Pairs of disjoint matchings and related classes of graphs
Abstract.
For a finite graph , we study the maximum -edge colorable subgraph problem and a related ratio , where is the matching number of , and is the size of the largest matching in any pair of disjoint matchings maximizing (equivalently, forming a maximum -edge colorable subgraph). Previously, it was shown that , and the class of graphs achieving was completely characterized. We show here that any rational number between and can be achieved by a connected graph. Furthermore, we prove that every graph with ratio less than must admit special subgraphs.
1. Introduction
We investigate the ratio of two parameters of a finite graph , where is the size of a maximum matching in , and is the size of the largest matching in a pair of disjoint matchings whose union is as large as possible. More formally,
One motivation for studying the ratio is the problem of covering as many edges of as possible by matchings, which is known as the Maximum -Edge-Colorable Subgraph problem. Let denote the maximum number of edges of that can be covered by matchings. When , it is clear that one just takes a maximum matching, so . We consider the problem with , as .
1.1. Computational Considerations
Recall that a proper edge coloring of a graph is an assignment of a color to each edge of such that no two adjacent edges have the same color. In a proper edge coloring, the set of edges with a given color is by definition a matching, so a proper edge coloring with colors corresponds exactly to covering with matchings. We can therefore reframe to be the maximum size in edges of a subgraph of that is -edge-colorable.
Edge coloring is a computationally complex problem; in [Holyer], I. Holyer showed that the problem of determining whether a graph admits a -edge coloring is -complete even in the case of cubic graphs. Note that a cubic graph is -edge colorable if and only if is equal to the number of vertices, and so Holyer’s result is equivalent to the -completeness of the problem of determining whether is equal to the number of vertices.
Furthermore, U. Feige, E. Ofek, and U. Wieder showed in [F-O-W:02] that for all , the -edge-colorable subgraph problem (computing ) is -hard (note that there are polynomial time algorithms computing , the first being due to J. Edmonds in [Edmonds:1965]). Therefore, unless , we cannot compute in polynomial time. In [A-K-S-S-T:2020], however, A. Agrawal et. al show that computing is fixed-parameter tractable.
A greedy algorithm to compute matchings realizing could first take a maximum matching of the whole graph, then recursively take a maximum matching of the remaining edges until matchings have been computed. However, this may not yield a cover with maximum number of edges ; see Fig. 1 for a minimal example. The parameter measures the failure of the optimality of this greedy algorithm for .

1.2. Numerical Bounds
In [Mkrtchyan:2008qr], V. Mkrtchyan, V. Musoyan, and A. Tserunyan proved that
for any graph , and A. Tserunyan, in [Tserunyan:2009qr], characterized all graphs that achieve the ratio —the characterization is somewhat involved, see Appendix A for a brief exposition. Figure 1 shows a picture of the spanner, the unique minimal graph that achieves the ratio .
In [A-M-P-V:2014] D. Aslanyan et. al. show that in the special case of cubic graphs,
Furthermore, in [M-P-V:10], it is shown that in cubic graphs, the following inequalities hold:
In this vein, L. Karapetyan and V. Mkrtchyan prove in [K-M:19] the following inequality: for a bipartite graph , for all ,
1.3. Our Results
The present paper deals with graphs achieving . In Section 3, we prove that for a connected graph , the ratio achieves any rational number within our bounds. In fact:
Theorem 1.1.
For any positive integers such that , there is a connected graph with and .


In Section 4, we prove the following necessary structural condition for graphs with .
Theorem 1.2.
If a finite connected graph has , then it contains a diamond spanner as a subgraph see Fig. 3, Definition 4.10.

