A general theorem in spectral extremal graph theory
Abstract
The extremal graphs and spectral extremal graphs are the sets of graphs on vertices with maximum number of edges and maximum spectral radius, respectively, with no subgraph in . We prove a general theorem which allows us to characterize the spectral extremal graphs for a wide range of forbidden families and implies several new and existing results. In particular, whenever contains the complete bipartite graph (or certain similar graphs) then contains the same graph when is sufficiently large. We prove a similar theorem which relates and , the set of -free graphs which maximize the spectral radius of the matrix , where is the adjacency matrix and is the diagonal degree matrix.
1 Introduction
For a family of graphs and , we define , , and to be the maximum number of edges, maximum spectral radius of the adjacency matrix, and maximum spectral radius of the matrix respectively over all -vertex graphs which do not contain any as a subgraph. Here where is the diagonal degree matrix and is the adjacency matrix. So and is one half of the maximum spectral radius of the signless Laplacian over -free graphs. As is standard, we define , , and as the set of extremal graphs for each respective function, and we call the graphs in each set (edge) extremal, spectral extremal, and alpha spectral extremal, respectively. When is a single graph we use the standard notation instead of and similarly with the other functions. If the family of extremal graphs consists of a single graph we will write instead of , and similarly with the other functions. Our goal in this paper is to prove general theorems which capture many previous and new results on these parameters.
Spectral extremal graph theory has become very popular recently. Several sporadic results appeared over the years, for example results of Wilf [59] and Nosal [54], before the field was studied systematically. All results in the area which regard the adjacency matrix can be understood under the general framework of Brualdi-Solheid problems [4], where one seeks to maximize the spectral radius of the adjacency matrix over a family of graphs. When the family is defined by a forbidden subgraph, this problem has a Turán-type flavor, and the spectral Turán problem was introduced systematically by Nikiforov [50]. Since then many papers have been written, and we refer to the excellent recent survey [41]. We also note that there are hypergraph versions of these problems (see for example [37, 52]), but we only consider graphs in this paper.
Researchers have also frequently considered other matrices besides the adjacency matrix. Signless Laplacian versions of Brualdi-Solheid problems were studied extensively and Nikiforov introduced the matrix as a way to merge these two theories [53].
With so much recent activity in this area, we believe that it is valuable to have general theorems that apply to families of forbidden graphs. One question that naturally presents itself when reviewing previous results is: when are the edge-extremal graphs the same as the spectral-extremal graphs? That is, when do and either coincide or overlap?
Some of the first results in the area suggest that perhaps the problems are the same. For example, the spectral Turán theorem [47] shows , and [48] shows that for large enough . Furthermore, for any non-bipartite , the theorems in [21, 22, 49] show that the asymptotics of the two functions coincide. However, the two problems can also be vastly different, for example when is an even cycle [13, 50, 61, 62]. One might then guess that there is a difference between bipartite and non-bipartite, but it is a bit more subtle than that. In [15], it was shown that when forbidding large enough odd wheels the two extremal families have similar structure but are in fact disjoint.
Hence we seek general criteria which can determine whether the extremal families overlap or not. One such very nice result is in [58], proving a conjecture in [15], where it was shown that for any graph such that any graph in is a Turán graph plus edges, then for large enough one has that . Another very nice paper proving general results about trees was written [23].
In this paper we prove some general results which apply to many forbidden graphs or families. As special cases of our theorems, we recover results from [7, 8, 9, 10, 11, 12, 14, 16, 23, 27, 28, 35, 39, 40, 43, 44, 50, 55, 56, 60, 64, 65] and additionally we can apply the theorems to prove several new results. More details about specific applications are given after statements of our theorems.
When studying a classical Turán-type problem, every edge increases the objective function by the same amount. But when trying to determine , some edges will contribute more to the spectral radius than others, and so vertices of large degree are incentivized. When , the presence of the diagonal degree matrix incentivizes large degree vertices even further. This paper is an attempt to formalize this phenomenon.
The rest of this paper is organized as follows. In the rest of Section 1 we define our notation and state our main results. In Section 2 we prove results relating and . In Section 3, we prove results relating and . In Section 4 we give concluding remarks.
