Description: Graph representation refers to the way a graph is stored in memory, typically using adjacency lists or adjacency matrices. A graph is a mathematical structure consisting of a set of nodes (or vertices) and a set of edges (or links) connecting pairs of nodes. Graph representation is crucial in computer science and graph theory, as it allows algorithms to efficiently manipulate and analyze these structures. Adjacency lists store each node along with a list of its adjacent nodes, which is space-efficient, especially for sparse graphs. On the other hand, adjacency matrices use a two-dimensional matrix where rows and columns represent nodes, and cells indicate the existence of edges between them. This representation is more suitable for dense graphs, although it consumes more memory. The choice of the appropriate representation depends on the characteristics of the graph and the operations to be performed, such as pathfinding, cycle detection, or connectivity evaluation. In summary, graph representation is a fundamental aspect of the study and application of graphs across various disciplines, including computer science, mathematics, biology, and social sciences.
