- Research
- Open Access
Hermitian-Randić matrix and Hermitian-Randić energy of mixed graphs
- Yong Lu^{1},
- Ligong Wang^{1}Email author and
- Qiannan Zhou^{1}
https://doi.org/10.1186/s13660-017-1329-8
© The Author(s) 2017
- Received: 30 November 2016
- Accepted: 23 February 2017
- Published: 3 March 2017
Abstract
Let M be a mixed graph and \(H(M)\) be its Hermitian-adjacency matrix. If we add a Randić weight to every edge and arc in M, then we can get a new weighted Hermitian-adjacency matrix. What are the properties of this new matrix? Motivated by this, we define the Hermitian-Randić matrix \(R_{H}(M)=(r_{h})_{kl}\) of a mixed graph M, where \((r_{h})_{kl}=-(r_{h})_{lk}=\frac{\mathbf{i}}{\sqrt {d_{k}d_{l}}}\) (\(\mathbf{i}=\sqrt{-1}\)) if \((v_{k},v_{l})\) is an arc of M, \((r_{h})_{kl}=(r_{h})_{lk}=\frac{1}{\sqrt{d_{k}d_{l}}}\) if \(v_{k}v_{l}\) is an undirected edge of M, and \((r_{h})_{kl}=0\) otherwise. In this paper, firstly, we compute the characteristic polynomial of the Hermitian-Randić matrix of a mixed graph. Furthermore, we give bounds on the Hermitian-Randić energy of a general mixed graph. Finally, we give some results about the Hermitian-Randić energy of mixed trees.
Keywords
- mixed graph
- Hermitian-adjacency matrix
- Hermitian-Randić matrix
- Hermitian-Randić energy
MSC
- 05C50
- 05C07
- 05C31
1 Introduction
In this paper, we only consider simple graphs without multiedges and loops. A graph M is said to be mixed if it is obtained from an undirected graph \(M_{U}\) by orienting a subset of its edges. We call \(M_{U}\) the underlying graph of M. Clearly, a mixed graph concludes both possibilities of all edges oriented and all edges undirected as extreme cases.
Let M be a mixed graph with vertex set \(V(M)=\{v_{1},v_{2},\ldots ,v_{n}\}\) and edge set \(E(M)\). For \(v_{i},v_{j}\in V(M)\), we denote an undirected edge joining two vertices \(v_{i}\) and \(v_{j}\) of M by \(v_{i}v_{j}\) (or \(v_{i}\leftrightarrow v_{j}\)). Denote a directed edge (or arc) from \(v_{i}\) to \(v_{j}\) by \((v_{i},v_{j})\) (or \(v_{i}\rightarrow v_{j}\)). In addition, let \(E_{0}(M)\) denote the set of all undirected edges and \(E_{1}(M)\) denote all the directed arcs set. Clearly, \(E(M)\) is the union of \(E_{0}(M)\) and \(E_{1}(M)\). A mixed graph is called mixed tree (or mixed bipartite graph) if its underlying graph is a tree (or bipartite graph). In general, the order, size, number of components and degree of a vertex of M are the same to those in \(M_{U}\). We use Bondy and Murty [1] for terminologies and notations not defined here.
Let G be a simple graph with vertex set \(\{v_{1},v_{2},\ldots,v_{n}\} \). The adjacency matrix of a simple graph G of order n is defined as the \(n\times n\) symmetric square matrix \(A=A(G)=(a_{ij})\), where \(a_{ij}=1\) if \(v_{i}v_{j}\) is an edge of G, otherwise \(a_{ij}=0\). We denote by \(d_{i}=d(v_{i})=d_{G}(v_{i})\) (\(i=1,2,\ldots,n\)) the degree of vertex \(v_{i}\). In addition, for a mixed graph M, if \(v_{i}\in V(M)\), then we also denote \(d_{i}=d(v_{i})=d_{M_{U}}(v_{i})\). The energy of the graph G (see the survey of Gutman, Li and Zhang [2] and the book of Li, Shi and Gutman [3]) is defined as \(\mathcal{E}_{A}(G)=\sum_{i=1}^{n}|\rho_{i}|\), where \(\rho_{1},\rho _{2},\ldots,\rho_{n}\) are all eigenvalues of \(A(G)\).
A convenient parameter of G is the general Randić index \(R_{\alpha}(G)\) defined as \(R_{\alpha}(G)=\sum_{uv\in E(G)}(d_{u}d_{v})^{\alpha}\), where the summation is over all (unordered) edges uv in G. The molecular structure-descriptor, first proposed by Randić [4] in 1975, is defined as the sum of \(\frac{1}{\sqrt{d_{u}d_{v}}}\) over all edges uv of G (with \(\alpha=-\frac{1}{2}\)). Nowadays, \(R=R(G)=\sum_{uv\in E(G)}\frac{1}{\sqrt{d_{u}d_{v}}}\) of G is referred to as the Randić index. Countless chemical applications, the mathematical properties and mathematical chemistry of the Randić index were reported in [5–7].
