A lower bound on the average degree forcing a minor
Sergey Norin, Bruce Reed, Andrew Thomason, David R. Wood

TL;DR
This paper establishes a lower bound on the average degree needed in a graph to guarantee the presence of a given minor, extending previous results and showing the optimality of certain bounds for sparse graphs.
Contribution
It provides a new lower bound on the average degree that forces a graph to contain a specific minor, generalizing earlier results and confirming the bounds are tight up to a constant.
Findings
Constructs graphs with high average degree avoiding certain minors
Extends previous bounds for complete and dense graphs
Shows bounds are tight up to a constant factor
Abstract
We show that for sufficiently large and for , there is a graph with average degree such that almost every graph with vertices and average degree is not a minor of , where is an explicitly defined constant. This generalises analogous results for complete graphs by Thomason (2001) and for general dense graphs by Myers and Thomason (2005). It also shows that an upper bound for sparse graphs by Reed and Wood (2016) is best possible up to a constant factor.
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A lower bound on the
average degree forcing a minor
Sergey Norin
Department of Mathematics and Statistics, McGill University, Montréal, Canada
,
Bruce Reed
School of Computer Science, McGill University, Montréal, Canada
,
Andrew Thomason
Department of Pure Mathematics and Mathematical Statistics, University of Cambridge, United Kingdom
and
David R. Wood
School of Mathematics, Monash University, Melbourne, Australia
Abstract.
We show that for sufficiently large and for , there is a graph with average degree such that almost every graph with vertices and average degree is not a minor of , where is an explicitly defined constant. This generalises analogous results for complete graphs by Thomason (2001) and for general dense graphs by Myers and Thomason (2005). It also shows that an upper bound for sparse graphs by Reed and Wood (2016) is best possible up to a constant factor.
Norin is supported by NSERC grant 418520. Wood is supported by the Australian Research Council.
1. Introduction
Mader [20] first proved that for every graph , every graph with sufficiently large average degree contains as a minor111A graph is a minor of a graph if a graph isomorphic to can be obtained from a subgraph of by contracting edges.. The natural extremal question arises: what is the least average degree that forces as a minor? To formalise this question, let be the infimum of all real numbers such that every graph with average degree at least contains as a minor. This value has been extensively studied for numerous graphs , including small complete graphs [6, 21, 12, 28, 29], the Petersen graph [11], general complete graphs [21, 14, 15, 5, 2, 30, 31, 23], complete bipartite graphs [3, 24, 17, 19, 16, 18], general dense graphs [25], general sparse graphs [26, 27, 9], disjoint unions of graphs [33, 4, 13], and disjoint unions of cycles [8]; see [32] for a survey.
For complete graphs , the above question was asymptotically answered in the following theorem of Thomason [31], where
[TABLE]
Theorem 1** ([31]).**
Every graph with average degree at least contains as a minor. Conversely, there is a graph with average degree at least that contains no minor. That is,
[TABLE]
Myers and Thomason [25] generalised this result for all families of dense graphs as follows222As is standard, we write that almost every graph with vertices and average degree satisfies property if the probability that a random graph with vertices and average degree satisfies property tends to 1 as ..
Theorem 2** ([25]).**
For every , for all and , for almost every graph with vertices and average degree (and for every -regular graph with vertices),
[TABLE]
Theorem 2 determines for most dense graphs with , but says nothing for sparse graphs , where can be much smaller than . In this regime, Reed and Wood [26, 27] established the following upper bound on .
Theorem 3** ([26, 27]).**
For sufficiently large , and for every graph with vertices and average degree , every graph with average degree at least contains as a minor. That is,
[TABLE]
The purpose of this paper is to show that this result is best possible up to a constant factor. Indeed, we precisely match the lower bounds in the work of Thomason [31] and Myers and Thomason [25], strengthening the lower bound in Theorem 2 by eliminating the assumption that . Informally, we prove that if is large, then almost every with vertices and average satisfies . To state the result precisely, let be the space of random graphs with vertex-set and edges. Thus is the space of random graphs with vertices and average degree .
Theorem 4**.**
For every there exists such that for every integer and for every integer , there is a graph with average degree at least such that if then , and in particular, .
Note that in the proofs of Theorems 1 and 2 the host graph is a random graph of appropriately chosen constant density. Indeed, every such extremal graph is essentially a disjoint union of pseudo-random graphs [23, 25]. However, random graphs themselves are not extremal when is small compared to . Indeed, Alon and Füredi [1] showed that if then, for every graph with vertices and maximum degree , a random graph on vertices (with edge probability ) will almost certainly contain a spanning copy of . To prove Theorem 4, we take to be a blowup of a suitably chosen small random graph. Note that Fox [7] also considers minors of blowups of random graphs. On the face of it, such blowups might not to be pseudo-random, thus contradicting the fact that in many cases the extremal graphs are known to be pseudo-random. But the notion of pseudo-randomness involved is weak, asserting only that induced subgraphs of constant proportion have roughly the same density, and the blowups used here have this property.
