Abstract
A graph G is a fractional -critical graph if removing any n vertices from G, the resulting subgraph still admits a fractional -factor. In this paper, we determine the exact tight isolated toughness bound for fractional -critical graphs. To be specific, a graph G is fractional -critical if and , where is an integer satisfies . Furthermore, the sharpness of bounds is showcased by counterexamples. Our contribution improves a result from [W. Gao, W. Wang, and Y. Chen, Tight isolated toughness bound for fractional -critical graphs, Discrete Appl. Math. 322 (2022), 194–202] which established the tight isolated toughness bound for fractional -critical graphs.
AMS:
1. Introduction
The graphs we discuss in this paper are simple and finite. Let G be a graph with vertex set and edge set . We denote and (simply by and ) as the degree and the neighbourhood of vertex v in G respectively, and is the minimum degree of G which took the smallest value of among all vertices. Let be the subgraph of G induced by . Denote as the number of isolated vertices in G. The operator in means adding edges for all pairs of vertices between and . The notations and terminologies used but undefined in this paper can be referred to Bondy and Murty (Citation2008).
Let a, b, k be positive integers with , and be an indicator function defined on the edge set. A fractional -factor is a spanning subgraph consisting of edge set such that (1) (1) for any . A graph G admits a fractional -factor means there is an indictor function h meeting (Equation1(1) (1) ). For , G is a fractional -critical graph if removing any n vertices from G, the resulting subgraph still admits a fractional -factor. In particular, if a = b = k, then fractional -factor and fractional -critical graph are degenerated to fractional k-factor and fractional -critical graph, respectively, which are the original versions of fractional factor and fractional critical graph.
As a salient graph parameter, isolated toughness is introduced by Yang et al. (Citation2001) which is stated as if G is not a complete graph, and if G is a complete graph.
In recent two decades, with the advancement of graph theory technology and spread networks applicability, fractional factor has developed into a prominent research field in both graph theory and computer networks, and has achieved crucial theoretical results. Ma and Liu (Citation2006) contended that a graph G admits a fractional k-factor if and . Gao and Wang (Citation2017) determined that G is a fractional -critical graph if , where and . Gao et al. (Citation2022) proved the tight isolated toughness bound for a graph G to be fractional -critical, i.e. G is a fractional -critical graph if and , where . Zhou (Citation2021) and Zhou, Liu, Xu (Citation2022) studied the graph parameter conditions of fractional critical covered graph which inquires fractional factors with given edges after removing fixed number of vertices. More results on this topic and other extensions can be referred to Chang et al. (Citation2022), Chen et al. (Citation2022), Zhou, Wu, Bian (Citation2022), Zhou, Wu, Liu (Citation2022) and Zhou, Wu, Xu (Citation2022).
Although there are fruitful advances in the correlation of isolated toughness and the existence of fractional factor, the study of generalisation properties of fractional factors has been largely limited to the special setting, especially the tight bounds are open problems in most fractional critical graph settings. Motivated by the aforementioned facts, in this paper, we determine the sharp isolated toughness bound for a graph to be fractional -critical, and our main conclusion is stated as follows which extends the previous result in Gao et al. (Citation2022).
Theorem 1.1
Let G be a graph, and a, b, n be positive integers with and , where is an integer. If and , then G is a fractional -critical graph.
To be obvious, is tight for a graph G to be fractional -critical in terms of the definition of fractional -factor. The sharpness of in Theorem 1.1 is showcased in the following instance.
Consider where a, b, n are positive integers with , and is an integer which is determined by the correlation with . We directly get On the other hand, set and , we yield Thus, G is not a fractional -critical graph by means of Lemma 2.2.
By setting a = b = k in Theorem 1.1, and thus the following corollary is derived for fractional -critical graphs.
Corollary 1.1
Gao et al., Citation2022
Let G be a graph, and be integers. If and , then G is a fractional -critical graph.
The remainder of the paper is arranged as follows. Several useful lemmas and remarks are presented in the next section. Then, the detailed proof of Theorem 1.1 is presented. Finally, we discuss some interesting topics for future studies.
2. Preliminary
The necessary and sufficient condition of fractional -critical graph is imperative to prove our main theorem which is determined by Liu (Citation2010).
Lemma 2.1
Liu, Citation2010
Let a, b and n be positive integers such that . Then a graph G is fractional -critical if and only if holds for any with , where .
It is noteworthy that for a given subset S of , T is determined by S which can be rewritten by . We emphasise that Lemma 2.1 has its equal expression which is manifested below.
Lemma 2.2
Liu, Citation2010
Let a, b and n be positive integers such that . Then a graph G is fractional -critical if and only if holds for any disjoint subsets with .
The following lemma is obtained by slightly revising the Lemma 2.2 in Liu and Zhang (Citation2008) in view of its proving process which presents the characteristic of independent sets and covering sets in specific settings.
Lemma 2.3
Liu & Zhang, Citation2008
Let G be a graph and let such that for every and no component of H is isomorphic to where and is an integer. Then there exists an independent set I and the covering set of H satisfying and where for and .
The crux of our proofing strategy is to get the integer upper bound of (or instead), with the aim to eliminate the decimal part of and obtain the desired conclusion. Another crucial trick in the proof process is to get the lower bound of the denominator of isolated toughness (, some terms may become zero in special cases). It is observed from the derivation in the next section that the lower bound of depends on , i.e. the correlation between a and b determines lower bound of denominator to maximise the , and then we infer the contradiction.
3. Proof of theorem thm1.1
If G is complete, the result is directly yielded by means of . In what follows, we always assume that G is not complete. Suppose that G satisfies the conditions of Theorem 1.1, but is not a fractional -critical graph. By Lemma 2.2, there exist disjoint subsets S and T of with satisfying (2) (2) We choose S and T such that is minimum. Thus, , and for any . Furthermore, due to , we obtain the following observation.