1.1 Notation
For graphs and , denotes the complement of , denotes the join of and , denotes their disjoint union, and denotes the disjoint union of copies of ; if then this means countably many copies. We write if is a subgraph of . We write for the maximum degree of . We write for the adjacency matrix, for the diagonal degree matrix, and . For a symmetric matrix we use to mean the largest eigenvalue of the matrix, and for a graph we write and for and , respectively. For and , we write for the neighborhood of , for , and for . For , we write for the set of vertices at distance from . For , we write for , and for ; we write and for the corresponding sets of edges. We write for the subgraph induced by and if we write for the bipartite subgraph on vertices and with all edges in between and . Our notation for specific classes of graphs is standard; we note that denotes the path of order , is a maximum matching on vertices, and means that the larger partite set has a countable set of vertices. Sometimes we will consider the graph on vertices which is the disjoint union of a maximum number of copies of , plus isolated vertices in the remainder, and we will call this the maximal union of .
Let be a family of graphs and let be a graph. We denote by the maximum number of edges in an -free graph which contains a copy of , and we write for the corresponding extremal graphs. We write for the connected extremal number of , the maximum number of edges in a connected -free graph, and for the set of corresponding extremal graphs.
1.2 Main results
Our first goal is to relate the extremal graphs and spectral extremal graphs. In [63] it was proven that, if or , then if is large enough. The following theorem generalizes this result (see the discussion following Proposition 1.2.)
Theorem 1.1.
Let be a family of graphs. Suppose that , is not -free, and for large enough , where one of the following holds:
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(a)
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(b)
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(c)
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(d)
where for some and is finite
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(e)
where for some and is finite
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(f)
(e) holds, all but a bounded number of vertices of have constant degree , is not -free.
If (a), (b), or (c) holds then for large enough, .
If (d) or (f) holds then for large enough, .
If (e) holds then for large enough all graphs in are of the form , where and is bounded in terms of .
We make two remarks about Theorem 1.1. First, we show in Section 2 any graph satisfying (d) must have for some . Secondly, Theorem 1.1 (d) is sharp in that it fails if . The reason is that there are two non-isomorphic trees of order .
Proposition 1.2.
There exists a finite family of graphs such that , where , and for infinitely many , .
We now turn to applications. We would like to make use of the existing literature on the extremal functions and . Thus, note that if or then , and moreover in cases (a)-(d) or else if , we have that is not -free. Furthermore it is not too difficult to show that if then . This implies that in such cases, if we replace the assumption “ and ” in Theorem 1.1 with either “” or “,” then we obtain a special case of the result, which generalizes Theorem 1.7 of [63].
Corollary 1.3.
Suppose that is a family of graphs such that, for large enough, (or ), where is one of the graphs in (a)-(d) or (f) of Theorem 1.1, and moreover that is finite in cases (d) and (f) and in case (f). Then for large enough, (or ).
We list some applications of Theorem 1.1 and Corollary 1.3. All of our results only apply when is large enough, and this condition is assumed everywhere in the list below. The literature for specific families contains many results with a specific lower bound on the ‘large enough’ , and thus our results do not always imply the quantitative part of the results that we mention.
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Star forests. Lidicky, Liu, and Palmer [42] investigated the extremal number of , where and . In this case it is possible that Note that , where is an almost -regular graph; ; and is not -free. Thus Theorem 1.1 (f) gives that . Then one can show using equitable partitions that if is even, we actually have . This was shown by Chen, Liu, and Zhang [9].
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Trees. At the same time that we were finishing this paper Fang, Lin, Shu, and Zhang [23] proved several theorems studying trees. These include the results listed below about “certain small trees”. Our result below about “almost all trees” is complementary to the results in [23]; their results determine for which trees but the characterization is phrased in terms of coverings and the extremal number of a decomposition-like family.
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Certain small trees. Caro, Patkós and Tuza [6] determined for many small trees . Let denote the spider obtained by identifying paths of orders at one endpoint, and let denote the double star on vertices whose two non-leaf vertices have degrees and . Let be the graph obtained by attaching a leaf to a leaf of . Among their results there are some to which we can apply Theorem 1.1 which are not already mentioned above: (i) ; (ii) ; (iii) ; (iv) ; (v) ; (vi) .
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Almost all trees. Let be a tree with proper coloring , where , such that contains a vertex of degree at least 3, exactly one of whose neighbors is not a leaf. (In the proof of Proposition 1.4 we will show that ‘almost all trees’ indeed have this property.) It is well-known that . Observe that is -free. To show it is -saturated, it remains to show that adding any edge to creates a copy of . Let be the partite sets with . Since has a leaf, , or else we could embed in by placing this leaf incident to an edge in and placing the rest of in . To show , suppose has an edge. Then we can embed in by placing at least 2 leaves of in and the rest of in , a contradiction. Thus, Theorem 1.1 (a) gives .
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Spectral Erdős-Sós theorem. Note that contains all trees on vertices if and only if is not -free, where is the set of all graphs which contain all trees on vertices. Note that (see e.g. Lemma 4.6 of [14]). Thus, we have . Similarly, if is the set of all graphs which contain all trees on vertices, then . These results were shown by Cioabă and the second and third authors [14].
