The vertex that does not have any weighting assigned to it in the graph is called an unweighted vertex.
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A Hamiltonian cycle in a bipartite graph is a cycle that visits every vertex exactly once and ends at the starting vertex. It is significant because it provides a way to traverse the entire graph efficiently. Having a Hamiltonian cycle in a bipartite graph ensures that the graph is well-connected and has a strong structure, as it indicates that there is a path that visits every vertex without repeating any. This enhances the overall connectivity and accessibility of the graph, making it easier to analyze and navigate.
The bipartite graph algorithm can be implemented using depth-first search (DFS) by assigning colors to each vertex as it is visited. If a vertex is visited and its neighbor has the same color, then the graph is not bipartite. If all vertices can be visited without any conflicts in colors, then the graph is bipartite.
To eulerize a graph and ensure that every vertex has an even degree, you can add new edges to the graph without creating any new vertices. This can be done by finding and adding paths between pairs of odd-degree vertices until all vertices have an even degree.
An irreducible graph is a graph where every pair of vertices is connected by a path. This means that there are no isolated vertices or disconnected components in the graph. The property of irreducibility ensures that the graph is connected, meaning that there is a path between any two vertices in the graph. This connectivity property is important in analyzing the structure and behavior of the graph, as it allows for the study of paths, cycles, and other connectivity-related properties.
The minimum spanning tree of an undirected graph g is the smallest tree that connects all the vertices in the graph without forming any cycles. It is a subgraph of the original graph that includes all the vertices and has the minimum possible total edge weight.