Container method

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The method of (hypergraph) containers is a powerful tool that can help characterize the typical structure and/or answer extremal questions about families of discrete objects with a prescribed set of local constraints. Such questions arise naturally in extremal graph theory, additive combinatorics, discrete geometry, coding theory, and Ramsey theory; they include some of the most classical problems in the associated fields.

These problems can be expressed as questions of the following form: given a hypergraph Template:Math on finite vertex set Template:Math with edge set Template:Math (i.e. a collection of subsets of Template:Math with some size constraints), what can we say about the independent sets of Template:Math (i.e. those subsets of Template:Math that contain no element of Template:Math)? The hypergraph container lemma provides a method for tackling such questions.

History

One of the foundational problems of extremal graph theory, dating to work of Mantel in 1907 and Turán from the 1940s, asks to characterize those graphs that do not contain a copy of some fixed forbidden Template:Math as a subgraph. In a different domain, one of the motivating questions in additive combinatorics is understanding how large a set of integers can be without containing a Template:Math-term arithmetic progression, with upper bounds on this size given by Roth (k=3) and Szemerédi (general Template:Math).

The method of containers (in graphs) was initially pioneered by Kleitman and Winston in 1980, who bounded the number of lattices[1] and graphs without 4-cycles.[2] Container-style lemmas were independently developed by multiple mathematicians in different contexts, notably including Sapozhenko, who initially used this approach in 2002-2003 to enumerate independent sets in regular graphs,[3] sum-free sets in abelian groups,[4] and study a variety of other enumeration problems[5]

A generalization of these ideas to a hypergraph container lemma was devised independently by Saxton and Thomason[6] and Balogh, Morris, and Samotij[7] in 2015, inspired by a variety of previous related work.

Main idea and informal statement

Many problems in combinatorics can be recast as questions about independent sets in graphs and hypergraphs. For example, suppose we wish to understand subsets of integers Template:Math to Template:Math, which we denote by [n] that lack a Template:Math-term arithmetic progression. These sets are exactly the independent sets in the Template:Math-uniform hypergraph H=({1,2,,n},E), where Template:Math is the collection of all Template:Math-term arithmetic progressions in {1,2,,n}.

In the above (and many other) instances, there are usually two natural classes of problems posed about a hypergraph Template:Math:

  • What is the size of a maximum independent set in Template:Math? What does the collection of maximum-sized independent sets in Template:Math look like?
  • How many independent sets does Template:Math have? What does a "typical" independent set in Template:Math look like?

These problems are connected by a simple observation. Let α(H) be the size of a largest independent set of Template:Math and suppose H has i(H) independent sets. Then,

2α(H)i(H)r=0α(H)(|V(H)|r),

where the lower bound follows by taking all subsets of a maximum independent set. These bounds are relatively far away from each other unless α(H) is very large, close to the number of vertices of the hypergraph. However, in many hypergraphs that naturally arise in combinatorial problems, we have reason to believe that the lower bound is closer to the true value; thus the primary goal is to improve the upper bounds on Template:Math.

The hypergraph container lemma provides a powerful approach to understanding the structure and size of the family of independent sets in a hypergraph. At its core, the hypergraph container method enables us to extract from a hypergraph, a collection of containers, subsets of vertices that satisfy the following properties:

  • There are not too many containers.
  • Each container is not much larger than the largest independent set.
  • Each container has few edges.
  • Every independent set in the hypergraph is fully included in some container.

The name container alludes to this last condition. Such containers often provide an effective approach to characterizing the family of independent sets (subsets of the containers) and to enumerating the independent sets of a hypergraph (by simply considering all possible subsets of a container).

The hypergraph container lemma achieves the above container decomposition in two pieces. It constructs a deterministic function Template:Math. Then, it provides an algorithm that extracts from each independent set Template:Math in hypergraph Template:Math, a relatively small collection of vertices SI, called a fingerprint, with the property that SISf(S). Then, the containers are the collection of sets Sf(S) that arise in the above process, and the small size of the fingerprints provides good control on the number of such container sets.

Graph container algorithm

We first describe a method for showing strong upper bounds on the number of independent sets in a graph; this exposition is adapted from a survey of Samotij[8] about the graph container method, originally employed by Kleitman-Winston and Sapozhenko.

Notation

We use the following notation in the below section.

  • G=(V,E) is a graph on |V|=n vertices, where the vertex set is equipped with (arbitrary) ordering {v1,,vn}.
  • Let (G) be the collection of independent sets of Template:Math with size i(G):=|(G)|. Let i(G,r) be the number of independent sets of size Template:Math.
  • The max-degree ordering of a vertex subset AV is the ordering of the vertices in Template:Math by their degree in the induced subgraph G[A].