Gutman et al. [8] pointed out that the Randić-index-concept is purposeful to associate the graph G with a symmetric square matrix of order n, named Randić matrix \(R(G)=(r_{ij})\), where \(r_{ij}=\frac{1}{\sqrt{d_{i}d_{j}}}\) if \(v_{i}v_{j}\) is an edge of G, otherwise \(r_{ij}=0\). Let \(D(G)\) be the diagonal matrix of vertex degrees of G. If G has no isolated vertices, then \(R(G)=D(G)^{-\frac {1}{2}}A(G)D(G)^{-\frac{1}{2}}\).
The concept of Randić energy of a graph G, denoted by \(\mathcal{E}_{R}(G)\), was introduced in [9] as \(\mathcal {E}_{R}(G)=\sum_{i=1}^{n}|\gamma_{i}|\), where \(\gamma_{i}\) is the eigenvalues of \(R(G)\), \(i=1,2,\ldots,n\). Some basic properties of the Randić index, Randić matrix and Randić energy were determined in the papers [8–20].
An oriented graph \(G^{\sigma}\) is a digraph which assigns each edge of G a direction σ. The skew adjacency matrix associated to \(G^{\sigma}\) is the \(n\times n\) matrix \(S(G^{\sigma})=(s_{ij})\), where \(s_{ij}=-s_{ji}=1\) if \((v_{i},v_{j})\) is an arc of \(G^{\sigma}\), otherwise \(s_{ij}=s_{ji}=0\). The skew energy of \(G^{\sigma}\), denoted by \(\mathcal{E}_{S}(G^{\sigma})\), is defined as the sum of the norms of all the eigenvalues of \(S(G^{\sigma})\). For more details about skew energy, we can refer to [21, 22].
In 2016, Gu, Huang and Li [14] defined the skew Randić matrix \(R_{s}(G^{\sigma})=((r_{s})_{ij})\) of an oriented graph \(G^{\sigma}\) of order n, where \((r_{s})_{ij}=-(r_{s})_{ji}=\frac {1}{\sqrt{d_{i}d_{j}}}\) if \((v_{i},v_{j})\) is an arc of \(G^{\sigma}\), otherwise \((r_{s})_{ij}=(r_{s})_{ji}=0\). Let \(D(G)\) be the diagonal matrix of vertex degrees of G. If \(G^{\sigma}\) has no isolated vertices, then \(R_{s}(G^{\sigma})=D(G)^{-\frac{1}{2}}S(G^{\sigma })D(G)^{-\frac{1}{2}}\).
The Hermitian-adjacency matrix of a mixed graph M of order n is the \(n\times n\) matrix \(H(M)=(h_{kl})\), where \(h_{kl}=-h_{lk}= \mathbf{i}\) (\(\mathbf{i}=\sqrt{-1}\)) if \((v_{k},v_{l})\) is an arc of M, \(h_{kl}=h_{lk}=1\) if \(v_{k}v_{l}\) is an undirected edge of M, and \(h_{kl}=0\) otherwise. Obviously, \(H(M)=H(M)^{\ast}:={\overline{H(M)}}^{T}\). Thus all its eigenvalues are real. This matrix was introduced by Liu and Li in [23] and independently by Guo and Mohar in [24]. The Hermitian energy of a mixed graph M is defined as \(\mathcal {E}_{H}(M)=\sum^{n}_{i=1}|\lambda_{i}|\), where \(\lambda_{1},\lambda _{2},\ldots,\lambda_{n}\) are all eigenvalues of \(H(M)\). Denote by \(\operatorname{Sp}_{H}(M)=(\lambda_{1},\lambda_{2},\ldots,\lambda_{n})\) the spectrum of \(H(M)\). For more details about the Hermitian-adjacency matrix and the Hermitian energy of mixed graphs, we can refer to [23–28].
From the above we can see that if we add a Randić weight to every edge in a simple graph G, then we can get a Randić matrix \(R(G)\). If we add a Randić weight to every arc in an oriented graph \(G^{\sigma}\), then we can get a skew Randić matrix \(R_{s}(G^{\sigma})\). Let M be a mixed graph and \(H(M)\) be its Hermitian-adjacency matrix. If we add a Randić weight to every edge and arc in M, then we can get a new weighted Hermitian-adjacency matrix. What are the properties of this new matrix? Motivated by this, we define the Hermitian-Randić matrix of a mixed graph M.