Unlike the lower bound , we still do not know exactly for which graphs the ratio achieves the upper bound . More precisely, the following is still open:
Problem 1.3.
Give a structural characterization of the class of all finite connected graphs with .
2. Definitions and notation
Here, we define the main notions we use, referring to [West:graph_theory] for basic graph-theoretic terminology.
By a graph, we mean a pair , where is a set of vertices, and a set of edges, i.e. . We will only be considering finite, simple, undirected graphs with no loops, i.e., and for all . We identify the corresponding undirected edge by . A matching in is a set of edges such that no two are adjacent. A perfect matching is a matching that covers every vertex, and a near perfect matching is a matching such that for every vertex in except for one, there exists an such that is incident to .
Below we define the parameters that we will investigate throughout the rest of the paper, as well as some additional definitions:
.
is the set of pairs of disjoint
matchings satisfying .
.
is the subset of of pairs with .
.
If , then an alternating path is a path such that alternating edges are in and the others in . We will frequently refer to alternating paths for the and described above.
A path/cycle is even (odd) if it has even (odd) number of edges.
A central vertex of a tree is a vertex with degree larger than 2.
A leg is a copy of (the path graph of length , i.e. with two edges). We say is obtained from by adjoining a leg to a vertex of if is obtained by taking the union of and and identifying one end vertex of with the vertex .
Recall that spanner is the tree depicted in Fig. 1. A -spanner is a tree obtained from the spanner with additional legs adjoined to either of the central vertices, in any combination. Note that the spanner is a 0-spanner. Fig. 4 depicts a -spanner.

An inner edge (resp. outer edge) is an edge in a leg of a
-spanner adjacent to a central vertex (resp. vertex of degree 1).
For a graph and a matching , we say that
a vertex is saturated in if an edge in is
incident to .
3. Achieving every ratio
In this section, we prove by construction that every rational ratio between and is achieved by a connected graph (Theorem 1.1).
3.1. Achieving any allowable ratio
Lemma 3.1.
Let be a graph with nonadjacent vertices and . Let , and . Then if and only if there is some such that are both unsaturated in or are both unsaturated in .
Proof.
Clearly, if and only if for any . The restriction of to gives a pair in with unsaturated in or . Conversely, if there is such that, say, doesn’t saturate and , then . ∎
Notation.
For a -spanner , , and a leg in , we write to denote with the two vertices incident to the outer edge of removed. Notice then that is a ()-spanner.
Lemma 3.2.
If is a -spanner, then for any , the inner edges of all but two of the legs adjoined to each central vertex do not belong to and the outer edges of those legs are in . Furthermore, is unique, up to an automorphism of .
Proof.
At most two of the edges incident to a central vertex can be in . Thus, must leave out the inner edge of all except perhaps two legs adjoined to each central vertex. The maximality of requires that we include exactly two edges incident to each central vertex in . The outer edges of the legs whose inner edges were left out must be in because otherwise, adding each such an edge to and removing it from if it was in results either in an increase of while preserving or in an increase of . ∎
The proof of Lemma 3.2 also establishes the following corollary.
Corollary 3.3.
In any -spanner and for any , we have that both of the central vertices are saturated in both and .

Lemma 3.4.
Let be a -spanner. Then admits a unique perfect matching and , , and .
Proof.
We take all the edges adjacent to the leaves and the unique edge between the central vertices. This is clearly a perfect matching and it contains one edge per leg, as well as another edge connecting the central vertices, so a total of edges. Fig. 2(a) illustrates this perfect matching in a -spanner.
To verify the uniqueness of this perfect matching, note that the edges incident to the leaves have to be in any perfect matching, therefore the edges adjacent to them cannot be. This leaves only the edge between the two central vertices, so it has to belong to every perfect matching in order to saturate the central vertices.
Fix . By Lemma 3.2, the inner edges of all but two legs incident to each central vertex do not belong to and the outer edges of those legs are in . Removing these legs from the graph results in a -spanner, for which it’s easy to see that the maximum number of edges from is , where has edges, and the only possibility is to leave the edge between the central vertices out. Each additional leg adds one edge to and none to , so the formulas follow. For example, Fig. 5 illustrates a pair in a -spanner. ∎
Lemma 3.5.
Let , , be distinct graphs, and in each graph, suppose there is a vertex that is saturated with both and for any . Let . Then for every , . In particular, for . The same statement holds with every occurrence of replaced with .
Proof.
Fix and note that it is enough to show that . Assume towards a contradiction that . Then for each because is unsaturated with either or . Thus, . But this contradicts the fact that for any , is a pair of disjoint matchings in with total number of edges equal . ∎
Lemma 3.6.
Let be a -spanner graph, and for any , let be a graph formed by connecting one of the central vertices in a spanner in to one of the central vertices of a new -spanner . Then , we have that if , then for each .
Proof.
By Corollary 3.3, the central vertices of every are saturated with both and for any . The statement, therefore, follows from Lemma 3.5. ∎
We are now ready to prove Theorem 1.1, which we restate here for the reader’s convenience.
Theorem 1.1. For any such that , there is a connected graph with and .
Proof.
All of the graphs with ratio less than 1 that have been constructed so far contain a perfect matching by design. However, this is not a necessary condition for a graph to have ratio less than 1: the graph in Fig. 6 is a counterexample. It has ratio , but it does not admit a perfect matching.