Observation 3.1
.
Let l be the number of the components of which are isomorphic to and let . Let H be the subgraph inferred from by deleting those l components isomorphic to . Let be a set of vertices that contains exactly a−1 vertices in each component of in .
If , then from (Equation2(2) (2) ) and Observation 3.1, we yield , i.e. which implies and . Thus, . In light of the definition of isolated toughness, we deduce and Let , where and . Then, by and , we infer which implies that arrives at the maximum value when reaches its lower bound . Hence, which contradicts to .
Hence, we have . Let where is the union of components of H which satisfies that for each vertex and . By means of Lemma 2.3, has a maximum independent set and the covering set such that (3) (3) and (4) (4) where for and . Using the definition of H and , we verify that each component of has a vertex of degree at most a−2 in G−S. Clearly, if , then , and can be selected by Algorithm 1 (Gao et al., Citation2022):
Moreover, we have the following observation due to and at least one vertex in has degree at most a−2 in G−S.
Observation 3.2
If , then .
Set and . The subsequent discussion is divided into two situations.
Case 1. .
The following two claims confirm that or can not exist independently.
Claim 3.1
If , then .
Proof.
Suppose . Then by .
We partition into two subsets.
: if there exists such that ;
: if there is no intersection between and .
We yield and In view of Observation 3.1, we deduce which implies .
Moreover, and thus Let , where and . Then, we obtain If n = 1 and , then is negative, thus which contradicts to . Hence, is a non-negative term and reaches the maximum value when reaches its lower bound . Therefore, which contradicts to the hypothesis of .
Claim 3.2
If , then .
Proof.
Suppose . We yield by , and hence .
Let be vertices in such that and . Then , and We acquire where and It is clear to see that to acquire the extremum isolated toughness, we maximise with the given number of , and thus only one vertex in has degree a−2 in G−S and others have degree a−1 in G−S. To bound the value of , it is imperative to re-compute the upper bound of as follows: Using Observation 3.2, we infer which implies , and hence .
In terms of the definition of isolated toughness, we verify Let , where and . Then, we infer If is negative, then n = 1 and which contradicts to . Hence, is non-negative and arrives at the maximum value when reaches the lower bound . We deduce which contradicts to and .
From Claim 3.1 and Claim 3.2, we check , and .
Denote as vertices in as defined in Claim 3.2. Then , and We acquire where and Similar to the discussion in Claim 3.2, to maximise , only one vertex in has degree a−2 in G−S and others have degree a−1 in G−S. To bound the value of , it is necessary to re-calculate the upper bound of : By means of Observation 3.2, we yield which implies , and hence .
Using the definition of , we obtain Let , where and . Then, If is negative, we get n = 1 and , which contradicts to . Hence, is non-negative and arrives at the maximum value when reaches the lower bound . We deduce which contradicts to and .
Case 2. .
Akin to Case 1, we verify that or can not exist independently.
Claim 3.3
If , then .
Proof.
Suppose . Then, we obtain , and .
If , then and . Thus, contradicts to Observation 3.1. Hence, .
In this case, where , and using the deduction in Claim 3.1, we get Using Observation 3.1, we deduce which implies .
Hence, Let , where and . Then, we acquire If is negative, then n = 1 and which contradicts to . Hence, is a non-negative term and it arrives at the maximum value when reaches its lower bound . We infer which contradicts to the hypothesis of isolated toughness.
Claim 3.4
If , then .
Proof.
Suppose , then and hence .
If , then we set and such that , thus . Hence, we deduce and a contradiction.
Hence, we get . Let be vertices in as defined in Claim 3.2, thus and . We have , and We infer where , and in view of the discussion in Claim 3.2, we yield It is noteworthy that, to maximise , only one vertex in has degree a−2 in G−S and others have degree a−1 in G−S. To bound the value of , we rewritten the upper bound of : According to Observation 3.2, we yield which implies , and hence .
Using the same fashion as presented before, we get Let , where and . Then, we acquire If is negative, then n = 1 and , which contradicts to . Hence, is a non-negative term and it arrives at the maximum value when reaches its lower bound . We infer which contradicts to and .
It verifies from Claim 3.3 and Claim 3.4 that , and . We check that where and In terms of the similar deduction to Case 1, we confirm that by Observation 3.2 and re-computing the supper bound of .
Therefore, we have Let , where and . Then, If is negative, we get n = 1 and , which contradicts to . Hence, is non-negative and arrives at the maximum value when reaches the lower bound . We deduce which contradicts to and .
Therefore, we complete the proof of Theorem 1.1.
4. Open problems
In this paper, we determine the sharp isolated toughness bound for a graph to be fractional -critical. Since fractional -factor is a specific case of the more general fractional factors. n the stage of computer network topology design, it needs to make a balance between network security and network construction cost. The denser the network, the greater the isolated toughness, the stronger the corresponding network's ability to resist attacks, and the stronger the network. However, such a high-density network requires high construction costs, which greatly increases the network construction and maintenance costs. The tight bound of the isolated toughness parameter of the fractional critical graph provides engineers an important reference index. The network constructed according to the tight bound can theoretically guarantee that data transmission can still be maintained when the network suffers certain damages, and at the same time ensure the minimum cost of network construction, thus cut the budget.
We raise the following problems for future studies (the concepts of all fractional factor and fractional -factor can be referred to the other related papers, and we skip the detailed explanation here).
Problem 4.1
What is the tight isolated toughness bound for all fractional -critical graphs?
Problem 4.2
What is the tight isolated toughness bound for fractional -critical graphs?
Acknowledgments
We thank the reviewers for their constructive comments in improving the quality of this paper.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Additional information
Funding
References
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