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Long cycles. Let be the set of cycles of length at least . Note if is odd and if is even, where ; this can be viewed as a special case of a result of Kopylov [38]. Erdős and Gallai [18] showed that . Thus, if is odd and if is even. This result was shown by Gao and Hou [28]. In fact, the result also follows from the spectral even cycle theorem [13], but we have included it to demonstrate the versatility of Theorem 1.1.
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Arithmetic progression of cycles. Let be the set of cycles of length modulo , . Bollobás [3] showed that . Thus, if is even and at least 5, then and if are both odd then . The first result follows from the spectral even cycle theorem, while the second one appears to be new.
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Interval of even cycles. Note that contains consecutive even cycle lengths if and only if is not -free, where is the set of all graphs which contain consecutive even cycle lengths. Verstraëte [57] proved that . Thus, . This result appears to be new.
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Disjoint equicardinal cycles. Let be the set of all disjoint unions of two cycles of the same length. Häggkvist [33] showed the . Thus, . This result appears to be new.
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Minors. Note that is -minor free if and only if is -free, where is the set of all graphs which have an -minor. Suppose that is -saturated; then , because has a -minor. Mader [46] showed that . Thus . We list below some special cases.
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The -minor free spectral extremal graph is . This was shown by the third author [55].
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If is obtained by deleting from the edges of disjoint paths, not all of order 3, then the -minor free spectral extremal graph is . This was shown recently by Chen, Liu, and Zhang [12].
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If is the friendship graph with triangles then the -minor free spectral extremal graph is . This was shown by He, Li, and Feng [35].
If then holds automatically, without making use of Theorem 1.1. The same applies to .
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Topological subdivisions. The extremal result of [46] is actually stronger than as stated in the application above; it applies even when is the family of all topological subdivisions of . A similar argument to the minor case then proves the following: if is the family of all topological subdivisions of , and is -saturated then .
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Two disjoint chorded cycles. Let be the family of all graphs made of two disjoint cycles, one of which has a chord, and let be the family of all graphs made of two disjoint chorded cycles. Bialostocki, Finkel, and Gyárfás [2] showed that and . Thus and . This result appears to be new.
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Disjoint chorded cycles. Let be the family of all graphs made of disjoint chorded cycles. The result of Gao and Wang [30] implies that via a well-known bound on max cut. Thus, . This result appears to be new.
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Multiply chorded cycles. Let be the family of all cycles with chords, . Gould, Horn, and Magnant [31] showed that . Thus, . This result appears to be new.
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Cycles with incident chords. Let be the family of cycles with chords all incident to the same vertex. Jiang [36] showed that . Thus, . This result appears to be new.
Proposition 1.4.
The proportion of all labelled -vertex trees such that for some , for large enough, approaches as .
Our second goal is to relate the spectral extremal graphs and alpha spectral extremal graphs.
Theorem 1.5.
Let be a family of graphs containing some bipartite graph for which is a forest, or such that . Suppose that for large enough, , where either:
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(a)
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(b)
.
Then for any , for any large enough, .
We give a list of new and existing results implied by Theorem 1.5; if no reference is given for the required spectral result that means that it falls under the previous list of applications.
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Paths. We have and . This was shown by Chen, Liu, and Zhang [11].
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Matchings. We have . This was shown by Yuan and Shao [60].
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Linear forests. Generalizing the previous two results: if where , , and at least one , then if some is even and if all are odd, where . This was shown by Chen, Liu, and Zhang [11].
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Certain small trees. We have (i) ; (ii) ; (iii) . These results appear to be new.
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Spectral Erdős-Sós theorem. Let be the set of all graphs which contain all trees on vertices, and let be the set of all graphs which contain all trees on vertices. Then and . These results were shown by Chen, Li, Li, Yu, and Zhang [7].
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Intersecting even cycles. Let be obtained by intersecting the cycles at a unique vertex. The second author [17] showed that if and some , then , where . Thus, . This result appears to be new.
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Long cycles. If then if is odd and if is even, where . This result is implied by the result forbidding even cycles or consecutive cycles.
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Arithmetic progression of cycles. Let be the set of cycles of length modulo , . If is even and at least 5, then . This result is implied by the result forbidding even cycles.
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Interval of even cycles. Let be the family of all graphs which contain consecutive even cycle lengths. Then . This result appears to be new.
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Disjoint cycles. If is the set of all disjoint unions of cycles (of possibly different lengths) then . This was shown by Li, Yu, and Zhang [40].
