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  2. Eigenvalues and eigenvectors - Wikipedia

    en.wikipedia.org/wiki/Eigenvalues_and_eigenvectors

    Moreover, if the entire vector space V can be spanned by the eigenvectors of T, or equivalently if the direct sum of the eigenspaces associated with all the eigenvalues of T is the entire vector space V, then a basis of V called an eigenbasis can be formed from linearly independent eigenvectors of T. When T admits an eigenbasis, T is ...

  3. Eigendecomposition of a matrix - Wikipedia

    en.wikipedia.org/wiki/Eigendecomposition_of_a_matrix

    Let A be a square n × n matrix with n linearly independent eigenvectors q i (where i = 1, ..., n).Then A can be factored as = where Q is the square n × n matrix whose i th column is the eigenvector q i of A, and Λ is the diagonal matrix whose diagonal elements are the corresponding eigenvalues, Λ ii = λ i.

  4. Complete set of commuting observables - Wikipedia

    en.wikipedia.org/wiki/Complete_set_of_commuting...

    Proof that a common eigenbasis implies commutation. Let {| } be a set of orthonormal states (i.e., | =,) that form a complete eigenbasis for each of the two compatible observables and represented by the self-adjoint operators ^ and ^ with corresponding (real-valued) eigenvalues {} and {}, respectively.

  5. QR algorithm - Wikipedia

    en.wikipedia.org/wiki/QR_algorithm

    In the case when the matrix is depicted as a near-circle, the matrix can be replaced with one whose depiction is a perfect circle. In that case, the matrix is a multiple of the identity matrix, and its eigendecomposition is immediate. Be aware though that the resulting eigenbasis can be quite far from the original eigenbasis.

  6. Position operator - Wikipedia

    en.wikipedia.org/wiki/Position_operator

    In literature, more or less explicitly, we find essentially three main directions to address this issue. The position operator is defined on the subspace D X {\displaystyle D_{X}} of L 2 {\displaystyle L^{2}} formed by those equivalence classes ψ {\displaystyle \psi } whose product by the embedding x {\displaystyle \mathrm {x} } lives in the ...

  7. Self-adjoint operator - Wikipedia

    en.wikipedia.org/wiki/Self-adjoint_operator

    If we use the third choice of domain (with periodic boundary conditions), we can find an orthonormal basis of eigenvectors for A, the functions ():=. Thus, in this case finding a domain such that A is self-adjoint is a compromise: the domain has to be small enough so that A is symmetric, but large enough so that D ( A ∗ ) = D ( A ...

  8. Commuting matrices - Wikipedia

    en.wikipedia.org/wiki/Commuting_matrices

    Commuting matrices preserve each other's eigenspaces. [2] As a consequence, commuting matrices over an algebraically closed field are simultaneously triangularizable; that is, there are bases over which they are both upper triangular.

  9. 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 ...