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  2. Spectral graph theory - Wikipedia

    en.wikipedia.org/wiki/Spectral_graph_theory

    Spectral graph theory emerged in the 1950s and 1960s. Besides graph theoretic research on the relationship between structural and spectral properties of graphs, another major source was research in quantum chemistry , but the connections between these two lines of work were not discovered until much later. [ 15 ]

  3. Fan Chung - Wikipedia

    en.wikipedia.org/wiki/Fan_Chung

    Fan-Rong King Chung Graham (Chinese: 金芳蓉; pinyin: Jīn Fāngróng; born October 9, 1949), known professionally as Fan Chung, is a Taiwanese-born American mathematician who works mainly in the areas of spectral graph theory, extremal graph theory and random graphs, in particular in generalizing the Erdős–Rényi model for graphs with general degree distribution (including power-law ...

  4. Expander mixing lemma - Wikipedia

    en.wikipedia.org/wiki/Expander_mixing_lemma

    The expander mixing lemma intuitively states that the edges of certain -regular graphs are evenly distributed throughout the graph. In particular, the number of edges between two vertex subsets S {\displaystyle S} and T {\displaystyle T} is always close to the expected number of edges between them in a random d {\displaystyle d} - regular graph ...

  5. Ramanujan graph - Wikipedia

    en.wikipedia.org/wiki/Ramanujan_graph

    In the mathematical field of spectral graph theory, a Ramanujan graph is a regular graph whose spectral gap is almost as large as possible (see extremal graph theory). Such graphs are excellent spectral expanders .

  6. Algebraic graph theory - Wikipedia

    en.wikipedia.org/wiki/Algebraic_graph_theory

    Algebraic graph theory is a branch of mathematics in which algebraic methods are applied to problems about graphs. This is in contrast to geometric, combinatoric, or algorithmic approaches. There are three main branches of algebraic graph theory, involving the use of linear algebra, the use of group theory, and the study of graph invariants.

  7. Graph Fourier transform - Wikipedia

    en.wikipedia.org/wiki/Graph_Fourier_transform

    Analogously to the classical Fourier transform, the eigenvalues represent frequencies and eigenvectors form what is known as a graph Fourier basis. The Graph Fourier transform is important in spectral graph theory. It is widely applied in the recent study of graph structured learning algorithms, such as the widely employed convolutional networks.

  8. Spectrum (functional analysis) - Wikipedia

    en.wikipedia.org/wiki/Spectrum_(functional_analysis)

    The study of spectra and related properties is known as spectral theory, which has numerous applications, most notably the mathematical formulation of quantum mechanics. The spectrum of an operator on a finite-dimensional vector space is precisely the set of eigenvalues. However an operator on an infinite-dimensional space may have additional ...

  9. Laplacian matrix - Wikipedia

    en.wikipedia.org/wiki/Laplacian_matrix

    The Laplacian matrix is the easiest to define for a simple graph, but more common in applications for an edge-weighted graph, i.e., with weights on its edges — the entries of the graph adjacency matrix. Spectral graph theory relates properties of a graph to a spectrum, i.e., eigenvalues, and eigenvectors of matrices associated with the graph ...