Note that Reed and Wood [26] claimed that a lower bound analogous to Theorem 4 followed from the work of Myers and Thomason [25]. However, this claim is invalid. The error occurs in the footnote on page 302 of [26], where Theorem 4.8 and Corollary 4.9 of Myers and Thomason [25] are applied. The assumptions in these results mean that they are only applicable if the average degree of is at least for some fixed , which is not the case here. Also note that Reed and Wood [26] claimed that a lower bound holds for every -regular graph (also as a corollary of the work of Myers and Thomason [25]). This is false, for example, when is the -dimensional hypercube [10].
2. The Proof
We will need the following Chernoff Bound.
Lemma 5** ([22]).**
Let be independent random variables, where each with probability and with probability . Let . Then for ,
[TABLE]
Let be a graph. For , a non-empty set of at most vertices in is called an -set. Two sets and of vertices in are non-adjacent if there is no edge in between and .
Our first lemma gives properties about a random graph.
Lemma 6**.**
Fix and , and let . Then there exists such that for every integer , if and , then there exists a graph with exactly vertices and more than edges, such that for every set of pairwise disjoint -sets in , more than pairs of -sets in are non-adjacent.
Proof.
Let be a graph on vertices, where each edge is chosen independently at random with probability . By Lemma 5, the probability that is less than .
If and are disjoint -sets, then the probability that and are non-adjacent equals . Consider a set of pairwise disjoint -sets in . Let be the number of pairs of elements of that are non-adjacent. Since the elements of are pairwise disjoint, Lemma 5 is applicable and implies that the probability that is at most , which is at most since is sufficiently large.
The number of -sets is . Thus the number of sets of pairwise disjoint -sets is at most . By the union bound, the probability that , for some set of pairwise disjoint -sets, is less than .
Hence with positive probability, edges, and for every set of pairwise disjoint -sets. The result follows. ∎
The next lemma is the heart of our proof.
Lemma 7**.**
Fix and let . Then there exists such that for every integer and for every integer , there is a graph with average degree at least such that such that if then .
Proof.
Let . Choose and let . We assume that is sufficiently large as a function of and to satisfy the inequalities occurring throughout the proof.
Let be the graph from Lemma 6 applied with in place of . Thus and , and for every set of pairwise disjoint -sets in , more than pairs of -sets in are non-adjacent. Call this property .
Let be obtained from by replacing each vertex by an independent set of size
[TABLE]
and replacing each edge of by a complete bipartite graph between and . Note that
[TABLE]
and
[TABLE]
Hence has average degree , as claimed. It remains to show that almost every graph with vertices and average degree is not a minor of .
A blob is a non-empty subset of . A blobbing is an ordered sequence of blobs with total size at most , such that each vertex of is in at most blobs.
The motivation for these definitions is as follows: Suppose that a graph is a minor of and . Then for each vertex of there is a set , such that for distinct , and for every edge of , there is an edge in between and . For each vertex of , let , called the projection of to . Note that , and each vertex of is in at most of . Thus is a blobbing. Also note that by the construction of , if , then there is an edge of between and if and only if there is an edge of between and .
Claim 1**.**
The number of blobbings is at most .
Proof.
For positive integers and for each positive integer , let be the number of -tuples such that is a non-empty subset of for all , and . Below we prove that by induction on . The result follows, since the number of blobbings is at most .
In the base case, , as desired. Now assume the claim for . Observe that
[TABLE]
By induction,
[TABLE]
This completes the proof. ∎
Two blobs are a good pair if they are disjoint and non-adjacent -sets in .
Claim 2**.**
Every blobbing has at least good pairs.
Proof.
Suppose for a contradiction that some blobbing has less than good pairs. Let be the set of blobs such that . Then , implying . Let be the set of blobs in that belong to at most good pairs. Thus the total number of good pairs is at least , implying that and . Let be a maximal subset of such that the blobs in are pairwise disjoint and contain at most good pairs. Then by property of . Let be the set of blobs in that are disjoint from every blob in . Since each blob in intersects at most other blobs, , and for sufficiently large . By the maximality of , every blob in is in a good pair with at least blobs in . So in total there are at least good pairs with and . So some is in more than good pairs, contradicting the definition of . ∎
Let be a graph with . We say that a blobbing is -compatible if for every the blobs and intersect or are adjacent, implying that is not good. As explained above, if is a minor of , then there exists an -compatible blobbing. By Claim 2, if then the probability that a given blobbing is -compatible is at most
[TABLE]
Combining this inequality, Claim 1 and the union bound, if then
[TABLE]
which is less than for sufficiently large . ∎
Proof of Theorem 4..
Choose so that , let , . Let , implying . By Lemma 7, there exists such that for every integer and for every integer , there is a graph with average degree at least such that if then . Since
[TABLE]
the graph satisfies the conditions of the theorem. ∎
We finish with the natural open problem that arises from this work: Can the constant in the upper bound of Reed and Wood [26] be improved to match the lower bound in the present paper? That is, is for every graph with vertices and average degree ?
Note Added in Proof
Following the initial release of this paper, Thomason and Wales [34] announced a solution to the above open problem.
Acknowledgement
This research was partially completed at the Armenian Workshop on Graphs, Combinatorics and Probability, June 2019. Many thanks to the other organisers and participants.
The reference list from the paper itself. Each links out to its DOI / PubMed record.
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