Nested cycles with no geometric crossings

By Irene Gil Fernández, Jaehoon Kim, Younjin Kim, and Hong Liu

Abstract

In 1975, Erdős asked the following question: what is the smallest function  for which all graphs with vertices and edges contain two edge-disjoint cycles and , such that the vertex set of is a subset of the vertex set of and their cyclic orderings of the vertices respect each other? We prove the optimal linear bound using sublinear expanders.

1. Introduction

Extremal problems involving cycles have been extensively studied. In particular, what kinds of cycles can we find in graphs with large (but constant) average/minimum degree? A classical result of this sort is the Corradi-Hajnal theorem Reference 3 from 1963, stating that any graph with minimum degree and contains pairwise vertex-disjoint cycles. This was later extended to cycles of the same length. Egawa Reference 4, improving an earlier result of Häggkvist Reference 6, showed that large graphs with minimum degrees contain pairwise vertex-disjoint cycles with the same length. By viewing cycles as minimal graphs of connectivity two or minimum degree two, these results were also generalized in the direction of finding disjoint subgraphs of certain minimum degree or connectivity in Reference 7Reference 11Reference 14Reference 15. See also a result of Verstraëte Reference 16 for vertex-disjoint cycles whose lengths form an arithmetic progression in graphs with large average degree.

In this note, we are interested in finding cycles with geometric constraints. Cycles , …, in a graph are said to be nested cycles if the vertex set of is a subset of the vertex set of for each . If, in addition, their edge sets are pairwise disjoint, we say they are edge-disjoint nested cycles (see Figure 1a). In 1975, Erdős Reference 5 conjectured that there is a constant such that graphs with vertices and at least edges must contain two edge-disjoint nested cycles. Bollobás Reference 1 proved this conjecture and asked for an extension to edge-disjoint nested cycles. This was confirmed later in 1996 by Chen, Erdős and Staton Reference 2, who showed that edge forces edge-disjoint nested cycles.

A stronger conjecture of Erdős that also appeared in Reference 5 is that there exists a constant  such that graphs with vertices and at least edges must contain two edge-disjoint nested cycles such that, geometrically, the edges of the inner cycle do not cross each other; in other words, if , then has no two edges and with . In this case, and  are said to be two nested cycles without crossings (see Figure 1b). The proof of the above nested cycles result of Chen, Erdős and Staton proceeds by finding a cycle in a graph with average degree such that the average degree of the subgraph induced on grows with . One can then iterate this to get nested cycles. This argument, however, does not say anything about the shape of the cycles that can be found in .

Here we prove this conjecture allowing us to find nested cycles without crossings.

Theorem 1.1.

There exists a constant such that every graph with average degree at least has two nested cycles without crossings.

Our proof utilises a notion of sublinear expanders (see Section 2.2), which plays an important role in some recent resolutions of long-standing conjectures; see e.g. Reference 8Reference 9Reference 12Reference 13. Our embedding strategy goes in reverse order. That is, we will find the inner cycle first and then embed the outer cycle in such a way that there is no geometric crossing. This is made possible via a structure we call kraken (see Definition 3.1). The bulk of the work is to construct a kraken in a graph with large but constant average degree.

It would be interesting to see if large constant average degree can also force many nested cycles without crossings. It seems that new ideas are needed for such an extension (if it is true!).

Question 1.2.

Given , does there exist such that every graph with average degree contains nested cycles without geometric crossings?

Organisation

After laying out the tools needed in Section 2, Theorem 1.1 will be proved in Section 3, assuming that we have a kraken on our side on the battlefield. Then in Section 4, we show how to summon such a creature.

2. Preliminaries

For , let , …, . If we claim that a result holds for , it means that there exist positive functions such that the result holds as long as and and . We will not compute these functions explicitly. In many cases, we treat large numbers as if they are integers, by omitting floors and ceilings if it does not affect the argument. We write for the base- logarithm.

2.1. Graph notation

Given a graph , denote its average degree by . Let and be graphs, and . We write for the induced subgraph of on vertex set . Denote by the graph with vertex set and edge set , and write for the induced subgraph , and for the spanning subgraph of obtained from removing the edge set of . For a set of vertices and , the distance in between and a vertex is the length of a shortest path from to ; denote

and write , , and for , let be the ball of radius around . When the underlying graph is clear from the context, we omit the subscript and simply write . For a path , we write for its length, which is the number of edges in the path.

2.2. Sublinear expander

Our proof makes use of the sublinear expander introduced by Komlós and Szemerédi Reference 10. Roughly speaking, a sublinear expander is a graph in which all sets of reasonable size expand by a sublinear factor. This weak expansion and its consequence that large sets are linked by a short path drive our whole embedding argument.

