1 Combinatorial methods

Definition 1.1 (Sumset). Let G be an abelian group. Given A,BG, define the sumset A+B to be

A+B:={a+b:aA,bB}

and the difference set AB to be

AB:={a+b:aA,bB}.

If A and B are finite, then certainly

max{|A|,|B|}|A+B||A||B|.

Example 1.2. Let A=[n]:={1,2,,n}. Then

|A+A|=|{2,,2n}|=2n1=2|A|1.

Lemma 1.3. Assuming that:

  • A is finite.

Then |A+A|2|A|1, with equality if and only if A is an arithmetic progression.

Proof. Let A={a1,a2,,an} with a1<a2<<an. Then

a1+a1<a1+a2<a1+a2<<a1+an<a2+an<<an+an,

so |A+A|2|A|1. But we could also have written

a1+a1<a1+a2<a2+a2<a2+a3<a2+a4<<a2+an<a3+an<<an+an.

When |A+A|=2|A|1, these two orderings must be the same. So a2+ai=a1+ai+1 for all i=2,,n1.

Exercise: If A,B, then |A+B||A|+|B|1 with equality if and only if A and B are arithmetic progressions with the same common difference.

Example 1.4. Let A,Bp with p prime. Then |A+B|p+1A+B=p. Indeed, gA+BA(gB) (note that gB means {g}B). But gp,

|A(gB)|=|A|+|gB||A(gB)||A|+|B|p1.

Theorem 1.5 (Cauchy-Davenport). Assuming that:

  • p is a prime

  • A,Bp nonempty

Then
|A+B|min{p,|A|+|B|1}.

Proof. Assume |A|+|B|p+1. Without loss of generality assume that 1|A||B| and that 0A. Apply induction on |A|. The case |A|=1 is trivial. Suppose |A|2, and let 0aA.

Since {a,2a,3a,,(p1)a,pa}=p and |A|+|B|p+1, there must exist m0 such that maB but (m+1)aB. Let B=Bma, so 0B, aB, |B|=|B|.

But 1|AB|<|A|, so the inductive hypothesis applies to AB and AB. Since

(AB)+(AB)A+B,

we have

|A+B|=|A+B||(AB)+(AB)||AB|+|AB|+1=|A|+|B|+1.

This fails for general abelian groups (or even general cyclic groups).

Example 1.6. Let p be (fixed, small) prime, and let V𝔽pn be a subspace. Then V+V=V, so |V+V|=|V|. In fact, if A𝔽pn is such that |A+A|=|A|, then A must be a coset of a subspace.

Example 1.7. Let A𝔽pn be such that |A+A|<32|A|. Then there exists V𝔽pn a subspace such that |V|<32|A| and A is contained in a coset of V. See Example Sheet 1.

Definition 1.8 (Ruzsa distance). Given finite sets A,BG, we define the Ruzsa distance d(A,B) between A and B by

d(A,B)=log|AB||A||B|

Note that this is symmetric, but is not necessarily non-negative, so we cannot prove that it is a metric. It does, however, satisfy triangle inequality:

Lemma 1.9 (Ruzsa’s triangle inequality). Assuming that:

  • A,B,CG finite

Then
d(A,C)d(A,B)+d(B,C).

Proof. Observe that

|B||AC||AB||BC|.

Indeed, writing each dAC as d=adcd with adA, cdC, the map

ϕ:B×(AC)(AB)×(BC)(b,d)(adb,bcd)

is injective. The triangle inequality now follows from the definition.

Definition 1.10 (Doubling / difference constant). Given a finite AG, we write

σ(A):=|A+A||A|

for the doubling constant of A and

δ(A):=|AA||A|

for the difference constant of A.

Then Lemma 1.9 shows, for example, that

logδ(A)=d(A,A)d(A,A)+d(A,A)=2 log σ(A).

So δ(A)σ(A)2, or |AA||A+A|2|A|.

Notation. Given AG and l,m0, we write

lAmA:=A+A++Al timesAAAm times.

Theorem 1.11 (Plunnecke’s Inequality). Assuming that:

  • A,BG are finite sets

  • |A+B|K|A| for some K1

Then l,m0,
|lBmB|Kl+m|A|.

Proof. Choose a non-empty subset AA such that the ratio |A+B||A| is minimised, and call this ratio K. Then |A+B|=K|A|, KK, and AA, |A+B|K|A|.

Claim: For every finite CG, |A+B+C|K|A+C|.