Kleitman-Winston algorithm

The following algorithm gives a small "fingerprint" for every independent set in a graph and a deterministic function of the fingerprint to construct a not-too-large subset that contains the entire independent set

Fix graph Template:Math, independent set I(G) and positive integer q|I|.

  1. Initialize: let A=V(G),S=.
  2. Iterate for s=1,2,,q:
    • Construct the max-degree ordering of A,(v1,v|A|)
    • Find the minimal index js such that vjsI (i.e. the vertex in Template:Math of largest degree in induced subgraph Template:Math)
    • Let SS{vjs},AA({v1,,vjs}N(vjs)), where N(v) is the neighborhood of vertex v.
  3. Output the vector (j1,,jq) and the vertex set AI.

Analysis

By construction, the output of the above algorithm has property that {vj1,,vjq}I{vj1,,vjq}(AI), noting that AI is a vertex subset that is completely determined by {j1,,jq} and not otherwise a function of I. To emphasize this we will write A=A(j1,,jq). We also observe that we can reconstruct the set S={vj1,,vjq}=S(j1,jq) in the above algorithm just from the vector (j1,,jq).

This suggests that S might be a good choice of a fingerprint and S(j1,jq)A(j1,,jq) a good choice for a container. More precisely, we can bound the number of independent sets of G of some size rq as a sum over output sequences (j1,jq)

i(G,r)=(js)s=1qi(G[A(j1,jq)],rq)(js)(A(j1,jq)rq),

where we can sum across r to get a bound on the total number of independent sets of the graph:

i(G)=r=0q1(nr)+(js)s=1qi(G[A(j1,jq)])r=0q1(nr)+(js)2|A(j1,jq)|.

When trying to minimize this upper bound, we want to pick q that balances/minimizes these two terms. This result illustrates the value of ordering vertices by maximum degree (to minimize |A(j1,jq)|).

Lemmas

The above inequalities and observations can be stated in a more general setting, divorced from an explicit sum over vectors (js).

Lemma 1: Given a graph G with n and assume that integer q and real numbers R,β[0,1] satisfy Reβqn. Suppose that every induced subgraph on at least R vertices has edge density at least β. Then for every integer rq,

i(G,r)(nq)(Rrq).

Lemma 2: Let G be a graph on n vertices and assume that an integer q and reals R,D are chosen such that nR+qD. If all subsets U of at least R vertices have at least D|U|/2 edges, then there is a collection of subsets of q vertices ("fingerprints") and a deterministic function f:𝒞𝒫(V(G)), so that for every independent set IV(G), there is S such that SIf(S)S.

Hypergraph container lemma

Informally, the hypergraph container lemma tells us that we can assign a small fingerprint SI to each independent set, so that all independent sets with the same fingerprint belong to the same larger set, C=f(S), the associated container, that has size bounded away from the number of vertices of the hypergraph. Further, these fingerprints are small (and thus there are few containers), and we can upper bound their size in an essentially optimal way using some simple properties of the hypergraph.

We recall the following notation associated to k uniform hypergraph .

  • Define Δl():=max{dH(A)AV(),|A|=l} for positive integers 1lk, where d(A)=|{eE()Ae}|.
  • Let () be the collection of independent sets of . I will denote some such independent set.

Statement

We state the version of this lemma found in a work of Balogh, Morris, Samotij, and Saxton.[9]

Let be a k-uniform hypergraph and suppose that for every l{1,2,,k} and some b,r, we have that Δl(H)(b|V(H)|)l1|E(H)|r. Then, there is a collection 𝒞𝒫(V(H)) and a function f:𝒫(V(H))𝒞 such that

  • for every I(H) there exists SI with |S|(k1)b and If(S).
  • |C||V(H)|δr for every C𝒞 and δ=2k(k+1).

Example applications

Regular graphs

Upper bound on the number of independent sets

We will show that there is an absolute constant Template:Math such that every n-vertex d-regular graph G satisfies i(G)2(1+Clogdd)n2.

We can bound the number of independent sets of each size r by using the trivial bound i(G,r)(nr)(nn/10)20.48n for rn/10. For larger r, take β>10/n,q=1/β,R=n2+βn22d. With these parameters, Template:Math-regular graph G satisfies the conditions of Lemma 1 and thus,

i(G,r)(nq)(Rrq)(nq)(n2+βn22drq)(enq)q(n2+βn22drq)(eβn)1/β(n2+βn22drq).

Summing over all 0rn gives

i(G)20.49n+2n2+βn22d+1/βlog2(eβn),

which yields the desired result when we plug in β=dlogd/n.

