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  2. Jacobian matrix and determinant - Wikipedia

    en.wikipedia.org/wiki/Jacobian_matrix_and...

    In vector calculus, the Jacobian matrix (/ dʒ ə ˈ k oʊ b i ə n /, [1] [2] [3] / dʒ ɪ-, j ɪ-/) of a vector-valued function of several variables is the matrix of all its first-order partial derivatives.

  3. Broyden's method - Wikipedia

    en.wikipedia.org/wiki/Broyden's_method

    Newton's method for solving f(x) = 0 uses the Jacobian matrix, J, at every iteration. However, computing this Jacobian can be a difficult and expensive operation; for large problems such as those involving solving the Kohn–Sham equations in quantum mechanics the number of variables can be in the hundreds of thousands.

  4. Jacobian conjecture - Wikipedia

    en.wikipedia.org/wiki/Jacobian_conjecture

    The polynomial xx p has derivative 1 − p x p−1 which is 1 (because px is 0) but it has no inverse function. However, Kossivi Adjamagbo suggested extending the Jacobian conjecture to characteristic p > 0 by adding the hypothesis that p does not divide the degree of the field extension k(X) / k(F). [3]

  5. Quasi-Newton method - Wikipedia

    en.wikipedia.org/wiki/Quasi-Newton_method

    The main difference is that the Hessian matrix is a symmetric matrix, unlike the Jacobian when searching for zeroes. Most quasi-Newton methods used in optimization exploit this symmetry. In optimization, quasi-Newton methods (a special case of variable-metric methods) are algorithms for finding local maxima and minima of functions.

  6. Numerical continuation - Wikipedia

    en.wikipedia.org/wiki/Numerical_continuation

    The same terminology applies. A regular solution is a solution at which the Jacobian is full rank (). A singular solution is a solution at which the Jacobian is less than full rank. A regular solution lies on a k-dimensional surface, which can be parameterized by a point in the tangent space (the null space of the Jacobian).

  7. Inverse function theorem - Wikipedia

    en.wikipedia.org/wiki/Inverse_function_theorem

    For functions of more than one variable, the theorem states that if is a continuously differentiable function from an open subset of into , and the derivative ′ is invertible at a point a (that is, the determinant of the Jacobian matrix of f at a is non-zero), then there exist neighborhoods of in and of = such that () and : is bijective. [1]

  8. Jacobian variety - Wikipedia

    en.wikipedia.org/wiki/Jacobian_variety

    In mathematics, the Jacobian variety J(C) of a non-singular algebraic curve C of genus g is the moduli space of degree 0 line bundles. It is the connected component of the identity in the Picard group of C , hence an abelian variety .

  9. Generalized Jacobian - Wikipedia

    en.wikipedia.org/wiki/Generalized_Jacobian

    For m = 0 the generalized Jacobian J m is just the usual Jacobian J, an abelian variety of dimension g, the genus of C. For m a nonzero effective divisor the generalized Jacobian is an extension of J by a connected commutative affine algebraic group L m of dimension deg(m)−1. So we have an exact sequence 0 → L m → J m → J → 0. The ...

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