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Kneser graphs are like Swiss cheese

- Math
- Weizmann Insitute
- More about Ehud Friedgut

- Courant, CS
- New York University
- More about Oded Regev

### Editorial introduction

Kneser graphs are like Swiss cheese, Discrete Analysis 2018:2, 18 pp.

This paper relates two very interesting areas of research in extremal combinatorics: removal lemmas, and influence of variables. A *removal lemma* is a result that states that if S is a set that contains only few copies of a certain structure, then one can remove just a few elements from S to create a set S′ that has no copies of that structure. For instance, the triangle removal lemma states that a graph with few triangles can be approximated by a graph with no triangles. Removal lemmas play a very important role in extremal and additive combinatorics. As for the influence of variables, the aspect that is of interest here is that there are many interesting theorems that state that if a function has a certain property, it must be because in a certain sense it depends on only a few variables. For example, a famous result of the first author shows that if a monotone graph property fails to have a sharp threshold, then the property can be approximated by one for which the minimal graphs that satisfy it are all small, with the result that the “influence” of individual edges on whether the graph has the property is substantial.

The main result of this paper is an “edge removal lemma” for various families of graphs. It states that if G is a graph in one of these families, then for every set X of vertices in G that spans only a few edges one can throw away just a small proportion of X to obtain a subset X′ that is independent. Of course, a result like this is completely false in general: one has only to take a sparse random graph, and then every subset will span few edges but no large subset will be independent. But it is true, for example, for complete bipartite graphs, since a set of vertices that spans a sparse subgraph will have to be contained almost entirely in one of the two vertex sets, and then one can throw away the vertices that are in the other set.

One of the families for which the authors prove an edge-removal lemma is that of Kneser graphs. For 0<m<n/2, the Kneser graph K(n,m) has as its vertex set the set of all subsets of {1,2,…,n} of size m, with two such subsets joined by an edge if and only if they are disjoint. Kneser graphs have large sparse sets, but the natural examples seem to depend on just a few variables: for example, one can take all sets that contain a particular element. (Note that an independent set in K(n,m) is just an intersecting family of m-sets.) The authors wanted to prove a precise conjecture that would say that every set of vertices that spans a sparse subgraph can be approximated by a set of vertices that (i) depends on just a few variables and (ii) spans an independent set. Before this paper a weaker statement was known where instead of (ii) one had a sparse set. In this paper the authors settle the conjecture completely by showing that a sparse set of vertices can be approximated by an independent set of vertices.

The other family of graphs for which the authors prove an edge removal lemma is that of product graphs. If H is a graph, then the product G=Hn is the graph where x and y are joined if for every coordinate i we have that xiyi is an edge of H. (There are different definitions of product graphs, but this is the one to which the result applies: note that it makes it quite hard for two vertices to be joined.) For example, if H is a complete graph on r coordinates, then G=[r]n with two vertices joined if and only if they differ in every coordinate.

The proof of the removal lemma uses ideas from Jacob Fox’s proof of the triangle removal lemma, which obtains the best known bound for that result.

Finally, what has this to do with Swiss cheese? The rough idea is that these graphs have large and highly structured independent sets, and a part of the graph is sparse if and only if it has a big intersection with one of these independent sets. Likewise a Swiss cheese contains lots of large holes, and a region of space contained within the boundary of the cheese will contain only a small amount of cheese if and only if it is almost entirely contained in one of the holes.

^{Article image by G. J. Wanderer and distributed under a CC-BY-NC-SA licence.}