Let \(D(M_{U})\) be the diagonal matrix of vertex degrees of \(M_{U}\). If M has no isolated vertices, then \(R_{H}(M)=D(M_{U})^{-\frac {1}{2}}H(M)D(M_{U})^{-\frac{1}{2}}\). For a mixed graph M, let \(R_{H}(M)\) be its Hermitian-Randić matrix. It is obvious that \(R_{H}(M)\) is a Hermitian matrix, so all its eigenvalues \(\mu_{1},\mu_{2},\ldots,\mu_{n}\) are real. The spectrum of \(R_{H}(M)\) is defined as \(\operatorname{Sp}_{R_{H}}(M)=(\mu_{1},\mu _{2},\ldots,\mu_{n})\). The energy of \(R_{H}(M)\), denoted by \(\mathcal {E}_{R_{H}}(M)\), is called Hermitian-Randić energy, which is defined as the sum of the absolute values of its eigenvalues of \(R_{H}(M)\), that is, \(\mathcal{E}_{R_{H}}(M)=\sum^{n}_{i=1}|\mu_{i}|\).
In this paper, we define the Hermitian-Randić matrix of a mixed graph M and study some basic characteristics of the Hermitian-Randić matrix of mixed graphs. In Section 2, we give the characteristic polynomial of the Hermitian-Randić matrix of a mixed graph M. In Section 3, we study some bounds on the Hermitian-Randić energy of mixed graphs with different parameters and give the conditions under which mixed graphs can attain those Hermitian-Randić energy bounds. In Section 4, we show that the Hermitian-Randić energy of a mixed tree is the same as the Randić energy of its underlying graph. In Section 5, we summarize the results of this paper and give some future works we will study.
2 Hermitian-Randić characteristic polynomial of a mixed graph
In this section, we will give the characteristic polynomial of a Hermitian-Randić matrix of a mixed graph M, i.e., the \(R_{H}\)-characteristic polynomial of M. At first, we will introduce some basic definitions.
The value of a mixed walk \(W=v_{1}v_{2}\cdots v_{l}\) is \(r_{h}(W)=(r_{h})_{12}(r_{h})_{23}(r_{h})_{(l-1)l}\). A mixed walk W is positive (or negative) if \(r_{h}(W)=\frac{1}{\sqrt {d_{1}d_{l}}d_{2}d_{3}\cdots d_{(l-1)}}\) (or \(r_{h}(W)=-\frac{1}{\sqrt {d_{1}d_{l}}d_{2}d_{3}\cdots d_{(l-1)}}\)). Note that for one direction the value of a mixed walk or a mixed cycle is α, then for the reversed direction its value is α̅. Thus, if the value of a mixed cycle C is \(\prod_{v_{j}\in V(C)}\frac{1}{d(v_{j})}\) (resp. \(-\prod_{v_{j}\in V(C)}\frac{1}{d(v_{j})}\)) in a direction, then its value is \(\prod_{v_{j}\in V(C)}\frac{1}{d(v_{j})}\) (resp. \(-\prod_{v_{j}\in V(C)}\frac{1}{d(v_{j})}\)) for the reversed direction. In these situations, we just term this mixed cycle a positive (resp. negative) mixed cycle without mentioning any direction.
If each mixed cycle is positive (resp. negative) in a mixed graph M, then M is positive (resp. negative). A mixed graph M is called an elementary graph if every component of M is an edge, an arc or a mixed cycle, where every edge-component in M is defined to be positive. A real spanning elementary subgraph of a mixed graph M is an elementary subgraph such that it contains all vertices of M and all its mixed cycles are real.
Now we will give two results which are similar to those in [23, 29, 30].
Theorem 2.1
Proof
Consider a term \(\operatorname{sgn}(\pi)(r_{h})_{1\pi(1)}(r_{h})_{2\pi(2)}\cdots (r_{h})_{n\pi(n)}\) in the expansion of \(\operatorname{det}R_{H}(M)\). If \(v_{k}v_{\pi(k)}\) is not an edge or arc of M, then \((r_{h})_{k\pi (k)}=0\); that is, this term vanishes. Thus, if the term corresponding to a permutation π is non-zero, then π is fixed-point-free and can be expressed uniquely as the composition of disjoint cycles of length at least 2. Consequently, each non-vanishing term in the expansion of \(\operatorname{det}R_{H}(M)\) gives rise to an elementary mixed graph \(M'\) of M with \(V(M')=V(M)\). That is, \(M'\) is a spanning elementary subgraph of M of order n.