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Disjoint long cycles. Let be the set of all disjoint unions of cycles, each of length at least . If is even then and if is odd then . This result seems to be new.
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Disjoint equicardinal cycles. If is the family of all disjoint unions of two cycles of the same length, then for large enough. This result seems to be new.
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Minors. If is the family of all graphs which have an -minor and is -saturated, then .
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Topological subdivisions. If is the family of all topological subdivisions of and is -saturated, then .
We observe that there are fewer options for the assumed extremal graph in Theorem 1.5 than in Theorem 1.1. In the case that there is a simple counterexample that explains this: let be any graph such that for large enough, where . Then is also -free, and if is sufficiently close to 1 then (see e.g. [53]). Thus, one could only hope to extend Theorem 1.5 to this case if is restricted to a certain range. When is of the form , then the situation may be more subtle and we do not attempt to address every case.
2 Spectral extremal results
In this section we prove results concerning . In subsections 2.1, 2.2, 2.3, and 2.4 we prove Theorem 1.1; in subsection 2.5 we prove Proposition 1.2; and in subsection 2.6 we prove Proposition 1.4. Unless stated otherwise, all claims are asserted only for large enough.
2.1 Structure of edge extremal graphs
Proposition 2.1.
Under the assumptions of Theorem 1.1 (d) can be obtained from a maximal union of , of , or of by adding or deleting a bounded number of edges.
Proof.
Note that for some . Let be the smallest degree in the partite set of of size . Note that , because .
Consider the components of . We claim the number of components of order at least 4 is bounded; otherwise, the union of these components is a subgraph with and , thus contradicting the fact that for large enough. Moreover, the order of a component of is bounded; otherwise, by taking the largest component , we find a subgraph with and , again contradicting our bound on .
Now let . If then is bounded, and we are done.
Suppose . Then is the union of an unbounded number copies of , a bounded number of graphs of bounded order, and isolated vertices. Suppose for contradiction there are 2 isolated vertices in ; then adding an edge between them creates a copy of a graph from . Since there were already an unbounded number of disjoint edges in , one such edge is disjoint from , and the neighborhoods of its endpoints contain the neighborhoods of the endpoints of , so we can replace by to find which already existed in , a contradiction. Thus there is at most 1 isolated vertex. Hence, is obtained from by deleting and adding a bounded number of edges.
Suppose . Then is the union of an unbounded number of copies of , a bounded number of graphs of bounded order, and graphs of order less than 3. We will show that the components smaller than span at most 5 vertices; for otherwise, we can find either 3 components, a component and a component, or three components. In any case we can add and delete edges for a net increase in without creating any components on more than 3 vertices, and such that the copy of some which must have been created uses a vertex from a newly created component; but similarly to the previous case, we find another component (or two disjoint components if needed) which was not used in , hence there was some which already existed, a contradiction. This shows that is obtained from a maximal union of by deleting and adding a bounded number of edges. ∎
2.2 Common features of the spectral extremal graphs
The purpose of this subsection is to prove the following proposition.
Proposition 2.2.
Assume the setup of any of the cases (a)-(f) of Theorem 1.1. If then .
Let be the edge extremal graph; when we need to specify the number of vertices, we will write instead of . Set , and let be a Perron eigenvector of , scaled so that its greatest entry is . Let be a graph such that , and let , . Let be chosen such that . We choose positive constants to satisfy the following inequalities:
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(i)
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(ii)
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(iii)
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(iv)
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(v)
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(vi)
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(vii)
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(viii)
To see that such a choice exists, we choose first with the additional constraint that ; this allows that some will satisfy (vii). Then we choose and in that order. With , let , , , and . For , let , , .
The proof of Proposition 2.2 is technical; a high-level outline is as follows.
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1.
Show that and are not too large, i.e. there are not too many vertices with large eigenweight.
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2.
Show that is in fact bounded.
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3.
Relate the eigenweight of vertices to their degrees.
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4.
Show that eigenweights of vertices in are close to 1.
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5.
Show that .
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6.
Show that if then for all .
Lemma 2.3.
We have
Proof.
Since is -free we have
For the upper bound,
∎
Lemma 2.4.
We have
Proof.
For any we have . Hence
Solving for proves the first claim. A similar argument applies to . ∎
Lemma 2.5.
For any ,
Proof.
Let . We have
from the eigenvector equation, where in the first three terms in the right hand side we used the estimate . We estimate , , and as follows. First, induces a subgraph of order which does not contain any element of , so . Similarly we have . For , we use and so we have . Rearranging the inequality, we get
By inequality (i), taking large enough gives
∎
Lemma 2.6.