Furthermore, by adding more vertices around the new 3-vertex, arbitrarily
many vertices can be missed from the maximum matching. This graph also
demonstrates that ratio less than 1 can be achieved by a graph with an
odd number of vertices.
4. Ratio 1
In this section, we provide several sufficient conditions for a graph to have ratio , most notable of which is Theorem 1.2. The latter involves diamond spanners, which, by definition, are spanners with any number (possibly zero) of central diamonds as in Fig. 3. We will prove Theorem 1.2 after some observations and lemmas.
Throughout, we let be a finite connected graph and .
4.1. Observations and examples for ratio 1
Observation 4.1.
.
Lemma 4.2.
If admits two disjoint matchings whose union contains at least edges, then .
Proof.
The hypothesis implies that , i.e., is or . Either way, , so by Observation 4.1. ∎
Definition 4.3.
A path/cycle in is called Hamiltonian if each vertex of appears in it exactly once.
Corollary 4.4.
If admits a Hamiltonian path, then .
Proof.
A Hamiltonian path has edges, which lie in a pair of disjoint matchings, so Lemma 4.2 applies. ∎
There are also plenty of graphs with ratio 1 and no Hamiltonian path.
Example 4.5.
In Fig. 7, we exhibit an augmented spanner with no Hamiltonian path and having ratio 1.

Indeed, the graph in Fig. 7 has , and this can be achieved with and , as in the figure. is also a perfect matching, so .
Example 4.6.
Here is another example with ratio 1 and no Hamiltonian path. Let be the propeller graph with blades of length , namely, the graph obtained by joining paths of length two to a shared central vertex. Figure 8 depicts .