A spanning elementary subgraph \(M'\) of M with \(s(M')\) number of mixed cycles (length ≥3) gives \(2^{s(M')}\) permutations π since, for each mixed cycle-component in \(M'\), there are two ways of choosing the corresponding cycles in π. For a vertex \(v_{k}\in V(M')\), we denote \(d_{k}=d(v_{k})=d_{M_{U}}(v_{k})\). Furthermore, if for some direction of a permutation π, a mixed cycle-component \(C_{1}\) has value \(\mathbf{i}\prod_{v_{j}\in V(C_{1})}\frac{1}{d(v_{j})}\) (or \(-\mathbf{i}\prod_{v_{j}\in V(C_{1})}\frac{1}{d(v_{j})}\)), then for the other direction \(C_{1}\) has value \(-\mathbf {i}\prod_{v_{j}\in V(C_{1})}\frac{1}{d(v_{j})}\) (or \(\mathbf {i}\prod_{v_{j}\in V(C_{1})}\frac{1}{d(v_{j})}\)) and vice versa. Thus, they cancel each other in the summation. In addition, if for some direction of a permutation π, \(C_{1}\) has value \(\prod_{v_{j}\in V(C_{1})}\frac{1}{d(v_{j})}\) (or \(-\prod_{v_{j}\in V(C_{1})}\frac {1}{d(v_{j})}\)), then for the other direction \(C_{1}\) has the same value. For each edge-component \((kl)\) corresponding to the factors \((r_{h})_{kl}(r_{h})_{lk}\) has value \(\frac{1}{\sqrt{d_{k}d_{l}}}\frac {1}{\sqrt{d_{l}d_{k}}}=\frac{1}{d_{k}d_{l}}\). For each arc-component \((kl)\) corresponding to the factors \((r_{h})_{kl}(r_{h})_{lk}\) has value \(\frac{\mathbf{i}\cdot(-\mathbf{i})}{\sqrt {d_{k}d_{l}}\sqrt{d_{l}d_{k}}}=\frac{1}{d_{k}d_{l}}\).
Since \(\operatorname{sgn}(\pi)=(-1)^{n-c(M')}=(-1)^{r(M')}\) and each real spanning elementary subgraph \(M'\) contributes \((-1)^{r(M')+l(M')}2^{s(M')}\prod_{v_{i}\in V(M')}\frac{1}{d_{M_{U}}(v_{i})}\) to the determinant of \(R_{H}(M)\). This completes the proof. □
Now, we shall obtain a description of all the coefficients of the characteristic polynomial \(P_{R_{H}}(M,x)\) of a mixed graph M.
Theorem 2.2
Proof
The proof follows from Theorem 2.1 and the fact that \((-1)^{k}a_{k}\) is the summation of determinants of all principal \(k\times k\) submatrices of \(R_{H}(M)\). □
Corollary 2.3
- (1)
If M is a mixed tree, then \((-1)^{k}a_{k}=\sum_{M'}(-1)^{r(M')}\prod_{v_{i}\in V(M')}\frac{1}{d_{M_{U}}(v_{i})}\).
- (2)
If M is a mixed graph and its underlying graph \(M_{U}\) is r regular (\(r\neq0\)), then \((-1)^{k}a_{k}=\sum_{M'}(-1)^{r(M')+l(M')}2^{s(M')}\frac{1}{r^{k}}\).
- (3)
If M is a mixed bipartite graph, then all coefficients of \(a_{\mathrm{odd}}\) are equal to 0, and its spectrum is symmetry about 0.
Then \(P_{R_{H}}(M,x)=P_{R_{H}}(M_{U},x)\), that is to say,
Theorem 2.4
If M is a positive mixed graph and \(M_{U}\) be its underlying graph, then \(\operatorname{Sp}_{R_{H}}(M)=\operatorname{Sp}_{R_{H}}(M_{U})\).
3 Bounds on the Hermitian-Randić energy of mixed graphs
In this section, we will give some bounds on the Hermitian-Randić energy of mixed graphs. First, we will give some properties of a Hermitian-Randić matrix of mixed graphs.
Lemma 3.1
- (1)
\(\mathcal{E}_{R_{H}}(M)=0\) if and only if \(M\cong\overline{K}_{n}\).
- (2)
If \(M=M_{1}\cup M_{2}\cup\cdots\cup M_{p}\), then \(\mathcal {E}_{R_{H}}(M)=\mathcal{E}_{R_{H}}(M_{1})+\mathcal {E}_{R_{H}}(M_{2})+\cdots+\mathcal{E}_{R_{H}}(M_{p})\).
From Lemma 3.1, we can obtain the following theorem.