There is a constant such that .
Proof.
Lemma 2.7.
For any vertex , we have
Proof.
Let . We have
We apply and to get
So
where the last inequality holds by (ii). ∎
Lemma 2.8.
If and , then .
Proof.
Now we claim there are at least vertices in with at least neighbors in . For if not, then because and . Thus which is a contradiction for large enough. Thus, let be a set of vertices in each with at least neighbors in . Since there are only options for these neighbors, there is some set of vertices in with at least common neighbors in . Since is bounded, we have as , and so by adding the vertex we find that for arbitrarily large . However for large enough, which is a contradiction. ∎
Lemma 2.9.
For the vertex with , we have .
Proof.
For the lower bound, we use Lemma 2.7:
where the second inequality follows from and the last inequality follows from . For the upper bound, suppose for a contradiction that . Let . We claim there are at least vertices inside with at least neighbors in . If not then
because and . Since , we then have , contradicting the assumption. Hence there is a subset with at least vertices such that every vertex in has at least neighbors in . Since there are at most options for these neighbors, there exists some set of vertices in with at least common neighbors in . Since , we have as , so adding in the vertex means that for arbitrarily large , hence contains , which is a contradiction. ∎
Lemma 2.10.
For all , and .
Proof.
We first show . Assume for a contradiction there is some with . Then the eigenvector equation for gives
where in the first line, the term absorbs both the eigenweights of the vertices in (using inequality (iv)) and the weights from the edges in since . This implies
However, since we have and so , so This contradicts inequality (v). Now since , we have using inequality (vi). ∎
Lemma 2.11.
We have .
Proof.
If then the common neighborhood of vertices in would have at least vertices, so contains for arbitrarily large , a contradiction.
Since and every vertex in has degree at least , the common neighborhood of has at least vertices. Let be this common neighborhood and . Note that . The following lemma completes the proof of Proposition 2.2.
Lemma 2.12.
We have .
Proof.
Suppose otherwise. Note that
Hence, there exists some such that . Consider the graph obtained by deleting all edges between and , and adding any missing edges between and . The decrease in is at most , and the increase is at least , hence by inequality (viii).
Case 1: is finite. Since , for some , and must use the vertex . Since , there is some , so by replacing with we find some which is isomorphic to , a contradiction.
Case 2: is infinite. Let , and note that is -free. Furthermore, any vertex in has neighbors only in , , and . Then similarly to the argument above we find such that . Delete all edges between and and add all edges between and to obtain , and note that again increases, so that . Set , and continue in this way until we obtain . Since the resulting graph satisfies , is not -free. We now consider whether we are in case (a), (b), or (c) in the statement of Theorem 1.1.
Subcase (a). Since and is not -free, must have an edge either in or ; but since , this implies that is not -free. Since no edges in were modified to get from to , this implies is not -free, a contradiction.
Subcase (b). Note that . Thus we can delete all edges in and add the same number of edges in to obtain a subgraph of (which is therefore -free). However, it is easy to see that this operation further increases so that the spectral radius of the resulting graph exceeds , which is a contradiction.
Subcase (c). Noting , the same argument, where we now delete all but one edge in , gives the required contradiction.
∎
We observe that our arguments for the case where is infinite apply when or , but not when where . This is because, after deleting the edges in and adding the same number of edges in , there is more than one possible graph spanned by the remaining edges in , hence we do not necessarily end up with a subgraph of .
2.3 Eigenweight estimates
We now know that there is a set of vertices which are adjacent to every vertex in . Any other vertex may have at most neighbors in , otherwise contains a and is not -free. In this subsection we give more refined estimates on the eigenvector entries.
Lemma 2.13.
For we have .
Proof.
Let . Then we have
∎
Lemma 2.14.
For we have
Proof.
Lemma 2.15.
For , we have
Proof.
First we find a lower bound on eigenweights for vertices in . Note that
Thus, for any we have
Hence, for we have
∎
2.4 Proof of Theorem 1.1
Note that Proposition 2.2 already proves Theorem 1.1 (a). Thus, let be the spectral extremal graph for any remaining case (b)-(f). For notational convenience, let and in case (b), and let and in case (c). This way, we can write in all cases. Note that, since we now know that , we have .
Lemma 2.16.
The set induces a clique.
Proof.
Suppose not. We transform into by deleting all edges in and then adding all edges in and in . Note , since and . At least one added edge was in and thus increased by at least . Thus the net change in is at least
which is a contradiction. ∎
Lemma 2.16 now gives that all vertices in are dominating and hence all have eigenvector entry equal to . This means that the error term in Lemma 2.15 can be removed, and
(1) |
Armed with this we may now prove the theorem.
