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  2. Spectral layout - Wikipedia

    en.wikipedia.org/wiki/Spectral_layout

    Spectral layout drawing of random small-world network. For comparison, the same graph plotted as spring graph drawing. Spectral layout is a class of algorithm for drawing graphs. The layout uses the eigenvectors of a matrix, such as the Laplace matrix of the graph, as Cartesian coordinates of the graph's vertices.

  3. NetworkX - Wikipedia

    en.wikipedia.org/wiki/NetworkX

    The Spectral layout is based on the spectral properties of the graph's adjacency matrix. It uses the eigenvalues and eigenvectors of the adjacency matrix to position nodes in a low-dimensional space. Spectral layout tends to emphasize the global structure of the graph, making it useful for identifying clusters and communities. [15]

  4. Ramanujan graph - Wikipedia

    en.wikipedia.org/wiki/Ramanujan_graph

    It is still an open problem whether there are infinitely many -regular (non-bipartite) Ramanujan graphs for any . In particular, the problem is open for d = 7 {\displaystyle d=7} , the smallest case for which d − 1 {\displaystyle d-1} is not a prime power and hence not covered by Morgenstern's construction.

  5. Spectral graph theory - Wikipedia

    en.wikipedia.org/wiki/Spectral_graph_theory

    The smallest pair of cospectral mates is {K 1,4, C 4 ∪ K 1}, comprising the 5-vertex star and the graph union of the 4-vertex cycle and the single-vertex graph [1]. The first example of cospectral graphs was reported by Collatz and Sinogowitz [2] in 1957. The smallest pair of polyhedral cospectral mates are enneahedra with eight vertices each ...

  6. Hertzsprung–Russell diagram - Wikipedia

    en.wikipedia.org/wiki/Hertzsprung–Russell_diagram

    In 1910 Hans Oswald Rosenberg published a diagram plotting the apparent magnitude of stars in the Pleiades cluster against the strengths of the calcium K line and two hydrogen Balmer lines. [3] These spectral lines serve as a proxy for the temperature of the star, an early form of spectral classification.

  7. Laplacian matrix - Wikipedia

    en.wikipedia.org/wiki/Laplacian_matrix

    Spectral graph theory relates properties of a graph to a spectrum, i.e., eigenvalues, and eigenvectors of matrices associated with the graph, such as its adjacency matrix or Laplacian matrix. Imbalanced weights may undesirably affect the matrix spectrum, leading to the need of normalization — a column/row scaling of the matrix entries ...

  8. Tanabe–Sugano diagram - Wikipedia

    en.wikipedia.org/wiki/Tanabe–Sugano_diagram

    From the high-spin (left) side of the d 7 Tanabe–Sugano diagram, the ground state is 4 T 1 (F), and the spin multiplicity is a quartet. The diagram shows that there are three quartet excited states: 4 T 2, 4 A 2, and 4 T 1 (P). From the diagram one can predict that there are three spin-allowed transitions.

  9. Spectral method - Wikipedia

    en.wikipedia.org/wiki/Spectral_method

    Compute the Fourier transform (b j,k) of g.Compute the Fourier transform (a j,k) of f via the formula ().Compute f by taking an inverse Fourier transform of (a j,k).; Since we're only interested in a finite window of frequencies (of size n, say) this can be done using a fast Fourier transform algorithm.