Theorem 3.2
Proof
If M has l isolated vertices, then \(M=M'\cup\overline {K}_{l}\), where \(M'\) has no isolated vertices. By Lemma 3.1, we have \(\operatorname{Sp}_{R_{H}}(M)=\operatorname{Sp}_{R_{H}}(M')\cup\{0, l\text{ times}\}\) and an analogous relation holds for Hermitian-adjacency spectrum of M. That is, \(H(M)\) and \(R_{H}(M)\) have zero eigenvalues, therefore their determinants are equal to zero.
This completes the proof. □
Similar to Theorem 3.2, we can obtain the following theorem.
Theorem 3.3
If M is a mixed graph with vertex set \(V(M)=\{v_{1},v_{2},\ldots ,v_{n}\}\) and its underlying graph \(M_{U}\) is r regular, then \(\mathcal{E}_{R_{H}}(M)=\frac{1}{r}\mathcal{E}_{H}(M)\). In addition, if \(r=0\), then \(\mathcal{E}_{R_{H}}(M)=0\).
Proof
If \(r=0\), then M is the graph that has no edges. Then all the entries of \(R_{H}(M)\) are equal to 0, i.e., \(R_{H}(M)=\mathbf {0}\). Similarly, \(H(M)=\mathbf{0}\). Since all eigenvalues of the zero matrix are equal to 0, hence \(\mathcal{E}_{R_{H}}(M)=\mathcal {E}_{H}(M)=0\).
If \(r>0\), i.e., M is regular of degree \(r>0\), then \(d_{1}=d_{2}=\cdots =d_{n}=r\), where \(d_{k}\) is the degree of \(v_{k}\), \(k=1,2,\ldots,n\). Hence, \((r_{h})_{sk}=-(r_{h})_{ks}=\frac{\mathbf{i}}{r}\) if \((v_{s},v_{k})\) is an arc of M, \((r_{h})_{sk}=(r_{h})_{ks}=\frac {1}{r}\) if \(v_{s}v_{k}\) is an undirected edge of M, and \((r_{h})_{sk}=0\) otherwise.
This implies that \(R_{H}(M)=\frac{1}{r}H(M)\). Therefore, \(\mu _{i}=\frac{1}{r}\lambda_{i}\), where \(\mu_{i}\) is the eigenvalue of \(R_{H}(M)\), and \(\lambda_{i}\) is the eigenvalue of \(H(M)\) for \(i=1,2,\ldots,n\). Then this theorem follows from the definitions of \(\mathcal{E}_{R_{H}}(M)\) and \(\mathcal{E}_{H}(M)\). □
Similar to the results about the skew Randić energy in [14], we can establish the following lower and upper bounds for the Hermitian-Randić energy. First, we need the following theorem. Here and later, \(\mathbf{I}_{n}\) denotes the unit matrix of order n.
Theorem 3.4
Let M be a mixed graph of order n and \(\mu_{1}\geq\mu_{2}\geq\cdots \geq\mu_{n}\) be the Hermitian-Randić spectrum of \(R_{H}(M)\). Then \(|\mu_{1}|=|\mu_{2}|=\cdots=|\mu_{n}|\) if and only if there exists a constant \(c=|\mu_{i}|^{2}\) for all i such that \(R^{2}_{H}(M)=c \mathbf{I}_{n}\).
Proof
This completes the proof. □
Theorem 3.5
Proof
Let \(\{\mu_{1},\mu_{2},\ldots,\mu_{n}\}\) be the Hermitian-Randić spectrum of M, where \(\mu_{1}\geq\mu_{2}\geq \cdots\geq\mu_{n}\). Since \(\sum_{j=1}^{n}\mu_{j}^{2}=\operatorname{tr}(R_{H}^{2}(M))=\sum_{j=1}^{n}\sum_{k=1}^{n}(r_{h})_{jk}(r_{h})_{kj}=\sum_{j=1}^{n}\sum_{k=1}^{n}(r_{h})_{jk}\overline{(r_{h})}_{jk} =\sum_{j=1}^{n}\sum_{k=1}^{n}|(r_{h})_{jk}|^{2}=2R_{-1}(M_{U})\), where \(R_{-1}(M_{U})=\sum_{v_{j}v_{k}\in E(M_{U})}\frac{1}{d_{j}d_{k}}\) (unordered).
From the Cauchy-Schwarz inequality and the arithmetic geometric average inequality, we know that the equalities hold both in the lower bound and upper bound if and only if \(|\mu_{1}|=|\mu_{2}|=\cdots=|\mu _{n}|\), i.e., there exists a constant \(c=|\mu_{i}|^{2}\) for all i such that \(R^{2}_{H}(M)=c \mathbf{I}_{n}\).
