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  2. Adjugate matrix - Wikipedia

    en.wikipedia.org/wiki/Adjugate_matrix

    Adjugate matrix. In linear algebra, the adjugate of a square matrix A is the transpose of its cofactor matrix and is denoted by adj (A). [1][2] It is also occasionally known as adjunct matrix, [3][4] or "adjoint", [5] though the latter term today normally refers to a different concept, the adjoint operator which for a matrix is the conjugate ...

  3. Hermitian matrix - Wikipedia

    en.wikipedia.org/wiki/Hermitian_matrix

    Hermitian matrices are applied in the design and analysis of communications system, especially in the field of multiple-input multiple-output (MIMO) systems. Channel matrices in MIMO systems often exhibit Hermitian properties. In graph theory, Hermitian matrices are used to study the spectra of graphs. The Hermitian Laplacian matrix is a key ...

  4. Conjugate transpose - Wikipedia

    en.wikipedia.org/wiki/Conjugate_transpose

    Conjugate transpose. In mathematics, the conjugate transpose, also known as the Hermitian transpose, of an complex matrix is an matrix obtained by transposing and applying complex conjugation to each entry (the complex conjugate of being , for real numbers and ). There are several notations, such as or , [1] , [2] or (often in physics) .

  5. Hermitian adjoint - Wikipedia

    en.wikipedia.org/wiki/Hermitian_adjoint

    Hermitian adjoint. In mathematics, specifically in operator theory, each linear operator on an inner product space defines a Hermitian adjoint (or adjoint) operator on that space according to the rule. where is the inner product on the vector space. The adjoint may also be called the Hermitian conjugate or simply the Hermitian[1] after Charles ...

  6. Matrix decomposition - Wikipedia

    en.wikipedia.org/wiki/Matrix_decomposition

    Matrix decomposition. In the mathematical discipline of linear algebra, a matrix decomposition or matrix factorization is a factorization of a matrix into a product of matrices. There are many different matrix decompositions; each finds use among a particular class of problems.

  7. Schur decomposition - Wikipedia

    en.wikipedia.org/wiki/Schur_decomposition

    Schur decomposition. In the mathematical discipline of linear algebra, the Schur decomposition or Schur triangulation, named after Issai Schur, is a matrix decomposition. It allows one to write an arbitrary complex square matrix as unitarily similar to an upper triangular matrix whose diagonal elements are the eigenvalues of the original matrix.

  8. Quantum logic gate - Wikipedia

    en.wikipedia.org/wiki/Quantum_logic_gate

    A gate that acts on qubits is represented by a unitary matrix, and the set of all such gates with the group operation of matrix multiplication [a] is the unitary group U(2 n). [2] The quantum states that the gates act upon are unit vectors in 2 n {\displaystyle 2^{n}} complex dimensions, with the complex Euclidean norm (the 2-norm ).

  9. Adjoint representation - Wikipedia

    en.wikipedia.org/wiki/Adjoint_representation

    t. e. In mathematics, the adjoint representation (or adjoint action) of a Lie group G is a way of representing the elements of the group as linear transformations of the group's Lie algebra, considered as a vector space. For example, if G is , the Lie group of real n -by- n invertible matrices, then the adjoint representation is the group ...