Proof Theorem 1.1 (e), (f).
We first only assume only (e). We already know that for some . Now, we can delete all edges in and add the edges in to transform into . The change in is at least
The last quantity above cannot be positive, and so , which proves the first claim. We already know that is bounded (by ).
Now assume (f). We first improve bounds on for . Note that all but a bounded number of have . By the above, , so the number of vertices in with degree less than is . Call a vertex bad if or and for some , and good otherwise. Since is bounded, the number of bad vertices in is . Now for any good vertex ,
On the other hand,
Combining the two estimates one obtains that . Now we delete all edges in and add all edges in . Note that at most edges of are incident to a bad vertex. It follows that for some , there is a set of edges of and a set of edges of which contain all edges of or , respectively, incident to a bad vertex. Then the change in is at least
If then the quantity above is positive, a contradiction. Hence , which implies that the number of bad vertices is in fact . Therefore we can take and repeat the previous argument to show that when we transform to the change in is at least
which implies ; hence . ∎
Proof of Theorem 1.1 (b), (c), (d).
From Proposition 2.1, we have for some . The first case is , in other words and consequently . If , then delete all edges in and add all edges in to make the graph isomorphic to . Let be the number of edges deleted and added, respectively, which satisfy . Then the change in is at least
which is a contradiction. Actually, this argument proves the following fact: whenever can be obtained from by deleting a bounded number of edges and adding more edges than were deleted, we have .
The second case is . We first note that since is -saturated, only a bounded number of vertices have , by the same argument as Proposition 2.1. On the other hand, must be unbounded, or the same argument as in the case would show . Therefore, the argument in Proposition 2.1 shows that has at most one isolated vertex. Thus is obtained from a maximal union of by deleting and adding a bounded number of edges. Since the same is true of , we can delete and add a bounded number of edges to transform into a graph isomorphic to . By the fact mentioned above, this implies that .
The final case is similar. We find that is the union of copies of and smaller graphs, plus a bounded number of graphs of bounded order. The number of copies of must be unbounded; otherwise, we have , and we may substitute in the argument above, and find
which gives a contradiction. The argument of Proposition 2.1 then shows that is obtained by deleting and adding a bounded number of edges to a maximal union of . By the fact mentioned above, this implies that . ∎
Note that the conclusions stated in (b) and (c) follow because in these cases contains a single graph up to isomorphism.
2.5 A counterexample
Proof of Proposition 1.2.
Let consist of the all the following graphs:
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1.
;
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2.
, for all connected graphs on 5 vertices;
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3.
, for all connected graphs on 5 vertices;
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4.
, for all connected graphs on 9 vertices;
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5.
, for all connected graphs on 8 vertices except for ;
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6.
, for all connected graphs on 5 vertices;
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7.
for .
We have chosen a very large family , which makes the extremal problem for easy. We suspect that a similar counterexample could be obtained with an even smaller family .
Lemma 2.17.
If is large enough, then we have that .
Proof.
One can check that is -free. Now let be the extremal graph, so that
By forbidding (1), we may choose vertices such that any other vertex has at most neighbors in . Consider the components of ; these are either graphs on 3 or 4 vertices containing a or , respectively (and by (7) there are at most 2 of each type), or connected graph of order at least (and by (6) there are at most 3 of these), or trees on at most vertices. We claim that the order of any graphs of the second type is at most . Let be such a component with ; let denote . Then for any , since , and consequently we can find vertices such that for , . This implies that , , induce 5 disjoint connected graphs on at least 5 vertices, which contradicts (6). Putting this all together, we find a partition where is a union of trees of order at most 4, , and . Hence, since , we have
So , , and . Note that and are contained in disjoint copies of so by (1), every other vertex of has at most 3 neighbors outside . Now we have
which implies we can find 2 disjoint edges in . Hence and are contained in disjoint copies of . Thus by (5) and (7), all components of , except possibly one (which by (4) can be of order at most ), are trees of order at most 4. Such a graph cannot have more edges than . If , then , where is a connected graph on 8 vertices (using (4)). By (5), we have ; but then by (3), . It follows that , hence . ∎
As in the proof above, let . Let . One can check that is also -free. We now show that . Note that and have equitable partitions with quotient matrices
The characteristic polynomials are
By the Weyl inequalities, and . Thus is negative on and positive on , and is negative on and positive on . So, to show it suffices to find some such that . For a constant , we compute
as . Choosing , we find that while . ∎
2.6 Forbidden trees
Proof of Proposition 1.4.
