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  2. 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.

  3. Tensor product of graphs - Wikipedia

    en.wikipedia.org/wiki/Tensor_product_of_graphs

    The adjacency matrix of G × H is the Kronecker (tensor) product of the adjacency matrices of G and H. If a graph can be represented as a tensor product, then there may be multiple different representations (tensor products do not satisfy unique factorization) but each representation has the same number of irreducible factors.

  4. Outer product - Wikipedia

    en.wikipedia.org/wiki/Outer_product

    The outer product of tensors is also referred to as their tensor product, and can be used to define the tensor algebra. The outer product contrasts with: The dot product (a special case of "inner product"), which takes a pair of coordinate vectors as input and produces a scalar; The Kronecker product, which takes a pair of matrices as input and ...

  5. 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.

  6. Vectorization (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Vectorization_(mathematics)

    Multiplication of X by e i extracts the i-th column, while multiplication by B i puts it into the desired position in the final vector. Alternatively, the linear sum can be expressed using the Kronecker product : vec ⁡ ( X ) = ∑ i = 1 n e i ⊗ X e i {\displaystyle \operatorname {vec} (\mathbf {X} )=\sum _{i=1}^{n}\mathbf {e} _{i}\otimes ...

  7. Tensor product - Wikipedia

    en.wikipedia.org/wiki/Tensor_product

    The tensor product of two vector spaces is a vector space that is defined up to an isomorphism.There are several equivalent ways to define it. Most consist of defining explicitly a vector space that is called a tensor product, and, generally, the equivalence proof results almost immediately from the basic properties of the vector spaces that are so defined.

  8. Kronecker delta - Wikipedia

    en.wikipedia.org/wiki/Kronecker_delta

    The generalized Kronecker delta or multi-index Kronecker delta of order is a type (,) tensor that is completely antisymmetric in its upper indices, and also in its lower indices. Two definitions that differ by a factor of p ! {\displaystyle p!} are in use.

  9. Cartesian tensor - Wikipedia

    en.wikipedia.org/wiki/Cartesian_tensor

    A dyadic tensor T is an order-2 tensor formed by the tensor product ⊗ of two Cartesian vectors a and b, written T = a ⊗ b.Analogous to vectors, it can be written as a linear combination of the tensor basis e x ⊗ e x ≡ e xx, e x ⊗ e y ≡ e xy, ..., e z ⊗ e z ≡ e zz (the right-hand side of each identity is only an abbreviation, nothing more):