We shall use the following extension by Haslegrave, Kim and Liu Reference 8.

Definition 2.1.

Let and . A graph is an -expander if for all with , and any subgraph with , we have

where

When the parameters and are clear from the context, we will omit them and write simply . Note that when , is decreasing, while is increasing.

Though the expansion rate of the expander above is only sublinear, the advantage of this notion is that every graph contains one such sublinear expander subgraph with almost the same average degree.

Theorem 2.2 (Reference 8, Lemma 3.2).

There exists some such that the following holds for every . Every graph has an -expander subgraph with and .

Thanks to this theorem, by passing to an expander subgraph, it suffices to prove Theorem 1.1 for expanders. A key property Reference 10, Corollary 2.3 of expanders that we will use is that there exists a short path between any two sufficiently large sets. This is formalised in the following statement.

Lemma 2.3.

Let . If is an -vertex -expander, then any two vertex sets , each of size at least , are at distance of at most apart. This remains true even after deleting vertices from .

2.3. Robust expansions

For our proof, we need to be able to expand a set past another set as long as does not interfere with each sphere around too much. The following notion makes this precise.

Definition 2.4.

For and , we say that a vertex set in a graph is -thin around if and, for each ,

As shown in the Lemma 2.6 below, the rate of expansion for every small set is almost exponential in an expander even after deleting a thin set around it. Its proof follows essentially Reference 8, Proposition 3.5.

Proposition 2.5.

Let and . Suppose is an -vertex -expander with , and are sets of vertices with and . Let be a -thin set around in . Then, for each , we have

Proof.

For each , let . As is -thin around in , we obtain that for each ,

Indeed, this follows from the expansion of if ; and if , it follows from . Thus we have and .

Let and define and . We first use induction on to show that for each , . The base case is trivial.

Now for we use Equation 1 together with the induction hypothesis and the facts that is increasing when and to obtain

We may then assume , as when . Now, as is sufficiently large (due to ), we get . Finally, noting that and , we have

as desired.

We will use Lemma 2.6 Reference 13, Lemma 3.12 to find a linear size vertex set with polylogarithmic diameter in while avoiding an arbitrary set of size .

Lemma 2.6.

Let and let be an -vertex -robust-expander with . For any with , there is a set with size at least and diameter at most .

3. Proof of Theorem 1.1

A key structure we use in our proof is a kraken defined below. The idea of the proof is depicted in Figure 2. We embed the desired nested cycles by taking the cycle in a kraken to be the inner cycle and linking the arms of the kraken iteratively to get the outer cycle so that the cyclic orderings of the vertices of both cycles respect each other.

Definition 3.1.

For , a graph is a -kraken if it contains a cycle with vertices , …, (in the order of the cycle ), vertices , , and subgraphs and , where

is a collection of pairwise disjoint sets of size lying in with , each with diameter at most .

is a collection of pairwise internally vertex disjoint paths such that is a path between and of length at most with internal vertices disjoint from .

We usually write a kraken as a tuple , . Lemma 3.2 finds a kraken in any expander with average degree at least some large constant.

Lemma 3.2.

Let and let be an -vertex -expander with . Let be the set of vertices in with degree at least and let . Then, there exists a -kraken , , in for some such that

either ;

or and any distinct are a distance at least apart in .

Proof of Theorem 1.1.

Let be the set of high degree vertices and , , be the kraken as in Lemma 3.2. We will embed, for each , a path between and of length at most , such that all paths are internally pairwise disjoint and also disjoint from and , . Here, indices are taken modulo . Such paths , , together with and , , form the desired nested cycles without crossings.

If the first alternative in Lemma 3.2 occurs, i.e. all , , then we can iteratively find the desired paths , , by linking and avoiding previously built paths and the kraken , using Lemma 2.3. Indeed, the number of vertices to avoid is at most , which is much smaller than the degree of vertices in .

We may then assume that and distinct are at distance at least apart in . Let be the set of vertices not linked to vertices in , i.e. .

For each and with , write . Note that . Recall that . Applying Proposition 2.5 with , we can expand in avoiding to get of size at least , where . Moreover, note that for distinct and with , and are at distance at least apart in ; therefore the corresponding and are disjoint.

Finally, for and with and all and whose corresponding lie in , we can choose pairwise disjoint , each of size . For each , link and in to get a path with length at most using Lemma 2.3, avoiding previously built path and (indices are taken modulo ). The desired path between and can be obtained by extending in .

This concludes the proof.

4. Release the Kraken!

In this section, we prove Lemma 3.2. The idea of the proof is the following. We take a shortest cycle in the graph, and consider two cases depending on whether the set of high degree vertices is large or not. For the case where this set is large, we want to link each vertex on the cycle to two different vertices in by expanding vertices in using Proposition 2.5. If there is a small number of high degree vertices, we will use the fact that the graph has relatively small maximum degree, and so we can find within many large connected sets of vertices that are pairwise far apart. Then we will expand vertices in to link them to these connected sets.