We will assume that all labelled trees have vertex set and let denote a uniformly random labelled tree on . For in , let be the event that , has a neighbor different from which is adjacent precisely to and 2 leaves, and has a neighbor different from which is adjacent precisely to and 2 leaves; let be the indicator function of . Observe that if occurs then is of the form described in the application ‘Almost all trees’ of Theorem 1.1, for some . Therefore, defining , it suffices to show that . Our argument is a variation on [20] in which it was shown that almost all labelled trees have a vertex with two leaves.
For (not necessarily distinct), we define to be the number of labelled trees on which contain the edge , and we define to be the number of labelled trees on which contain both edges and . From Lemma 6 of [45], we have the following formulas.
Lemma 2.18.
For any distinct we have:
-
(a)
-
(b)
-
(c)
.
Next we estimate and . To specify a tree such that occurs, we choose the neighbor of and its pair of leaves, then we choose the neighbor of and its pair of leaves, and then attach a tree containing the edge and the unused vertices in . For a constant we have that . This gives:
Next we consider . There are 2 types of trees which realize this event: (i) those in which the special neighbor of in is the same as the special neighbor of in (the special neighbor of and must be distinct in a tree), and (ii) those in which they are different. So we have
Finally, if are distinct, then we have
Therefore, we have
Therefore , and Chebyshev’s inequality gives
∎
3 Alpha spectral extremal results
Let be the family of graphs in Theorem 1.5. We first consider the case where contains some bipartite graph with a vertex such that is a forest.
Lemma 3.1.
There exists such that, for any graph with and
there exists a copy of in such that embeds in .
Proof.
Let be the vertex such that is a forest, and let . Let be a proper coloring with . Then has a proper coloring , and contains all the neighbors of in . Set and .
Let be a forest obtained from 2 copies of by selecting a vertex from from each component (observe that every component of must contain a vertex in ) and making it adjacent to the corresponding vertex in the other copy of . Now if then it is known that .
Now consider the graph with , appearing in the statement of this lemma. If then and we are done. If then , and by the design of this means there is a copy of in in which embeds in . Hence, to guarantee the conclusion of the lemma, it suffices that or , and we may take e.g. . ∎
If is any -free graph, then for any , there cannot be a copy of in such that all the neighbors of embed in . Applying Lemma 3.1 gives
(2) |
If does not contain a graph so that is a forest, then we assume that . By choosing large enough in Equation 2, we may assume that the equation holds in either case, for some , for any -free graph.
Lemma 3.2.
([53]) Let be a graph and , then
Lemma 3.3.
For any -free graph we have .
Proof.
We have , and by the Weyl inequalities we have
∎
Lemma 3.4.
Let be a connected graph and let be a Perron vector of . Then for all , we have
Now let be a graph in and let be its Perron vector, scaled so that its largest entry is . Let be a positive constant satisfying and . With , let and let . Also, write and . As in Section 2, all claims below are only asserted for large enough unless stated otherwise.
Lemma 3.5.
For sufficiently large, we have that
Proof.
Lemma 3.6.
For all , we have .
Proof.
Suppose to the contrary that there is some with . Then,
Lemma 3.7.
There is some such that . Consequently, for some fixed .
Proof.
If not, then is -free. Since , this contradicts the fact that . ∎
Lemma 3.8.
The size of is .
Proof.
First assume for a contradiction that . Then there is a set with . Therefore, every vertex has , and the common neighborhood of the vertices in has at least vertices. This implies that for large enough, which contradicts Lemma 3.7.
To show , assume to the contrary that . In cases (b) and (c), we have
Therefore,
But from Lemma 3.5 we have
using . Since , these two inequalities give a contradiction. ∎
It follows from Lemma 3.6 and Lemma 3.8 that and for all . Let denote the common neighborhood of all vertices in . Then . Let , so that . We will show that and so .
Lemma 3.9.
For any , we have .
Proof.
Assume to the contrary that there is some with . Then the second-degree eigenvector equation with respect to gives
On the other hand, from Lemma 3.5 we have which, since gives a contradiction. ∎
Note that since , for any we have .
Lemma 3.10.
For any we have .
Proof.
Let . Then we have
so
∎
Lemma 3.11.
We have .
Proof.
Delete all edges between and and add all missing edges between and , to obtain a graph . The deletions decrease by at most
while the additions increase by at least If then the net change is positive. Hence, for some . This implies that in case (a) and in case (b). Either way, it follows that , since is -free. Delete from all edges in and add an edge in , to obtain a subgraph of . The deletions decrease by at most
while the addition increases by at least , so the net change is again positive. Thus which is a contradiction. ∎
Lemma 3.12.
The set induces a clique.
Proof.
