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  2. Prism correction - Wikipedia

    en.wikipedia.org/wiki/Prism_correction

    Prism dioptres. Prism correction is commonly specified in prism dioptres, a unit of angular measurement that is loosely related to the dioptre. Prism dioptres are represented by the Greek symbol delta (Δ) in superscript. A prism of power 1 Δ would produce 1 unit of displacement for an object held 100 units from the prism. [2]

  3. Predictor–corrector method - Wikipedia

    en.wikipedia.org/wiki/Predictor–corrector_method

    A simple predictor–corrector method (known as Heun's method) can be constructed from the Euler method (an explicit method) and the trapezoidal rule (an implicit method). Consider the differential equation. and denote the step size by . First, the predictor step: starting from the current value , calculate an initial guess value via the Euler ...

  4. MacCormack method - Wikipedia

    en.wikipedia.org/wiki/MacCormack_method

    MacCormack method. In computational fluid dynamics, the MacCormack method (/məˈkɔːrmæk ˈmɛθəd/) is a widely used discretization scheme for the numerical solution of hyperbolic partial differential equations. This second-order finite difference method was introduced by Robert W. MacCormack in 1969. [1] The MacCormack method is elegant ...

  5. Woodbury matrix identity - Wikipedia

    en.wikipedia.org/wiki/Woodbury_matrix_identity

    The Woodbury matrix identity is [5] where A, U, C and V are conformable matrices: A is n × n, C is k × k, U is n × k, and V is k × n. This can be derived using blockwise matrix inversion . While the identity is primarily used on matrices, it holds in a general ring or in an Ab-category . The Woodbury matrix identity allows cheap computation ...

  6. Quasi-Newton method - Wikipedia

    en.wikipedia.org/wiki/Quasi-Newton_method

    Quasi-Newton methods are methods used to find either zeroes or local maxima and minima of functions, as an alternative to Newton's method. They can be used if the Jacobian or Hessian is unavailable or is too expensive to compute at every iteration. The "full" Newton's method requires the Jacobian in order to search for zeros, or the Hessian for ...

  7. Sherman–Morrison formula - Wikipedia

    en.wikipedia.org/wiki/Sherman–Morrison_formula

    One uses the Sherman–Morrison formula to calculate the inverse (satisfying certain time-ordering boundary conditions) of the inverse propagator—or simply the (Feynman) propagator—which is needed to perform any perturbative calculation [9] involving the spin-1 field. One of the issues with the formula is that little is known about its ...

  8. Maddox rod - Wikipedia

    en.wikipedia.org/wiki/Maddox_rod

    The strength of the prism is increased until the streak of the light passes through the centre of the prism, as the strength of the prism indicates the amount of deviation present. The Maddox rod is a handheld instrument composed of red parallel plano convex cylinder lens , which refracts light rays so that a point source of light is seen as a ...

  9. Newton's method - Wikipedia

    en.wikipedia.org/wiki/Newton's_method

    Use of Newton's method to compute square roots. Newton's method is one of many known methods of computing square roots. Given a positive number a, the problem of finding a number x such that x2 = a is equivalent to finding a root of the function f(x) = x2 − a. The Newton iteration defined by this function is given by.

  10. Levenberg–Marquardt algorithm - Wikipedia

    en.wikipedia.org/wiki/Levenberg–Marquardt...

    In mathematics and computing, the Levenberg–Marquardt algorithm ( LMA or just LM ), also known as the damped least-squares ( DLS) method, is used to solve non-linear least squares problems. These minimization problems arise especially in least squares curve fitting. The LMA interpolates between the Gauss–Newton algorithm (GNA) and the ...

  11. Cholesky decomposition - Wikipedia

    en.wikipedia.org/wiki/Cholesky_decomposition

    In linear algebra, the Cholesky decomposition or Cholesky factorization (pronounced / ʃəˈlɛski / shə-LES-kee) is a decomposition of a Hermitian, positive-definite matrix into the product of a lower triangular matrix and its conjugate transpose, which is useful for efficient numerical solutions, e.g., Monte Carlo simulations.