One difficulty here is that the number of paths we need to build to link either high degree vertices or large connected sets to vertices in could be as large as , while the degree of each vertex in could be as small as . We have to be careful when embedding these paths so that no vertex in gets isolated.

Let us first see how we can link vertices on a shortest cycle to high degree vertices in as follows.

Lemma 4.1.

Let and let be an -vertex -expander with . Let be the set of vertices in with degree at least and let . Let be a shortest cycle in with vertices , …, and let be a maximal collection of paths in from to such that:

each is linked to at most vertices in ;

all paths are pairwise disjoint outside of with internal vertices in ;

each path has length at most .

Subject to being maximal, let be minimised.

Let . Then,

(i)

for any vertex that is in less than 2 paths in , the set is -thin around in ; and

(ii)

at least many vertices in are linked to paths in .

Proof.

First of all, due to . Consequently, as there are at most two paths containing each vertex in , we have that . So

Notice that as is a shortest cycle in , for any , we have

for otherwise, replacing the segment of intersecting with a path of length at most in results in a shorter cycle than , contradicting the minimality of .

Let us first prove (i). Suppose is in less than 2 paths in .

Claim 4.2.

is -thin around in .

Proof of Claim 4.2.

Fix first an arbitrary path in . Similar to Equation 3, by the minimality of , we have for any that

Next, fix and consider the set . Let be a path in whose endvertex in is not in (if such a path exists). Notice that

To see this, split into two parts and , with consisting of the nearest vertices to in , and being the remaining ones. If there is a vertex , let be the path between and of length with internal vertices in . Then contains a path between and of length at most with . Replacing the segment between and in (which is of length at least ) with results in a shorter cycle than , a contradiction. So, we must have . If there is , then is at distance at most from in and at distance at least from on , so contains a shorter path between and , contradicting the minimality of . Hence, , as desired.

Let be the set of paths in whose endvertices in are in . By Equation 4 and Equation 5, we see that

This, together with Equation 3, implies that

Therefore, is -thin around as claimed.

Let us now turn to part (ii). Suppose for a contradiction that less than many vertices in are linked to paths in . Then either or and . In both cases, there are a vertex which is in less than paths in and a high degree vertex not linked to any path in . Then, by Claim 4.2, is -thin around in .

Setting and applying Proposition 2.5 with gives

Recall that we have a vertex not in any paths in with degree . Thus, by Lemma 2.3Equation 2 and Equation 6, we can connect  and with a path of length at most in , which extends in to a path between and in with length at most , contradicting the maximality of . Thus, at least many vertices in are linked to paths in as desired.

We are now ready to prove Lemma 3.2.

Proof of Lemma 3.2.

Let and be as in Lemma 4.1. We distinguish two cases depending on how many high degree vertices there are in .

Case 1.

Suppose . Then by Lemma 4.1(ii), at least vertices in are linked in paths in . By the choice of , we see that each vertex in is in exactly paths in . Label the paths so that is the endvertex of in for , and let be the endvertex of in . As vertices in have high degree, we can comfortably choose pairwise disjoint from , each of size , yielding the first alternative.

Case 2.

Suppose . Then by Lemma 4.1(ii) again, we see that every vertex in is linked to a path in , i.e. . Note that . Relabelling if necessary, let be such that , …, are the vertices in that are not linked in to two vertices in . Let

Then, by the definition of , .

Claim 4.3.

There are sets , , each of diameter at most and size , that are at distance at least from each other and from in .

Proof of Claim.

Take a maximal collection of sets , , with the claimed size, which are pairwise far apart and far from in . If , then

Then by Lemma 2.6 with , we can find another large set with small diameter far apart from in , a contradiction.

Let , be the sets from the above claim. For each , let be a connected subset of size , and set . Let be a maximal collection of paths in from to such that

each is in at most two paths of and each set in is linked to at most one path;

all paths are pairwise disjoint outside of with internal vertices in ;

the length of each path is at most .

Subject to being maximal, let be minimised.

Suppose, for contradiction, that there is some which is in less than two paths in . Let be the collection of sets linked to some path in ; then . Let and let , so . Note that , thus taking the subfamily of connected sets that are disjoint from , we have .

By the choice of , the vertex is in less than 2 paths in . Thus, by Lemma 4.1(i), is -thin around in . On the other hand, by the minimality of and , as in Equation 4 and Equation 5, we have for any , for any path , and for each path whose endvertex in is not in (if such a path exists) that

Thus, writing for the set of paths in whose endvertices in are in , we get that

This, together with the fact that is -thin around in , implies that

where the second inequality holds as .