Proposition 4.7.
, , and hence . In particular, the difference between the parameters and can be arbitrarily large.
Proof.
For any pair of disjoint matchings, each leaf can be incident to at most one edge in and the central vertex can be incident to at most two edges in , so . We show that this is, in fact, an equality. Letting denote the central vertex, be a leaf, and be the vertex adjacent to both and , we let contain and all edges incident to all leaves except for . We then let contain and an edge incident to distinct from . Thus and , so achieves . By Observation 5.2, is a maximum matching, so . ∎
4.2. Alternating paths
We present some lemmas about alternating paths before we prove Theorem 1.2.
Definition 4.8.
Choose matchings such that , , is disjoint from , , is maximized, and among these, such that is maximized. Call the triple a maximum intersection triple.
Lemma 4.9.
Let be a finite graph with . Let be a maximum intersection triple of . Let be a maximal alternating chain, and it follows from maximality of that is length at least two. Then
-
(i)
is not a cycle.
-
(ii)
The length of is odd and its end edges are in .
-
(iii)
The end edges of are in .
-
(iv)
All interior vertices of are incident to .
-
(v)
contains at least one edge.
-
(vi)
There does not exist an even cycle in such that half of ’s edges are in , the remaining edges in , and .
Proof.
(i): Suppose is a cycle. If is an odd cycle then note that two adjacent edges will be in the same matching, contradicting matching definition. Suppose then that is an even cycle. Consider , and note that this is a matching since is an even cycle and maximum since is. Then and , a contradiction.
(ii): By (i), is not a cycle, so is a path. Suppose that some end edge of , is in . can be incident to on only one side, as is a maximal alternating path. Call this edge . Since is incident to on only one side, we may define . is a maximal matching, but , contradicting that () was a maximal intersection triple. thus has no end edges in . This implies that also has odd length.
(iii): Consider an end edge in . Again note that can be incident to on only one side. If is not in , then we can remove , the preceding edge, from , add to , and again increase .
(iv): Suppose instead some interior vertex is not incident to , and note that this vertex is incident to no end edges. This vertex is incident to exactly one edge in , which we call . is incident to at most once. Via a similar argument to above, if we take to be in instead of this adjacent edge, we increase .
(v): Suppose towards a contradiction that all edges in are also in . Swapping and on the path will increase and keep the same, a contradiction. We are allowed to do this because the two end edges of are not connected to .
(vi): Suppose there exists such a . Observe that must contain some edge. To see this, note that because is acyclic, some edge, say , is incident to fewer than two edges. Then must be adjacent to a edge, or else is not maximal. Then , and since . Now, define . is a matching since no vertex of is adjacent to an edge not already in . is maximal since is. Because contained some edge, immediately .
∎
4.3. Sufficient condition for ratio 1: forbidden subgraphs
Let the diamond graph be the graph with four vertices depicted
in Fig. 9(a).
Let a diamond chain be a graph resulting from taking some
natural number copies of the diamond graph, indexing them .
Arbitrarily
distinguishing between the two vertices of degree two in each diamond
as the “left” and “right” such vertices, add an edge between
the right degree two vertex of diamond and the left degree two
vertex of for . A diamond chain is depicted in Fig. 9(b)


Definition 4.10.
A diamond spanner is a graph obtained from the spanner via removing the edge between the central vertices and taking disjoint union with a diamond chain. The central vertices of the spanner are then connected to the degree two end vertices of the diamond chain. We also consider the spanner to be a diamond spanner. See Fig. 3.
We prove one more lemma about - alternating paths before proving Theorem 1.2.
Lemma 4.11.
Assume the same conditions as in Lemma 4.9, and let be a maximal alternating path. If contains an edge of such that has no edge or alternating path connecting the two components of , then is an edge of a diamond spanner of .

Proof.
The setup is depicted in Fig. 10. We will show that each piece of must witness a chain of diamonds that terminates in a spanner-end. Observe first that is not an end edge of by (iii) of Lemma 4.9. Consider the right vertex of . By (iv) of Lemma 4.9, it must be adjacent to an edge. By assumption, this edge does not cross over to the left side of . Either this edge connects to some vertex not in or to another vertex to the right of . In the first case, note that this edge must be connected to an edge, or else is not maximal. This edge must also be off of since all edges are saturated with . We now have a path of length at least 2 extending off of , and we see that the right side of is now a “spanner-end”, as in Fig. 11.

If instead our edge connects back to the right of on , then if it connects to a vertex of distance more than 2 away then we again have a spanner end, as shown in Fig. 12.

If instead it connects to the vertex 2 to the right of , then if follows from (iv) of Lemma 4.9 that the vertex directly to the right of must also be connected to an edge. Again, if this edge connects more than distance 2 to the right, or goes off the path, we have a spanner-end. If instead this second edge connects distance 2 away, observe that we now have a diamond configuration on the right hand side of . This is illustrated in Fig. 13.

