4.3 Article

Some mixed graphs with H-rank 4, 6 or 8

期刊

JOURNAL OF COMBINATORIAL OPTIMIZATION
卷 41, 期 3, 页码 678-693

出版社

SPRINGER
DOI: 10.1007/s10878-021-00704-6

关键词

H-rank; Switching equivalence; Mixed bipartite graph

资金

  1. National Natural Science Foundation of China [11871398]
  2. Natural Science Basic Research Plan in Shaanxi Province of China [2018JM1032]
  3. Fundamental Research Funds for the Central Universities [3102019ghjd003]
  4. Innovation and Creation for Graduate Students in Northwestern Polytechnical University [ZZ2019031]

向作者/读者索取更多资源

This paper explores the phenomenon of twins in mixed graphs and the properties of twin reduction graphs, providing upper and lower bounds for the number of vertices in certain cases and characterizing twin reduction graphs for connected mixed bipartite graphs with specific H-ranks. It also identifies all connected mixed graphs with certain H-ranks among those containing induced mixed odd cycles of certain lengths.
The H-rank of a mixed graph G(alpha) is defined to be the rank of its Hermitian adjacency matrix H(G(alpha)). If G(alpha) is switching equivalent to a mixed graph (G(alpha))', and two vertices u, v of G(alpha) have exactly the same neighborhood in (G(alpha))', then u and v are said to be twins. The twin reduction graph T-G alpha of G(alpha) is a mixed graph whose vertices are the equivalence classes, and [u][v]is an element of E(T-G alpha) if uv is an element of E((G(alpha))'), where [u] denotes the equivalence class containing the vertex u. In this paper, we give the upper (resp., lower) bound of the number of vertices of the twin reduction graphs of connected mixed bipartite graphs, and characterize all twin reduction graphs of the connected mixed bipartite graphs with H-rank 4 (resp., 6 or 8). Then, we characterize all connected mixed graphs with H-rank 4 (resp., 6 or 8) among all mixed graphs containing induced mixed odd cycles whose lengths are no less than 5 (resp., 7 or 9).

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.3
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据