Thus, is -thin around in . Then as in Equation 6, we can expand in . Furthermore, by Claim 4.3, is disjoint from . As is much smaller than and , we can find a path of length at most in between and using Lemma 2.3. Extending this path to yields one more path between and , contradicting the maximality of .

Therefore, each vertex in is in exactly two paths in , and by construction, the non- endvertices of (each in some set ) are pairwise at least apart in . Thus, picking appropriate neighbourhoods of endvertices of in , together with and , yields the second alternative.

Figures

Figure 1.
Figure 1(a)

(a) Two edge-disjoint nested cycles

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Figure 1(b)

(b) Two nested cycles without crossings

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Figure 2.

A -kraken with an inner cycle of length . Each vertex in has two arms attached to it. The arms of the kraken and the (red) paths linking them form the outer cycle.

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Mathematical Fragments

Theorem 1.1.

There exists a constant such that every graph with average degree at least has two nested cycles without crossings.

Lemma 2.3.

Let . If is an -vertex -expander, then any two vertex sets , each of size at least , are at distance of at most apart. This remains true even after deleting vertices from .

Proposition 2.5.

Let and . Suppose is an -vertex -expander with , and are sets of vertices with and . Let be a -thin set around in . Then, for each , we have

Equation (1)
Lemma 2.6.

Let and let be an -vertex -robust-expander with . For any with , there is a set with size at least and diameter at most .

Definition 3.1.

For , a graph is a -kraken if it contains a cycle with vertices , …, (in the order of the cycle ), vertices , , and subgraphs and , where

is a collection of pairwise disjoint sets of size lying in with , each with diameter at most .

is a collection of pairwise internally vertex disjoint paths such that is a path between and of length at most with internal vertices disjoint from .

Lemma 3.2.

Let and let be an -vertex -expander with . Let be the set of vertices in with degree at least and let . Then, there exists a -kraken , , in for some such that

either ;

or and any distinct are a distance at least apart in .

Lemma 4.1.

Let and let be an -vertex -expander with . Let be the set of vertices in with degree at least and let . Let be a shortest cycle in with vertices , …, and let be a maximal collection of paths in from to such that:

each is linked to at most vertices in ;

all paths are pairwise disjoint outside of with internal vertices in ;

each path has length at most .

Subject to being maximal, let be minimised.

Let . Then,

(i)

for any vertex that is in less than 2 paths in , the set is -thin around in ; and

(ii)

at least many vertices in are linked to paths in .

Equation (2)
Equation (3)
Claim 4.2.

is -thin around in .

Equation (4)
Equation (5)
Equation (6)
Claim 4.3.

There are sets , , each of diameter at most and size , that are at distance at least from each other and from in .

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Article Information

MSC 2020
Primary: 05C38 (Paths and cycles), 05C48 (Expander graphs), 05C35 (Extremal problems in graph theory), 05C10 (Planar graphs; geometric and topological aspects of graph theory)
Author Information
Irene Gil Fernández
Mathematics Institute, University of Warwick, Coventry, United Kingdom
irene.gil-fernandez@warwick.ac.uk
Jaehoon Kim
Department of Mathematical Sciences, KAIST, Daejeon, South Korea
jaehoon.kim@kaist.ac.kr
ORCID
MathSciNet
Younjin Kim
Institute of Mathematical Sciences, Ewha Womans University, Seoul, South Korea
younjinkim@ewha.ac.kr
Hong Liu
Mathematics Institute and DIMAP, University of Warwick, Coventry, United Kingdom
h.liu.9@warwick.ac.uk
Additional Notes

The second author was supported by the POSCO Science Fellowship of POSCO TJ Park Foundation and by the KAIX Challenge program of KAIST Advanced Institute for Science-X. The third author was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2017R1A6A3A04005963). The fourth author was supported by the UK Research and Innovation Future Leaders Fellowship MR/S016325/1.

Communicated by
Patricia L. Hersh
Journal Information
Proceedings of the American Mathematical Society, Series B, Volume 9, Issue 3, ISSN 2330-1511, published by the American Mathematical Society, Providence, Rhode Island.
Publication History
This article was received on , revised on , and published on .
Copyright Information
Copyright 2022 by the authors under Creative Commons Attribution 3.0 License (CC BY 3.0)
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  • Show rawAMSref \bib{4377266}{article}{ author={Fern\'andez, Irene}, author={Kim, Jaehoon}, author={Kim, Younjin}, author={Liu, Hong}, title={Nested cycles with no geometric crossings}, journal={Proc. Amer. Math. Soc. Ser. B}, volume={9}, number={3}, date={2022}, pages={22-32}, issn={2330-1511}, review={4377266}, doi={10.1090/bproc/107}, }

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