Let’s complete the proof of the theorem assuming the claim. We first show that m0, |A+mB|Km|A|. Indeed, the case m=0 is trivial, and m=1 is true by assumption. Suppose m>1 and the inequality holds for m1. By the claim with C=(m1)B, we get

|A+mB|=|A+B+(m1)B|K|A+(m1)B|Km|A|.

But as in the proof of Ruzsa’s triangle inequality, l,m0, we can show

|A||lBmB||A+lB||A+mB|Kl|A|Km|A|=Kl+m|A|2.

Hence |lBmB|Kl+m|A|Kl+m|A|, which completes the proof (assuming the claim).

We now prove the claim by induction on |C|. When |C|=1 the statement follows from the assumptions. Suppose the claim is true for C, and consider C=C{x} for some xC. Observe that

A+B+C=(A+B+C)+((A+B+x)(D+B+x))

with D={aA:a+B+xA+B+X}.

By definition of K, |D+B|K|D|, so

|A+B+C||A+B+C|+|A+B+x||D+B+x|IHK|A+C|+K|A|K|D|=K(|A+C|+|A||D|)

We apply this argument a second time, writing

A+C=(A+C)((A+x)(E+x))

where E={aA:a+xA+C}D. We conclude that

|A+C|=|A+C|+|A+x||E+x||A+C|+|A||D|

so

|A+B+C|K(|A+C|+|A||D|)K|A+C|,

proving the claim.

We are now in a position to generalise Example 1.7.

Theorem 1.12 (Freiman-Ruzsa). Assuming that:

  • A𝔽pn

  • |A+A|K|A| (i.e. σ(A)K)

Then A is contained in a subspace H𝔽pn of size |H|K2pK4|A|.

Proof. Choose X2AA maximal such that the translates x+A with xX are disjoint. Such a set X cannot be too large: xX, x+A3AA, so by Plunnecke’s Inequality, since |3AA|K4|A|,

|X||A|=|xX(x+A)||3AA|.

So |X|K4. We next show

2AAX+AA.(∗)

Indeed, if y2AA and yX, then by maximality of X, y+Ax+A for some xX (and if yX, then clearly yX+AA).

It follows from () by induction that l2,

lAA(l1)X+AA,(∗∗)

since

lAA=A+(l1)AA(l2)X+AA(l2)X+2AAX+AA(l1)X+AA.

Now let H𝔽pn be the subgroup generated by A, which we can write as

H=l1(lAA)()Y+AA

where Y𝔽pn is the subgroup generated by X.

But every element of Y can be written as a sum of |X| elements of X with coefficients amongst 0,1,,p1, hence |Y|p|X|pK4. To conclude, note that

|U||Y||AA|pK4pK4K2|A|,

where we use Plunnecke’s Inequality or even Ruzsa’s triangle inequality.

Example 1.13. Let A=VR where V𝔽pn is a subspace of dimension KdnK and R consists of K1 linearly independent vectors not in V.

Then

|A|=|VR|=|V|+|R|=pnk+K1pnk=|V|

and

|A+A|=|(VR)+(VR)|=|V(V+R)(R+R)|K|V|.

But any subspace K𝔽pn containing A must have size at least pnK+(K1)|V|pK, so the exponential dependence on K is necessary.

Theorem 1.14 (Polynomial Freiman-Ruzsa, due to Gowers–Green–Manners–Tao 2024). Assuming that:

  • A𝔽pn

  • |A+A|K|A|

Then there exists a subspace K𝔽pn of size at most C1(K)|A| such that for some x𝔽pn,
|A(x+K)||A|C2(K),

where C1(K) and C2(K) are polynomial in K.

Proof. Omitted, because the techniques are not relevant to other parts of the course. See Entropy Methods in Combinatorics next term.

Definition 1.15. Given A,BG we define the additive energy between A and B to be

E(A,B)=|{(a,a,b,b)A×A×B×B:a+b=a+b}|.

We refer to the quadruples (a,a,b,b) such that a+b=a+b as additive quadruples.

Example 1.16. Let V𝔽pn be a subspace. Then E(V)=E(V,V)=|V|3.

On the other hand, if Ap is chosen at random from p (each element chosen independently with probability α>0), then with high probability

E(A)=E(A,A)=α4p3=α|A|3.

Lemma 1.17. Assuming that:

  • A,BG

  • both non-empty

Then
E(A,B)|A|2|B|2|A+B|.

Proof. Define rA+B(x)=|{(a,b)A×B:a+b=x}| (and notice that this is the same as |A(xB)|). Observe that

E(A,B)=|{(a,a,b,b)A2×B2:a+b=a+b}=xGrA+B(x)2=xA+BrA+B(x)2(xA+BrA+B(x))2|A+B|by Cauchy-Schwarz

but

xG|A(xB)|=xGyG𝟙A(y)𝟙xB(y)=xGyG𝟙A(y)𝟙B(xy)=|A||B|

(As usual, 𝟙A here means the indicator function).

