Computational science, also known as scientific computing, technical computing or scientific computation, is a division of science, and more specifically of the computer sciences, that uses advanced computing capability to understand and solve complex physical problems. The field spans algorithms, meaning the mathematical models, computational models and computer simulations developed to solve problems in science, engineering and the humanities; computer hardware that develops and optimizes the advanced system hardware, firmware, networking and data management components needed for computationally demanding problems; and the computing infrastructure that supports both the science and engineering problem solving and the underlying computer and information science. This description is adapted from Wikipedia contributors under CC BY-SA 4.0; changes were made. https://creativecommons.org/licenses/by-sa/4.0/
Facts
Core ConcernUsing advanced computing capability to understand and solve complex physical science problems 1 Connections
Associated With
Field-to-field association; both are standard neighbouring areas of computing
Source Wikipedia: Computational science
Computer Algebra, Fields Field-to-field association; both are standard neighbouring areas of computing
Data Science, Fields Field-to-field association; both are standard neighbouring areas of computing
Field-to-field association; both are standard neighbouring areas of computing
Source Wikipedia: Computational science
Includes
Source Secant method (Wikipedia)
Source SIMPLE algorithm (Wikipedia)
Source Simpson's Rule (Wikipedia)
Source Stanislaw Ulam (MacTutor biography)
Source Steffensen's method (Wikipedia)
Source Upwind scheme (Wikipedia)
Source Walter Edwin Arnoldi (source article)
Source Welch's method (Wikipedia)
Source Wikipedia: William Kahan
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1. Wikipedia: Computational science
Wikimedia FoundationLead section, para 1
Computational science, also known as scientific computing, technical computing or scientific computation (SC), is a division of science, and more specifically the computer sciences, which uses advanced computing capabilities to understand and solve complex physical problems in science.
Associated With: Parallel Computing, Methods and algorithms
In addition, parallel computing is heavily used in scientific computing to find solutions of large problems in a reasonable amount of time.
Associated With: Bioinformatics, Computational biology
Going beyond current bioinformatics approaches, computational biology needs to develop new methods to discover meaningful patterns in these large data sets.
- In Group: Computing for the Sciences and Engineering, lead section
View the Source IEEE Computer Society History Committee: Computer Pioneers: James (Jim) Hardy Wilkinson
IEEE Computer Society History CommitteeIncludes: James H. Wilkinson, Biography headerQuote, Includes: James H. Wilkinson, Biography header
numerical analyst, developer of the so-called "backward" error analysis
View the Source Wikipedia: Alston Scott Householder
Wikimedia FoundationIncludes: Alston Scott Householder, Lead sectionQuote, Includes: Alston Scott Householder, Lead section
specialized in mathematical biology and numerical analysis
View the Source Cleve Moler, Wikipedia
Includes: Cleve Moler, Lead sectionQuote, Includes: Cleve Moler, Lead section
specialized in numerical analysis
View the Source Wikipedia: William Kahan
Wikimedia FoundationIncludes: William Kahan, LeadQuote, Includes: William Kahan, Lead
He received the Turing Award in 1989 for "his fundamental contributions to numerical analysis."
View the Source James Demmel - Wikipedia
Includes: James Demmel, LeadQuote, Includes: James Demmel, Lead
In 1999, Demmel was elected a member of the National Academy of Engineering for contributions to numerical linear algebra and scientific computing.
View the Source Wikipedia: Amber S. Boehnlein
Wikimedia FoundationIncludes: Amber S. Boehnlein, Infobox: known_forQuote, Includes: Amber S. Boehnlein, Infobox: known_for
Computational Physics
View the Source RANDU (Wikipedia)
Includes: RANDU, LeadQuote, Includes: RANDU, