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  2. Connectivity (graph theory) - Wikipedia

    en.wikipedia.org/wiki/Connectivity_(graph_theory)

    The connectivity and edge-connectivity of G can then be computed as the minimum values of κ(u, v) and λ(u, v), respectively. In computational complexity theory , SL is the class of problems log-space reducible to the problem of determining whether two vertices in a graph are connected, which was proved to be equal to L by Omer Reingold in ...

  3. Algebraic connectivity - Wikipedia

    en.wikipedia.org/wiki/Algebraic_connectivity

    An example graph, with 6 vertices, diameter 3, connectivity 1, and algebraic connectivity 0.722 The algebraic connectivity (also known as Fiedler value or Fiedler eigenvalue after Miroslav Fiedler) of a graph G is the second-smallest eigenvalue (counting multiple eigenvalues separately) of the Laplacian matrix of G. [1]

  4. NetworkX - Wikipedia

    en.wikipedia.org/wiki/NetworkX

    NetworkX is suitable for operation on large real-world graphs: e.g., graphs in excess of 10 million nodes and 100 million edges. [ clarification needed ] [ 19 ] Due to its dependence on a pure-Python "dictionary of dictionary" data structure, NetworkX is a reasonably efficient, very scalable , highly portable framework for network and social ...

  5. Strongly connected component - Wikipedia

    en.wikipedia.org/wiki/Strongly_connected_component

    Several algorithms based on depth-first search compute strongly connected components in linear time.. Kosaraju's algorithm uses two passes of depth-first search. The first, in the original graph, is used to choose the order in which the outer loop of the second depth-first search tests vertices for having been visited already and recursively explores them if not.

  6. Laplacian matrix - Wikipedia

    en.wikipedia.org/wiki/Laplacian_matrix

    In the matrix notation, the adjacency matrix of the undirected graph could, e.g., be defined as a Boolean sum of the adjacency matrix of the original directed graph and its matrix transpose, where the zero and one entries of are treated as logical, rather than numerical, values, as in the following example:

  7. Modularity (networks) - Wikipedia

    en.wikipedia.org/wiki/Modularity_(networks)

    Many scientifically important problems can be represented and empirically studied using networks. For example, biological and social patterns, the World Wide Web, metabolic networks, food webs, neural networks and pathological networks are real world problems that can be mathematically represented and topologically studied to reveal some unexpected structural features. [1]

  8. N2 chart - Wikipedia

    en.wikipedia.org/wiki/N2_Chart

    The N 2 chart or N 2 diagram (pronounced "en-two" or "en-squared") is a chart or diagram in the shape of a matrix, representing functional or physical interfaces between system elements. It is used to systematically identify, define, tabulate, design, and analyze functional and physical interfaces.

  9. Bipartite network projection - Wikipedia

    en.wikipedia.org/wiki/Bipartite_network_projection

    Bipartite network projection is an extensively used method for compressing information about bipartite networks. [1] Since the one-mode projection is always less informative than the original bipartite graph, an appropriate method for weighting network connections is often required.