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  2. Numerical stability - Wikipedia

    en.wikipedia.org/wiki/Numerical_stability

    Stability is sometimes achieved by including numerical diffusion. Numerical diffusion is a mathematical term which ensures that roundoff and other errors in the calculation get spread out and do not add up to cause the calculation to "blow up". Von Neumann stability analysis is a commonly used procedure for the stability analysis of finite ...

  3. Lanczos algorithm - Wikipedia

    en.wikipedia.org/wiki/Lanczos_algorithm

    Numerical stability is the central criterion for judging the usefulness of implementing an algorithm on a computer with roundoff. For the Lanczos algorithm, it can be proved that with exact arithmetic , the set of vectors v 1 , v 2 , ⋯ , v m + 1 {\displaystyle v_{1},v_{2},\cdots ,v_{m+1}} constructs an orthonormal basis, and the eigenvalues ...

  4. Von Neumann stability analysis - Wikipedia

    en.wikipedia.org/wiki/Von_Neumann_stability_analysis

    The stability of numerical schemes can be investigated by performing von Neumann stability analysis. For time-dependent problems, stability guarantees that the numerical method produces a bounded solution whenever the solution of the exact differential equation is bounded.

  5. Floating-point arithmetic - Wikipedia

    en.wikipedia.org/wiki/Floating-point_arithmetic

    Stability is a measure of the sensitivity to rounding errors of a given numerical procedure; by contrast, the condition number of a function for a given problem indicates the inherent sensitivity of the function to small perturbations in its input and is independent of the implementation used to solve the problem. [53]

  6. Eigenvalue algorithm - Wikipedia

    en.wikipedia.org/wiki/Eigenvalue_algorithm

    Given an n × n square matrix A of real or complex numbers, an eigenvalue λ and its associated generalized eigenvector v are a pair obeying the relation [1] =,where v is a nonzero n × 1 column vector, I is the n × n identity matrix, k is a positive integer, and both λ and v are allowed to be complex even when A is real.l When k = 1, the vector is called simply an eigenvector, and the pair ...

  7. Explicit and implicit methods - Wikipedia

    en.wikipedia.org/wiki/Explicit_and_implicit_methods

    In the vast majority of cases, the equation to be solved when using an implicit scheme is much more complicated than a quadratic equation, and no analytical solution exists. Then one uses root-finding algorithms, such as Newton's method, to find the numerical solution. Crank-Nicolson method. With the Crank-Nicolson method

  8. T-matrix method - Wikipedia

    en.wikipedia.org/wiki/T-matrix_method

    This approach avoids numerical stability issues associated with the null-field method. [8] Several numerical codes for the evaluation of the T-matrix can be found online . The T matrix can be found with methods other than null field method and extended boundary condition method (EBCM); therefore, the term "T-matrix method" is infelicitous.

  9. Moving particle semi-implicit method - Wikipedia

    en.wikipedia.org/wiki/Moving_particle_semi...

    K. Shibata and S. Koshizuka, "Numerical analysis of shipping water impact on a deck using a particle method," Ocean Engineering, Vol 34, pp. 585–593, 2007. Y. Suzuki, S. Koshizuka, Y. Oka, "Hamiltonian moving-particle semi-implicit (HMPS) method for incompressible fluid flows," Computer Methods in Applied Mechanics and Engineering, Vol 196 ...