We initiate the study of computational complexity of graph coverings, aka locally bijective graph homomorphisms, for {\em graphs with semi-edges}. The notion of graph covering is a discretization of coverings between surfaces or topological spaces, a notion well known and deeply studied in classical topology. Graph covers have found applications in discrete mathematics for constructing highly symmetric graphs, and in computer science in the theory of local computations. In 1991, Abello et al. asked for a classification of the computational complexity of deciding if an input graph covers a fixed target graph, in the ordinary setting (of graphs with only edges). Although many general results are known, the full classification is still open. In spite of that, we propose to study the more general case of covering graphs composed of normal edges (including multiedges and loops) and so-called semi-edges. Semi-edges are becoming increasingly popular in modern topological graph theory, as well as in mathematical physics. They also naturally occur in the local computation setting, since they are lifted to matchings in the covering graph. We show that the presence of semi-edges makes the covering problem considerably harder; e.g., it is no longer sufficient to specify the vertex mapping induced by the covering, but one necessarily has to deal with the edge mapping as well. We show some solvable cases, and completely characterize the complexity of the already very nontrivial problem of covering one- and two-vertex (multi)graphs with semi-edges. Our NP-hardness results are proven for simple input graphs, and in the case of regular two-vertex target graphs, even for bipartite ones. This provides a strengthening of previously known results for covering graphs without semi-edges, and may contribute to better understanding of this notion and its complexity.
翻译:我们开始研究图形覆盖的计算复杂性, aka 本地双向图形同质性。 图形覆盖的概念是将表面或地形空间之间的覆盖分解, 这是一个在古典地形学中广为人知和深入研究的概念。 图形覆盖在离散数学中找到了构建高度对称图形的应用程序, 在本地计算理论中发现了计算机科学中的应用程序。 1991年, Abello 等人要求将计算复杂性分类, 确定输入图形是否覆盖普通设置的固定目标图形( 图表只有边缘 ) 。 虽然许多一般结果已经为人所知, 完整的分类仍然开放。 尽管如此, 我们提议研究由正常边缘( 包括多端和环) 和所谓的半端组成的覆盖图的更一般案例。 半端对于现代的图形理论和数学物理学来说越来越受欢迎, 半端的计算结果也自然出现在本地计算中, 因为它们被提升到不完全匹配的图形中的两个目标( 图表只有边缘 ) 。 我们建议研究更清楚的是, 我们的半端的图像存在更深层次 。