In particular, if |A+A|K|A|, then

E(A)=E(A,A)|A|4|A+A||A|3K.

The converse is not true.

Example 1.18. Let G be your favourite (class of) abelian group(s). Then there exist constants 𝜃,η>0 such that for all sufficiently large n, there exists AG, with |A|n satisfying E(A)η|A|3 and |A+A|𝜃|A|2.

Theorem 1.19 (Balog–Szemeredi–Gowers, Schoen). Assuming that:

  • AG is finite

  • E(A)η|A|3 for some η>0

Then there exists AA of size at least c1(η)|A| such that |A+A||A|c2(η), where c1(η) and c2(η) are polynomial in η.

Idea: Find AA such that a,bA such that ab has many representations as (a1a2)+(a3a4) with aiA.

We first prove a technical lemma, using a technique called “dependent random choice”.

Definition 1.20 (gamma-popular differences). Given AG and γ>0, let

Pγ={xG:|A(x+A)|γ|A|}

be the set of γ-popular differences of A.

Lemma 1.21. Assuming that:

  • AG is finite

  • E(A)η|A|3

  • c>0

Then there is a subset XA of size |X|η|A|3 such that for all but a (16c)-proportion of pairs (a,b)X2, abPcη.

Proof. Let U={xG:|A(x+A)|12η|A|}. Then

xU|A(x+A)|2=12η|A|x|A(x+A)|=12η|A|3=12E(A)

For 0ilog2η1, let

Qi={xG:|A|2i+1<|A(x+A)||A|2i},

and set δi=η122i. Then

iδi|Qi|=i|Qi|η22i=1η|A|2i|A|222i|Qi|=1η|A|2i|A|222ixU𝟙{|A|2i+1<|A(x+A)||A|2i}1η|A|2xU|A(x+A)|21η|A|212E(A)(xU|A(x+A)|212E(A))=12|A|()

Let S={(a,b)A2:abPcη}. Then

i(a,b)S|(Aa)(Ab)Qi|(a,b)S|(Aa)(Ab)|=|A(ab+A)|cη|A|by definition of S|S|cη|A|cη|A|32cη|A|212|A|()2cη|A|2iδi|Qi|

Hence there exists i0 such that

(a,b)S|(Aa)(Ab)Qi0|2cη|A|2δi0|Qi0|.

Let Q=Qi0, δ=δi0, λ=2i0. So

(a,b)S|(Aa)(Ab)Q|2cηδ|A|2|Q|.(∗∗)

Find x such that X=|A(A+x)| is large.

Given xG, let X(x)=A(x+A). Then

𝔼xQ|X(x)|=1|Q|xQ|A(x+A)|12λ|A|.

Let T(x)={(a,b)X(x)2:abPcη}. Then

𝔼XQ|T(x)|=𝔼xQ|{(a,b)(A(xxAaAb+A))2:abPcη}|=1|Q|xQ|{(a,b)S:xAaAb}|=1|Q|(a,b)S|(Aa)(Ab)Q|1|Q|2cη|A|2δ|Q|=2cηδ|A|2=2cλ2|A|2

Therefore,

𝔼xQ|X(x)|2(16c)1|T(x)|C-S(𝔼xQ|X(x)|)2(16c)1𝔼xQ|T(x)|(λ2)2|A|2(16c)12cλ2|A|2=(λ24λ28)|A|2=λ28|A|

So there exists xQ such that |X(x)|2λ28|A|2, in which case we have

|X|λ8|A|η3|A|

and |T(x)|16c|X|2.

Proof of Theorem 1.19. Given AG with E(A)η|A|3, apply Lemma 1.21 with c=27 to otain XA of size |X|η3|A| such that for all but 18 of pairs (a,b)X2, abPη27. In particular, the bipartite graph

G=(X˙X,{(x,y)X×X:xyPη27})

has at least 78|X|2 edges. Let A={xX:deg(x)34|X|}.

PIC

Clearly, |A||X|8. For any a,bA, there are at least |X|2 elements yX such that (a,y),(b,y)E(G) (ay,byPη27).

Thus ab=(ay)(by) has at least

η6|A|choices for yη27|A|η27|A|η3217|A|3

representations of the form a1a2(a3a4) with aiA.

It follows that

η3217|A|3|AA||A|4|AA|217η3|A|222η4|A|

Thus |A+A|244η8|A|.