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  2. Brouwer–Haemers graph - Wikipedia

    en.wikipedia.org/wiki/Brouwer–Haemers_graph

    The Brouwer–Haemers graph is the first in an infinite family of Ramanujan graphs defined as generalized Paley graphs over fields of characteristic three. [2] With the 3 × 3 {\displaystyle 3\times 3} Rook's graph and the Games graph , it is one of only three possible strongly regular graphs whose parameters have the form ( ( n 2 + 3 n − 1 ...

  3. Strongly regular graph - Wikipedia

    en.wikipedia.org/wiki/Strongly_regular_graph

    Andries Brouwer and Hendrik van Maldeghem (see #References) use an alternate but fully equivalent definition of a strongly regular graph based on spectral graph theory: a strongly regular graph is a finite regular graph that has exactly three eigenvalues, only one of which is equal to the degree k, of multiplicity 1.

  4. Category:Strongly regular graphs - Wikipedia

    en.wikipedia.org/wiki/Category:Strongly_regular...

    Download as PDF; Printable version; ... Berlekamp–Van Lint–Seidel graph; Brouwer–Haemers graph ... Text is available under the Creative Commons Attribution ...

  5. Brouwer's conjecture - Wikipedia

    en.wikipedia.org/wiki/Brouwer's_conjecture

    Brouwer has confirmed by computation that the conjecture is valid for all graphs with at most 10 vertices. [1] It is also known that the conjecture is valid for any number of vertices if t = 1, 2, n − 1, and n. For certain types of graphs, Brouwer's conjecture is known to be valid for all t and for any number of vertices

  6. Spectral graph theory - Wikipedia

    en.wikipedia.org/wiki/Spectral_graph_theory

    The 1980 monograph Spectra of Graphs [16] by Cvetković, Doob, and Sachs summarised nearly all research to date in the area. In 1988 it was updated by the survey Recent Results in the Theory of Graph Spectra. [17] The 3rd edition of Spectra of Graphs (1995) contains a summary of the further recent contributions to the subject. [15]

  7. Adjacency matrix - Wikipedia

    en.wikipedia.org/wiki/Adjacency_matrix

    For a simple graph with vertex set U = {u 1, …, u n}, the adjacency matrix is a square n × n matrix A such that its element A ij is 1 when there is an edge from vertex u i to vertex u j, and 0 when there is no edge. [1] The diagonal elements of the matrix are all 0, since edges from a vertex to itself are not

  8. Spectral layout - Wikipedia

    en.wikipedia.org/wiki/Spectral_layout

    The layout uses the eigenvectors of a matrix, such as the Laplace matrix of the graph, as Cartesian coordinates of the graph's vertices. The idea of the layout is to compute the two largest (or smallest) eigenvalues and corresponding eigenvectors of the Laplacian matrix of the graph and then use those for actually placing the nodes.

  9. Tietze extension theorem - Wikipedia

    en.wikipedia.org/wiki/Tietze_extension_theorem

    Pavel Urysohn. In topology, the Tietze extension theorem (also known as the Tietze–Urysohn–Brouwer extension theorem or Urysohn-Brouwer lemma [1]) states that any real-valued, continuous function on a closed subset of a normal topological space can be extended to the entire space, preserving boundedness if necessary.

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