−λ1)⋯(t−λs) as ∑⁡i=0saiti, with ai∈ℤ – possible because t(t−1)⋯(t−i+1)=i!ti.

Let M=∑⁡i=0saiM(i) (each row is in V).

Then for all x,y∈X(r):

Mxy=∑iai|x∩y|i=(|x∩y|−λi)⋯(|x∩y|−λs).

So the submatrix of M spanned by the rows and columns corresponding to the elements of A is

(⁄≡00⋯00⁄≡0⋯0⋮⋮⋱⋮00⋯⁄≡0).

Hence the rows of M corresponding to A are linearly independent over ℤp, so also over ℤ, so also over ℚ, so also over ℝ.

So |A|≤dim⁡V≤ns. □

Remark. Do need p prime. Grolmusz constructed, for each n, a value of r≡0(mod6) and a family A⊂[n](r) such that for all distinct x,y∈A we have |x∩y|⁄≡0(mod6) with |A|>nclog⁡n∕ log ⁡ log ⁡n. This is not a polynomial in n.

Corollary 5. Assuming that:

  • A⊂[n](r) with |x∩y|⁄≡r(modp), for each distinct x,y∈A, where p<r is prime

Then |A|≤np−1.

Proof. We are allowed p−1 values of |x∩y|(modp), so done by Frankl-Wilson Theorem. □

Two n2-sets in [n] typically meet in about n4 points – but |x∩y| exactly equaling n4 is very unlikely. But remarkably:

Corollary 6. Assuming that:

  • p is prime, and let A⊂[4p](2p) have |x∩y|≠p for all distinct x,y∈A (“this is not much of a constraint”)

Then |A|≤24pp−1.

Note. 4pp−1 is a tiny (exponentially small) proportion of 4p2p. Indeed, nn∕2∼c⋅2nn (for some c) whereas nn∕4≤2e−n∕322n.

Proof. Halving |A| if necessary, may assume that no x,xc∈A (any x∈[4p](2p)).

Then x,y∈A distinct implies |x∩y|≠0,p, so |x∩y|⁄≡0(modp).

So |A|≤4pp−1 by Corollary 5. □

3.3 Borsuk’s Conjecture

Let S be a bounded subset of ℝn.

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How few pieces can we break S into such that each piece has smaller diameter than that of S?

The example of a regular simplex in ℝn (n+1 points, all at distance 1) shows that we may need n+1 pieces.

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Conjecture (Borsuk’s conjecture (1920s)). n+1 pieces always sufficient.

Known for n=1,2,3. Also known for S a smooth convex body in ℝn or a symmetric convex body in ℝn (convex means x∈S implies −x∈S).

However, Borsuk is massively false:

Theorem 7 (Kahn, Kalai 1995). Assuming that:

  • n∈ℕ

Then there exists bounded S⊂ℝn such that to break S into pieces of smaller diameter we need ≥Cn, for some constant c>1 (not depending on n).

Note.

  • (1) Our proof will show Borsuk’s conjecture (1920s) is false for n≥2000.
  • (2) We’ll prove it for n of the form 4p2, where p is prime. Then done for all n (with a different c, e.g. because there exists a prime p with n2≤p≤n).

Proof. We’ll find S⊂Qn⊂ℝn – in fact S⊂[n](r) for some r. We have already had two genuine ideas from this sentence: first that we think about having S⊂Qn, and second that we go for S⊂[n](r).

Have S⊂[n](r), so ∀⁡x,y∈S:

∥x−y∥2=#coordinates where x and y differ=2(r−|x∩y|).

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So seek S with diameter min⁡|x∩y|=k, but every subset of S with min⁡|x∩y|>k is very small (hence we will need many pieces).

Identify [n] with the edge-set of K4p, the complete graph on 4p points.

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For each x∈[4p](2p) let Gx be the complete bipartite graph, with vertex classes x,xc. Let S={Gx:x∈[4p](2p)}. So S⊂[n](4p2), and |S|=124p2p.

Now

|Gx∩Gy|=|x∩y||xc∩yc|+|xc∩y||x∩yc|=|x∩y|2+|xc∩y|2=d2+(2p−d)2

where d=|x∩y|.

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This is minimised when d=p, i.e. when |x∩y|=p.

Now let S′⊂S have smaller diameter than that of S: say S′={Gx:x∈A}. So must have ∀⁡x,y∈A distinct: |x∩y|≠p (else diameter of S′ is the diameter of S).

Thus

|A|≤24pp−1.

Conclusion: the number of pieces needed is ≥124p2p24pp−1≥c⋅24p∕pe−p∕824p (for some c). This is ≥(c′)p, for some c′>1, which is at least (c″)n for some c″>1. □