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  2. Rank–nullity theorem - Wikipedia

    en.wikipedia.org/wiki/Ranknullity_theorem

    Ranknullity theorem. The ranknullity theorem is a theorem in linear algebra, which asserts: the number of columns of a matrix M is the sum of the rank of M and the nullity of M; and; the dimension of the domain of a linear transformation f is the sum of the rank of f (the dimension of the image of f) and the nullity of f (the dimension of ...

  3. Rank (graph theory) - Wikipedia

    en.wikipedia.org/wiki/Rank_(graph_theory)

    Equivalently, the rank of a graph is the rank of the oriented incidence matrix associated with the graph. [2] Analogously, the nullity of the graph is the nullity of its oriented incidence matrix, given by the formula m − n + c, where n and c are as above and m is the number of edges in the graph. The nullity is equal to the first Betti ...

  4. Circuit rank - Wikipedia

    en.wikipedia.org/wiki/Circuit_rank

    The circuit rank of a hypergraph can be derived by its Levi graph, with the same circuit rank but reduced to a simple graph. = (+) + where g is the degree sum, e is the number of edges in the given graph, v is the number of vertices, and c is the number of connected components.

  5. Nullity (graph theory) - Wikipedia

    en.wikipedia.org/wiki/Nullity_(graph_theory)

    The nullity of M is given by m − n + c, where, c is the number of components of the graph and n − c is the rank of the oriented incidence matrix. This name is rarely used; the number is more commonly known as the cycle rank, cyclomatic number, or circuit rank of the graph. It is equal to the rank of the cographic matroid of the graph.

  6. Kernel (linear algebra) - Wikipedia

    en.wikipedia.org/wiki/Kernel_(linear_algebra)

    In the case where V is finite-dimensional, this implies the ranknullity theorem: ⁡ (⁡) + ⁡ (⁡) = ⁡ (). where the term rank refers to the dimension of the image of L, ⁡ (⁡), while nullity refers to the dimension of the kernel of L, ⁡ (⁡). [4] That is, ⁡ = ⁡ (⁡) ⁡ = ⁡ (⁡), so that the ranknullity theorem can be ...

  7. Schmidt decomposition - Wikipedia

    en.wikipedia.org/wiki/Schmidt_decomposition

    Consider a vector of the tensor product . in the form of Schmidt decomposition = =. Form the rank 1 matrix =.Then the partial trace of , with respect to either system A or B, is a diagonal matrix whose non-zero diagonal elements are | |.

  8. Rank (differential topology) - Wikipedia

    en.wikipedia.org/wiki/Rank_(differential_topology)

    Constant rank maps have a number of nice properties and are an important concept in differential topology. Three special cases of constant rank maps occur. A constant rank map f : M → N is an immersion if rank f = dim M (i.e. the derivative is everywhere injective), a submersion if rank f = dim N (i.e. the derivative is everywhere surjective),

  9. File:Rank-nullity.svg - Wikipedia

    en.wikipedia.org/wiki/File:Rank-nullity.svg

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