Notice that the edge to the right of this diamond cannot be in , and that any or -- path crossing it would have to cross as well. Thus, we may repeat our argument for this new edge. Since is finite, we must eventually choose a spanner end on the right side. We extend this argument to the left side of by noting that any edge going off of on the left cannot be incident to any - path off of on the right of by assumption. ∎
We may now prove Theorem 1.2, which we restate here for the reader’s convenience.
Theorem 1.2. If a finite connected graph has , then it contains a diamond spanner as a subgraph.
Proof.
Assume the same conditions and fix as in Lemma 4.11. Note that such an alternating chain must exist, or else . Then contains some edge by (v) of Lemma 4.9. Consider the leftmost of these edges . The left vertex of must be incident to some edge. If this edge does not connect to some vertex on the right of and is not part of an -- path connecting to the right of , then Lemma 4.11 implies the existence of a spanner or diamond spanner. Otherwise, we may assume it is an edge connecting back to , since we will derive contradictions by the illegal even cycles described in (vi) of Lemma 4.9. This edge connects to some vertex to the right of , observe that if this connects directly to the left of some edge that we have created an even cycle forbidden by Lemma 4.9. This cycle is pictured in Fig. 14.

This edge must then connect to the left of some edge by a vertex . Note cannot be in . If none of the vertices between and are linked by an or -- path to some vertex on the right of , then Lemma 4.11 again gives us a spanner or diamond spanner. The barrier is drawn in Fig. 15.

Suppose instead that one of these vertices is linked to the right of . Choose the vertex between and that is connected by such a path that travels the furthest to the right. Call this vertex and the vertex it is linked to . If is on the left of an edge and on the right of an edge, then the two paths between and form another prohibited even cycle. If is on the right of an edge and on the right of an edge, then the cycle connecting to to to is also prohibited. This forbidden cycle is shown in Fig. 16.

Thus, must also be on the left of some edge . By a similar argument to the case for , if no vertex between and is linked to a vertex of on the right of by an or -- path, then Lemma 4.11 applies. Thus, some vertex between and must be linked to the right of . In fact, by choice of being furthest away of all linked vertices from those between and , we may restrict out attention to the vertices between and . Among these, again choose the vertex that is linked the furthest to the right to some vertex , as shown in Fig. 17.

Again, if is to the left of an edge and to the right, then these two paths between these two vertices form a forbidden even cycle. If instead is on the right of an edge and on the right, then these two vertices are part of another forbidden even cycle, regardless of whether is on the left or right of an edge. Thus, is on the left of an edge . We may continue arguing in this manner, but observe that there are only finitely many edges in , so eventually, we will not be able to cross some edge without creating a prohibited cycle. No vertex to the right of can be linked to a vertex to the left since our and -- paths were chosen to reach the furthest. Then witnesses a spanner or diamond spanner by Lemma 4.11. ∎
Appendix A Characterization of Graphs Achieving Ratio
For the reader’s convenience, here we provide a short exposition of Tserunyan’s characterization [Tserunyan:2009qr] of exactly when the lower bound is achieved by a connected graph.
Let denote the spanner as a concrete graph, and note that is a tree. Call a vertex of the spanner a -vertex if it has degree . For a -vertex or -vertex , call the nearest -vertex the base of . Call an edge between an -vertex and a -vertex an edge. Define two sets associated to the spanner :
For an arbitrary graph , call a spanning subgraph where every connected component is isomorphic to an -forest. Let admit an -forest . Denote the connected components , and define
Note that are subsets of whereas are subsets of .
Call a non-repeating sequence of edges such that is adjacent to for all a trail. If are the vertices incident to , call a trail closed if . For sets , say a trail is -alternating if the edges of even index belong to and those of odd index belong to or vice-versa.
Theorem A.1.
A connected graph has ratio if and only if admits a spanning -forest such that
-
(a)
-vertices of are not incident to any edge from
-
(b)
if is a -vertex and is incident to an edge of , then the -vertex adjacent to is not incident to any edges of
-
(c)
for any -alternating closed trail containing a edge, we have is not bipartite.
Acknowledgements
We thank Vahan Mkrtchyan for his invaluable insight into this direction of research and for pointing out the relevant literature and context. We also thank Alexandr Kostochka for helpful suggestions and advice.