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  2. Matrix addition - Wikipedia

    en.wikipedia.org/wiki/Matrix_addition

    The Kronecker sum is different from the direct sum, but is also denoted by ⊕. It is defined using the Kronecker product ⊗ and normal matrix addition. If A is n -by- n , B is m -by- m and I k {\displaystyle \mathbf {I} _{k}} denotes the k -by- k identity matrix then the Kronecker sum is defined by:

  3. Kronecker product - Wikipedia

    en.wikipedia.org/wiki/Kronecker_product

    In mathematics, the Kronecker product, sometimes denoted by ⊗, is an operation on two matrices of arbitrary size resulting in a block matrix.It is a specialization of the tensor product (which is denoted by the same symbol) from vectors to matrices and gives the matrix of the tensor product linear map with respect to a standard choice of basis.

  4. Kronecker sum of discrete Laplacians - Wikipedia

    en.wikipedia.org/wiki/Kronecker_sum_of_discrete...

    Based on this, eigenvalues and eigenvectors of the Kronecker sum can also be explicitly calculated. The eigenvalues and eigenvectors of the standard central difference approximation of the second derivative on an interval for traditional combinations of boundary conditions at the interval end points are well known .

  5. Kronecker delta - Wikipedia

    en.wikipedia.org/wiki/Kronecker_delta

    The map , representing scalar multiplication as a sum of outer products. The generalized Kronecker delta or multi-index Kronecker delta of order 2 p {\displaystyle 2p} is a type ( p , p ) {\displaystyle (p,p)} tensor that is completely antisymmetric in its p {\displaystyle p} upper indices, and also in its p {\displaystyle p} lower indices.

  6. Tensor product of representations - Wikipedia

    en.wikipedia.org/wiki/Tensor_product_of...

    The motivation for the use of the Kronecker sum in this definition comes from the case in which and come from representations and of a Lie group. In that case, a simple computation shows that the Lie algebra representation associated to Π 1 ⊗ Π 2 {\displaystyle \Pi _{1}\otimes \Pi _{2}} is given by the preceding formula.

  7. Separation of variables - Wikipedia

    en.wikipedia.org/wiki/Separation_of_variables

    The matrix form of the separation of variables is the Kronecker sum. As an example we consider the 2D discrete Laplacian on a regular grid : L = D x x ⊕ D y y = D x x ⊗ I + I ⊗ D y y , {\displaystyle L=\mathbf {D_{xx}} \oplus \mathbf {D_{yy}} =\mathbf {D_{xx}} \otimes \mathbf {I} +\mathbf {I} \otimes \mathbf {D_{yy}} ,\,}

  8. Kronecker coefficient - Wikipedia

    en.wikipedia.org/wiki/Kronecker_coefficient

    In mathematics, Kronecker coefficients g λ μν describe the decomposition of the tensor product (= Kronecker product) of two irreducible representations of a symmetric group into irreducible representations. They play an important role algebraic combinatorics and geometric complexity theory.

  9. Cartesian product of graphs - Wikipedia

    en.wikipedia.org/wiki/Cartesian_product_of_graphs

    where denotes the Kronecker product of matrices and denotes the identity matrix. [7] The adjacency matrix of the Cartesian graph product is therefore the Kronecker sum of the adjacency matrices of the factors.