Suppose not. Then we transform into by deleting all edges in and adding at least one edge in . The deletions decrease by at most
while the additions increase by at least , which is a contradiction. ∎
4 Concluding remarks
Our aim in this paper was to study situations where or . In fact, we have given ‘recipes’ which allow one to determine these extremal graphs in more general situations. Many more applications of these results could be stated, and in our list of applications we have restricted ourselves to families for which the edge extremal graphs were studied in previous papers. There are also applications which follow easily from the methods of this paper but are not strictly consequences of our main theorems. We list some such cases below.
-
•
When one has a ‘nice characterization’ of the graphs such that is -free, stronger results can be proved. For example, suppose if -free if and only if ; then one can remove the assumption that is finite from Theorem 1.1 (c) and prove an analagous result for the alpha spectrum. This allows one to prove the following results.
-
–
This also follows from the spectral extremal result for [47].
-
–
[56].
-
–
has the largest (alpha) spectral radius without disjoint even cycles.
-
–
has the largest (alpha) spectral radius without 2 disjoint theta graphs; see [29] for the definition and required extremal result.
Another such ‘nice characterization’ occurs in the spectral result for star forests; here is -free if and only if . Thus we can obtain the corresponding alpha spectral result from [10].
-
–
-
•
In some cases our methods work for extremal graphs of the form , where is a fixed graph which is neither empty nor complete. For example, if is finite and every graph in contains edges in and no edges in , then under the other assumptions of Theorem 1.1, we have that any graphs in are where . As consequence, we obtain the spectral analogues of Theorems 1.6 and 1.7 of [44].
-
•
As mentioned in the introduction, when then under the assumptions of Theorem 1.5 we can show that for a certain range of . However, additional arguments would be needed to characterize for every .
Additionally, when our methods do not determine the extremal graphs exactly, one can sometimes still obtain general structural results. For example, let be any finite family of graphs such that . Let Then the proof of Proposition 2.2 gives that any has . Moreover, any vertex in the partite set of of size has degree at most , where is the smallest minimum degree of a vertex in the partite set of size of any satisfying .
We end by listing some open questions.
-
•
To prove Theorem 1.1 in its generality we require that . However, many of the techniques in the proof were originally discovered in the proof of the spectral even-cycle theorem [13] where the Turán number is much larger. When considering a specific forbidden family, the structure of the forbidden graph(s) can be used and in some cases the condition on the Turán number can be relaxed. When , perhaps the assumption that is a forest for some bipartite could be useful. For example, it would be interesting to try to prove a spectral version of the general result of Faudree and Simonovits [26]. In any case, it seems possible that our assumption could be weakened or modified, and one could obtain a general result which implies, e.g., the spectral even cycle theorem.
-
•
For the case , we do not know whether the assumption that is a forest could be weakened. For example, if one may assume only that is a forest then perhaps one could determine the alpha spectral extremal graphs for .
-
•
We would like to obtain a counterexample similar to Proposition 1.2 using a smaller family or ideally a single graph . Alternatively, perhaps Theorem 1.3 be strengthened when consists of a single forest . It seems reasonable to guess that, for , we have while for any this is not necessarily the case. The reason is that, when we can use the fact that is a union of bounded trees or of cycles; while for certain , certain path-star forests [25] provide counterexamples.
-
•
The only step in the proof of Theorem 1.1 which prevents us from allowing to be infinite in all cases is Lemma 2.12. We were unable to modify our arguments to work for all infinite graph families or to find a counterexample showing this cannot be done. In some cases, the nature of the graph family allows one to prove Lemma 2.12 without resorting to the argument we use for cases (a)-(c). For example, if , then the ‘nice characterization’ argument alluded to above achieves this, but alternatively one can argue instead of Lemma 2.12 that the existence of a long cycle in the modified graph implies the existence of a different long cycle in the original graph . Ad-hoc arguments of this kind may work for many other natural infinite families.
-
•
In cases (d) and (e) of Theorem 1.1, it is not too difficult to show that if , then there is some such that . Can this be shown for ?
-
•
As mentioned in the introduction, the extremal graphs covered by Theorem 1.5 are more restricted than those covered by Theorem 1.1. Our methods should give some information about when is as in cases (a), (d), (e), or (f) of Theorem 1.1, but we have not attempted to determine the strongest possible statement one can prove using our methods.
-
•
When , we have seen that the extremal function is relevant to determining the spectral extrema for many families of forbidden graphs. Perhaps this motivates further study of this or other ‘restricted extremal problems’; in particular, it would be interesting to see if there are cases in which determination of is nontrivial while also providing an application of Theorem 1.1.
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