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  2. Jacobian matrix and determinant - Wikipedia

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

    The Jacobian at a point gives the best linear approximation of the distorted parallelogram near that point (right, in translucent white), and the Jacobian determinant gives the ratio of the area of the approximating parallelogram to that of the original square. If m = n, then f is a function from R n to itself and the Jacobian matrix is a ...

  3. Determinant - Wikipedia

    en.wikipedia.org/wiki/Determinant

    The determinant of an n × n matrix can be defined in several equivalent ways, the most common being Leibniz formula, which expresses the determinant as a sum of ! (the factorial of n) signed products of matrix entries.

  4. Jacobi sum - Wikipedia

    en.wikipedia.org/wiki/Jacobi_sum

    Jacobi sums are the analogues for finite fields of the beta function. Such sums were introduced by C. G. J. Jacobi early in the nineteenth century in connection with the theory of cyclotomy. Jacobi sums J can be factored generically into products of powers of Gauss sums g. For example, when the character χψ is nontrivial,

  5. Jacobi's formula - Wikipedia

    en.wikipedia.org/wiki/Jacobi's_formula

    In matrix calculus, Jacobi's formula expresses the derivative of the determinant of a matrix A in terms of the adjugate of A and the derivative of A. [ 1 ] If A is a differentiable map from the real numbers to n × n matrices, then

  6. Jacobi polynomials - Wikipedia

    en.wikipedia.org/wiki/Jacobi_polynomials

    Plot of the Jacobi polynomial function (,) with = and = and = in the complex plane from to + with colors created with Mathematica 13.1 function ComplexPlot3D In mathematics , Jacobi polynomials (occasionally called hypergeometric polynomials ) P n ( α , β ) ( x ) {\displaystyle P_{n}^{(\alpha ,\beta )}(x)} are a class of classical orthogonal ...

  7. Hessian matrix - Wikipedia

    en.wikipedia.org/wiki/Hessian_matrix

    In two variables, the determinant can be used, because the determinant is the product of the eigenvalues. If it is positive, then the eigenvalues are both positive, or both negative. If it is negative, then the two eigenvalues have different signs. If it is zero, then the second-derivative test is inconclusive.

  8. Matrix calculus - Wikipedia

    en.wikipedia.org/wiki/Matrix_calculus

    In mathematics, matrix calculus is a specialized notation for doing multivariable calculus, especially over spaces of matrices.It collects the various partial derivatives of a single function with respect to many variables, and/or of a multivariate function with respect to a single variable, into vectors and matrices that can be treated as single entities.

  9. Jacobian conjecture - Wikipedia

    en.wikipedia.org/wiki/Jacobian_conjecture

    The Jacobian conjecture is the following partial converse: Jacobian conjecture: Let k have characteristic 0. If J F is a non-zero constant, then F has an inverse function G: k N → k N which is regular, meaning its components are polynomials.