This completes the proof. □
Corollary 3.6
Proof
If M is a mixed graph and its underlying graph \(M_{U}\) is r regular, then \(R_{-1}(M_{U})=\frac{m}{r^{2}}\) and \(2m=nr\). By Theorems 3.4 and 3.5, we can obtain the results. □
Lemma 3.7
[19]
- (1)
n is even and G is the disjoint union of \(n/2\) paths of length 1, or
- (2)
n is odd and G is the disjoint union of \((n-3)/2\) paths of length 1 and one path of length 2.
Combining Theorem 3.5 and Lemma 3.7, we can get upper and lower bounds for the Hermitian-Randić energy by replacing \(R_{-1}(M_{U})\) with other parameters. We now give bounds of the Hermitian-Randić energy of a mixed graph with respect to its order.
Theorem 3.8
Proof
Let \(R_{H}(M)\) be the Hermitian-Randić matrix of M and \(\mu_{1}\geq\mu_{2}\geq\cdots\geq\mu_{n}\) be the Hermitian-Randić spectrum of \(R_{H}(M)\).
Hence, \(\sum_{k< l}\mu_{k}\mu_{l}=-R_{-1}(M_{U})\).
From the proof above and Lemma 3.7, we know that the equality in the lower bound holds if and only if \(M_{U}\) is a complete graph and \(\mu_{k}\mu_{l}\geq0\) or \(\mu_{k}\mu _{l}\leq0\) for all \(1\leq k< l\leq n\). Note that \(\sum_{k=1}^{n}\mu _{k}=0\) and M has no isolated vertices, so the former case can not happen. Hence, the equality in the lower bound holds if and only if \(M_{U}\) is a complete graph and \(\mu_{1}=-\mu_{n}\neq0\), \(\mu_{j}=0\), \(j=2,\ldots,n-1\).
This completes the proof. □
Remark 3.9
It should be pointed out that when M is a complete mixed graph, its Hermitian-Randić spectrum is not unique. For example, let \(M_{U}=K_{3}\), if all edges of \(E(M)\) are oriented, then we have \(\mu _{1}=-\mu_{3}=\frac{\sqrt{3}}{2}\), \(\mu_{2}=0\), then we can obtain the lower bound in Theorem 3.8. If some edges of \(E(M)\) are undirected, then we can not obtain the lower bound in Theorem 3.8. For example, if \((r_{h})_{12}=(r_{h})_{32}=\frac{i}{2}\), \((r_{h})_{13}=\frac{1}{2}\), then \(\mu_{1}=1\) and \(\mu_{2}=\mu_{3}=-\frac {1}{2}\). Hence, the problem of determining all complete mixed graphs for which the lower bound in Theorem 3.8 is attained appears to be somewhat more difficult.
To deduce more bounds on \(\mathcal{E}_{R_{H}}(M)\), the following lemma is needed.
Lemma 3.10
[31]
Now we turn to new bounds on \(\mathcal{E}_{R_{H}}(M)\).
Theorem 3.11
Proof
Let \(S=\sum_{1\leq i\neq j\leq n}|\mu_{i}||\mu_{j}|\), \(x_{i}=|\mu_{i}|\) and \(y_{i}=\mathcal{E}_{R_{H}}(M)-|\mu_{i}|\), \(i=1,2,\ldots,n\). Then \(S=\sum^{n}_{i=1}x_{i}y_{i}\).
This completes the proof. □
Note that the right-hand side of (1) is a non-decreasing function on \(\alpha\geq0\). Combining this with Theorem 3.4, we have the following corollary.
Corollary 3.12
In particular, if M is a connected mixed bipartite graph, then we have the following theorem.
Theorem 3.13
Proof
Let \(T=\sum_{1\leq i\neq j\leq\lfloor\frac{n}{2}\rfloor}\mu_{i}\mu _{j}\), \(x_{i}=\mu_{i}\) and \(y_{i}=\frac{\mathcal{E}_{R_{H}}(M)}{2}-\mu _{i}\), \(i=1,2,\ldots,\lfloor\frac{n}{2}\rfloor\). Then \(T=\sum^{\lfloor\frac{n}{2}\rfloor}_{i=1}x_{i}y_{i}\).
This completes the proof. □
Note that the right-hand side of (3) is a non-decreasing function on \(\alpha\geq0\). Combining this with Theorem 3.4, we have the following corollary.
Corollary 3.14
4 Hermitian-Randić energy of trees
In [21], the authors proved that the skew energy of a directed tree is independent of its orientation. In [14], the authors showed that the skew Randić energy of a directed tree has the same result. In this section, we will show that the Hermitian-Randić energy also has the same result. In the beginning of this section, we first characterize the mixed graphs with cut-edge.
