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  2. Positive operator - Wikipedia

    en.wikipedia.org/wiki/Positive_operator

    In mathematics (specifically linear algebra, operator theory, and functional analysis) as well as physics, a linear operator acting on an inner product space is called positive-semidefinite (or non-negative) if, for every ⁡ (), , and , , where ⁡ is the domain of .

  3. Positive semidefinite - Wikipedia

    en.wikipedia.org/wiki/Positive_semidefinite

    In mathematics, positive semidefinite may refer to: Positive semidefinite function; Positive semidefinite matrix; Positive semidefinite quadratic form;

  4. Gram matrix - Wikipedia

    en.wikipedia.org/wiki/Gram_matrix

    The Gram matrix is symmetric in the case the inner product is real-valued; it is Hermitian in the general, complex case by definition of an inner product. The Gram matrix is positive semidefinite, and every positive semidefinite matrix is the Gramian matrix for some set of vectors. The fact that the Gramian matrix is positive-semidefinite can ...

  5. Copositive matrix - Wikipedia

    en.wikipedia.org/wiki/Copositive_matrix

    The class of copositive matrices can be characterized using principal submatrices. One such characterization is due to Wilfred Kaplan: [6]. A real symmetric matrix A is copositive if and only if every principal submatrix B of A has no eigenvector v > 0 with associated eigenvalue λ < 0.

  6. Square root of a matrix - Wikipedia

    en.wikipedia.org/wiki/Square_root_of_a_matrix

    A positive semidefinite matrix A can also have many matrices B such that =. However, A always has precisely one square root B that is both positive semidefinite and symmetric. In particular, since B is required to be symmetric, B = B T {\displaystyle B=B^{\textsf {T}}} , so the two conditions A = B B {\displaystyle A=BB} or A = B T B ...

  7. Polar decomposition - Wikipedia

    en.wikipedia.org/wiki/Polar_decomposition

    In mathematics, the polar decomposition of a square real or complex matrix is a factorization of the form =, where is a unitary matrix and is a positive semi-definite Hermitian matrix (is an orthogonal matrix and is a positive semi-definite symmetric matrix in the real case), both square and of the same size.

  8. Trace distance - Wikipedia

    en.wikipedia.org/wiki/Trace_distance

    The trace distance is defined as half of the trace norm of the difference of the matrices: (,):= ‖ ‖ = [() † ()], where ‖ ‖ ⁡ [†] is the trace norm of , and is the unique positive semidefinite such that = (which is always defined for positive semidefinite ).

  9. Trace inequality - Wikipedia

    en.wikipedia.org/wiki/Trace_inequality

    Let denote the space of Hermitian matrices, + denote the set consisting of positive semi-definite Hermitian matrices and + + denote the set of positive definite Hermitian matrices. For operators on an infinite dimensional Hilbert space we require that they be trace class and self-adjoint , in which case similar definitions apply, but we discuss ...

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