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  2. Truncation error (numerical integration) - Wikipedia

    en.wikipedia.org/wiki/Truncation_error...

    The relation between local and global truncation errors is slightly different from in the simpler setting of one-step methods. For linear multistep methods, an additional concept called zero-stability is needed to explain the relation between local and global truncation errors.

  3. Backward Euler method - Wikipedia

    en.wikipedia.org/wiki/Backward_Euler_method

    In general, a method with (+) LTE (local truncation error) is said to be of kth order. The region of absolute stability for the backward Euler method is the complement in the complex plane of the disk with radius 1 centered at 1, depicted in the figure. [ 4 ]

  4. Truncation error - Wikipedia

    en.wikipedia.org/wiki/Truncation_error

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  5. Numerical methods for ordinary differential equations - Wikipedia

    en.wikipedia.org/wiki/Numerical_methods_for...

    The step size is =. The same illustration for = The midpoint method converges faster than the Euler method, as .. Numerical methods for ordinary differential equations are methods used to find numerical approximations to the solutions of ordinary differential equations (ODEs).

  6. Euler method - Wikipedia

    en.wikipedia.org/wiki/Euler_method

    When given the values for and (), and the derivative of is a given function of and denoted as ′ = (, ()).Begin the process by setting = ().Next, choose a value for the size of every step along t-axis, and set = + (or equivalently + = +).

  7. Adaptive step size - Wikipedia

    en.wikipedia.org/wiki/Adaptive_step_size

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  8. Verlet integration - Wikipedia

    en.wikipedia.org/wiki/Verlet_integration

    Verlet integration (French pronunciation:) is a numerical method used to integrate Newton's equations of motion. [1] It is frequently used to calculate trajectories of particles in molecular dynamics simulations and computer graphics.

  9. Runge–Kutta methods - Wikipedia

    en.wikipedia.org/wiki/Runge–Kutta_methods

    In numerical analysis, the Runge–Kutta methods (English: / ˈ r ʊ ŋ ə ˈ k ʊ t ɑː / ⓘ RUUNG-ə-KUUT-tah [1]) are a family of implicit and explicit iterative methods, which include the Euler method, used in temporal discretization for the approximate solutions of simultaneous nonlinear equations. [2]