Theorem 4.1
Let M be a mixed graph of order n, and \(e=uv\) is an edge of M. If uv is a cut-edge of \(M_{U}\), where \(M_{U}\) is the underlying graph of M, then the spectrum and energy of \(R_{H}(M)\) are unchanged when the edge uv is replaced with a single arc uv or vu and vice versa.
Proof
Combining (5) and (6), we have \(a_{k}(M)-a_{k}(M_{1})=0\) for any integer k.
Thus \(\operatorname{Sp}_{R_{H}}(M)=\operatorname{Sp}_{R_{H}}(M_{1})\). Moreover, \(\mathcal {E}_{{R_{H}}}(M)=\mathcal{E}_{{R_{H}}}(M_{1})\).
Similarly, we can prove that \(\operatorname{Sp}_{R_{H}}(M)=\operatorname{Sp}_{R_{H}}(M_{2})\) and \(\mathcal{E}_{{R_{H}}}(M)=\mathcal{E}_{{R_{H}}}(M_{2})\), where \(M_{2}\) is the mixed graph obtained from M by replacing the arc uv or vu with the edge uv. □
Thus, the Hermitian-Randić spectrum and the Hermitian-Randić energy are invariants when reversing the cut-arc’s orientation or unorienting it or orienting an undirected cut-edge. By applying Theorem 4.1, we can obtain the following corollaries.
Corollary 4.2
Let T be a mixed tree of order n and \(T'\) be the mixed tree obtained from T by reversing the orientations of all the arcs incident with a particular vertex of T. Then \(\mathcal{E}_{R_{H}}(T)=\mathcal{E}_{R_{H}}(T')\).
Corollary 4.3
- (1)
The Hermitian-Randić energy of T is independent of its orientation of the arc set.
- (2)
The Hermitian-Randić energy of T is the same as the Randić energy of \(T_{U}\).
5 Conclusions
In this paper, we define the Hermitian-Randić matrix of a mixed graph M and give the definitions of Hermitian-Randić characteristic polynomial and Hermitian-Randić energy of a mixed graph M. We give the bounds on the Hermitian-Randić energy of a mixed graph M with respect to its order, the Hermitian-Randić spectrum and a general Randić index (with \(\alpha=-1\)). We also obtain that the Hermitian-Randić energy of a mixed tree is the same as the Randić energy of its underlying graph.
Our future work will focus more on the characterizations of the Hermitian-Randić matrix of mixed graphs, such as the Hermitian-Randić spectrum of a complete mixed graph, more bounds on the Hermitian-Randić energy of mixed graphs with other parameters and mixed graphs that share the same Hermitian-Randić spectra with their underlying graphs.
Declarations
Acknowledgements
This work is supported by the National Natural Science Foundations of China (No.11171273).
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Authors’ Affiliations
References
- Bondy, JA, Murty, USR: Graph Theory with Applications. Elsevier, New York (1976) View ArticleMATHGoogle Scholar
- Gutman, I, Li, XL, Zhang, JB: Graph energy. In: Dehmer, M, Emmert-Streib, F (eds.) Analysis of Complex Network: From Biology to Linguistics, pp. 145-174. Wiley-VCH Verlag, Weinheim (2009) View ArticleGoogle Scholar
- Li, XL, Shi, YT, Gutman, I: Graph Energy. Springer, New York (2012) View ArticleMATHGoogle Scholar
- Randić, M: On characterization of molecular branching. J. Am. Chem. Soc. 97, 6609-6615 (1975) View ArticleGoogle Scholar
- Li, XL, Gutman, I: Mathematical Aspects of Randić-Type Molecular Structure Descriptors. Univ. Kragujevac, Kragujevac (2006) MATHGoogle Scholar
- Li, XL, Shi, YT: A survey on the Randić index. MATCH Commun. Math. Comput. Chem. 59, 127-156 (2008) MathSciNetMATHGoogle Scholar
- Randić, M: On history of the Randić index and emerging hostility toward chemical graph theory. MATCH Commun. Math. Comput. Chem. 59, 5-124 (2008) MathSciNetMATHGoogle Scholar
- Gutman, I, Furtula, B, Bozkurt, Ş: On Randić energy. Linear Algebra Appl. 422, 50-57 (2014) View ArticleMATHGoogle Scholar
