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  2. Eigenfunction - Wikipedia

    en.wikipedia.org/wiki/Eigenfunction

    As shown in an earlier example, the solution of Equation is the exponential = /. Equation is the time-independent Schrödinger equation. The eigenfunctions φ k of the Hamiltonian operator are stationary states of the quantum mechanical system, each with a corresponding energy E k. They represent allowable energy states of the system and may be ...

  3. Eigenvalues and eigenvectors - Wikipedia

    en.wikipedia.org/wiki/Eigenvalues_and_eigenvectors

    An example of an eigenvalue equation where the transformation is represented in terms of a differential operator is the time-independent Schrödinger equation in quantum mechanics: H ψ E = E ψ E {\displaystyle H\psi _{E}=E\psi _{E}\,}

  4. Eigenvalues and eigenvectors of the second derivative

    en.wikipedia.org/wiki/Eigenvalues_and...

    Note that there are 2n + 1 of these values, but only the first n + 1 are unique. The (n + 1)th value gives us the zero vector as an eigenvector with eigenvalue 0, which is trivial. This can be seen by returning to the original recurrence. So we consider only the first n of these values to be the n eigenvalues of the Dirichlet - Neumann problem.

  5. Sturm–Liouville theory - Wikipedia

    en.wikipedia.org/wiki/Sturm–Liouville_theory

    The differential equation is said to be in Sturm–Liouville form or self-adjoint form.All second-order linear homogenous ordinary differential equations can be recast in the form on the left-hand side of by multiplying both sides of the equation by an appropriate integrating factor (although the same is not true of second-order partial differential equations, or if y is a vector).

  6. Graph Fourier transform - Wikipedia

    en.wikipedia.org/wiki/Graph_Fourier_transform

    In mathematics, the graph Fourier transform is a mathematical transform which eigendecomposes the Laplacian matrix of a graph into eigenvalues and eigenvectors. Analogously to the classical Fourier transform , the eigenvalues represent frequencies and eigenvectors form what is known as a graph Fourier basis .

  7. Eigenvalue algorithm - Wikipedia

    en.wikipedia.org/wiki/Eigenvalue_algorithm

    Given an n × n square matrix A of real or complex numbers, an eigenvalue λ and its associated generalized eigenvector v are a pair obeying the relation [1] =,where v is a nonzero n × 1 column vector, I is the n × n identity matrix, k is a positive integer, and both λ and v are allowed to be complex even when A is real.l When k = 1, the vector is called simply an eigenvector, and the pair ...

  8. Hilbert–Schmidt theorem - Wikipedia

    en.wikipedia.org/wiki/Hilbert–Schmidt_theorem

    Let (H, , ) be a real or complex Hilbert space and let A : H → H be a bounded, compact, self-adjoint operator.Then there is a sequence of non-zero real eigenvalues λ i, i = 1, …, N, with N equal to the rank of A, such that |λ i | is monotonically non-increasing and, if N = +∞, + =

  9. Calculus of variations - Wikipedia

    en.wikipedia.org/wiki/Calculus_of_Variations

    This variational characterization of eigenvalues leads to the Rayleigh–Ritz method: choose an approximating as a linear combination of basis functions (for example trigonometric functions) and carry out a finite-dimensional minimization among such linear combinations. This method is often surprisingly accurate.