Sum-free sets

A set A of elements of an abelian group is called sum-free if there are no x,y,zA satisfying x+y=z. We will show that there are at most 2(1/2+o(1))n sum-free subsets of [n]:={1,2,,n}.

This will follow from our above bounds on the number of independent sets in a regular graph. To see this, we will need to construct an auxiliary graph. We first observe that up to lower order terms, we can restrict our focus to sum-free sets with at least n2/3 elements smaller than n/2 (since the number of subsets in the complement of this is at most (n/2)n2/32n/2+1).

Given some subset S{1,2,,n/21}, we define an auxiliary graph GS with vertex set [n] and edge set {{x,y}x+sy(modn) for some sS(S)}, and observe that our auxiliary graph is 2|S| regular since each element of Template:Math is smaller than n/2. Then if SA are the smallest n2/3 elements of subset A[n], the set ASA is an independent set in the graph GSA. Then, by our previous bound, we see that the number of sum-free subsets of [n] is at most

(n/2)n2/32n/2++(n/2n2/3)2(1+O(n1/3logn))n22(1/2+O(n1/3logn))n.

Triangle-free graphs

We give an illustration of using the hypergraph container lemma to answer an enumerative question by giving an asymptotically tight upper bound on the number of triangle-free graphs with n vertices.[10]

Informal statement

Since bipartite graphs are triangle-free, the number of triangle free graphs with n vertices is at least 2n2/4, obtained by enumerating all possible subgraphs of the balanced complete bipartite graph Kn/2,n/2.

We can construct an auxiliary Template:Math-uniform hypergraph Template:Math with vertex set V(H)=E(Kn) and edge set E(H)={{e1,e2,e3}E(Kn)=V(H)e1,e2,e3 form a triangle}. This hypergraph "encodes" triangles in the sense that the family of triangle-free graphs on n vertices is exactly the collection of independent sets of this hypergraph, (H).

The above hypergraph has a nice degree distribution: each edge of Kn, and thus vertex in V(H) is contained in exactly n2 triangles and each pair of elements in V(H) is contained in at most 1 triangle. Therefore, applying the hypergraph container lemma (iteratively), we are able to show that there is a family of nO(n3/2) containers that each contain few triangles that contain every triangle-free graph/independent set of the hypergraph.

Upper bound on the number of triangle-free graphs

We first specialize the generic hypergraph container lemma to 3-uniform hypergraphs as follows:

Lemma: For every c>0, there exists δ>0 such that the following holds. Let H be a 3-uniform hypergraph with average degree d1/δ and suppose that Δ1(H)cd,Δ2(H)cd. Then there exists a collection 𝒞𝒫(V(H)) of at most |𝒞|(|V(H)||V(H)|/d) containers such that

  • for every I(H), there exists IC𝒞
  • |C|(1δ)|V(H)| for all C𝒞

Applying this lemma iteratively will give the following theorem (as proved below):

Theorem: For all ϵ>0, there exists C>0 such that the following holds. For each positive integer Template:Math, there exists a collection 𝒢 of graphs on Template:Math vertices with |𝒢|nCn3/2 such that

  • each G𝒢 has fewer than ϵn3 triangles,
  • each triangle-free graph on n vertices is contained in some G𝒢.

Proof: Consider the hypergraph H defined above. As observed informally earlier, the hypergraph satisfies |V(H)|=(n2),Δ2(H)=1,d(v)=n2 for every vV(H). Therefore, we can apply the above Lemma to H with c=1 to find some collection 𝒞 of nO(n3/2) subsets of E(Kn) (i.e. graphs on n vertices) such that

  • every triangle free graph is a subgraph of some C𝒞,
  • every C𝒞 has at most (1δ)(n2) edges.

This is not quite as strong as the result we want to show, so we will iteratively apply the container lemma. Suppose we have some container C𝒞 with at least ϵn3 triangles. We can apply the container lemma to the induced sub-hypergraph H[C]. The average degree of H[C] is at least 6ϵn, since every triangle in C is an edge in H[C], and this induced subgraph has at most (n2) vertices. Thus, we can apply Lemma with parameter c=1/ϵ, remove C from our set of containers, replacing it by this set of containers, the containers covering (H[C]).

We can keep iterating until we have a final collection of containers 𝒞 that each contain fewer than ϵn3 triangles. We observe that this collection cannot be too big; all of our induced subgraphs have at most (n2) vertices and average degree at least 6ϵn, meaning that each iteration results in at most nO(n3/2) new containers. Further, the container size shrinks by a factor of 1δ each time, so after a bounded (depending on ϵ) number of iterations, the iterative process will terminate.

See also

Independent set (graph theory)
Szemerédi's theorem
Szemerédi regularity lemma

References

Template:Reflist