- Bozkurt, Ş, Güngör, AD, Gutman, I, Çevik, AS: Randić matrix and Randić energy. MATCH Commun. Math. Comput. Chem. 64, 239-250 (2010) MathSciNetMATHGoogle Scholar
- Bozkurt, Ş, Bozkurt, D: Randić energy and Randić Estrada index of a graph. Eur. J. Pure Appl. Math. 5, 88-96 (2012) MathSciNetMATHGoogle Scholar
- Bozkurt, Ş, Bozkurt, D: Sharp upper bounds for energy and Randić energy. MATCH Commun. Math. Comput. Chem. 70, 669-680 (2013) MathSciNetMATHGoogle Scholar
- Bozkurt, Ş, Güngör, AD, Gutman, I: Randić spectral radius and Randić energy. MATCH Commun. Math. Comput. Chem. 64, 321-334 (2010) MathSciNetMATHGoogle Scholar
- Gu, R, Huang, F, Li, XL: General Randić matrix and general Randić energy. Trans. Comb. 3(3), 21-33 (2014) MathSciNetGoogle Scholar
- Gu, R, Huang, F, Li, XL: Skew Randić matrix and skew Randić energy. Trans. Comb. 5(1), 1-14 (2016) MathSciNetView ArticleGoogle Scholar
- Gu, R, Li, XL, Liu, JF: Note on three results on Randić energy and incidence energy. MATCH Commun. Math. Comput. Chem. 73, 61-71 (2015) MathSciNetGoogle Scholar
- Li, JX, Guo, JM, Shiu, WC: A note on Randić energy. MATCH Commun. Math. Comput. Chem. 74, 389-398 (2015) MathSciNetGoogle Scholar
- Li, XL, Wang, JF: Randić energy and Randić eigenvalues. MATCH Commun. Math. Comput. Chem. 73, 73-80 (2015) MathSciNetGoogle Scholar
- Li, XL, Yang, YT: Best lower and upper bounds for the Randić index \(R_{-1}\) of chemical trees. MATCH Commun. Math. Comput. Chem. 52, 147-156 (2004) MATHGoogle Scholar
- Li, XL, Yang, YT: Sharp bounds for the general Randić index. MATCH Commun. Math. Comput. Chem. 51, 155-166 (2004) MATHGoogle Scholar
- Shi, YT: Note on two generalizations of the Randić index. Appl. Math. Comput. 265, 1019-1025 (2015) MathSciNetGoogle Scholar
- Adiga, C, Balakrishnan, R, So, W: The skew energy of a digraph. Linear Algebra Appl. 432, 1825-1835 (2010) MathSciNetView ArticleMATHGoogle Scholar
- Li, XL, Lian, HS: Skew energy of oriented graphs. In: Gutman, I, Li, XL (eds.) Energies of Graphs - Theory and Applications. Mathematical Chemistry Monograph, vol. 17, pp. 191-236 (2016). Or available at arXiv:1304.5707 (2013) Google Scholar
- Liu, JX, Li, XL: Hermitian-adjacency matrices and Hermitian energies of mixed graphs. Linear Algebra Appl. 466, 182-207 (2015) MathSciNetView ArticleMATHGoogle Scholar
- Guo, K, Mohar, B: Hermitian adjacency matrix of digraphs and mixed graphs. J. Graph Theory (2016). doi:10.1002/jgt.22057 Google Scholar
- Chen, XL, Li, XL, Zhang, YY: 3-regular mixed graphs with optimum Hermitian energy. Linear Algebra Appl. 496, 475-486 (2016) MathSciNetView ArticleMATHGoogle Scholar
- Mohar, B: Hermitian adjacency spectrum and switching equivalence of mixed graphs. Linear Algebra Appl. 489, 324-340 (2016) MathSciNetView ArticleMATHGoogle Scholar
- Yu, GH, Liu, X, Qu, H: Singularity of Hermitian (quasi-)Laplacian matrix of mixed graphs. Appl. Math. Comput. 293, 287-292 (2017) MathSciNetGoogle Scholar
- Yu, GH, Qu, H: Hermitian Laplacian matrix and positive of mixed graphs. Appl. Math. Comput. 269, 70-76 (2015) MathSciNetGoogle Scholar
- Gong, SC, Xu, GH: The characteristic polynomial and the matchings polynomial of a weighted oriented graph. Linear Algebra Appl. 436, 3597-3607 (2012) MathSciNetView ArticleMATHGoogle Scholar
- Hou, YP, Lei, TG: Characteristic polynomials of skew-adjacency matrices of oriented graphs. Electron. J. Comb. 18, #P156 (2011) MathSciNetMATHGoogle Scholar
- Dragomir, SS: A generalization of Grüss’s inequality in inner product spaces and applications. J. Math. Anal. Appl. 237, 74-82 (1999) MathSciNetView ArticleMATHGoogle Scholar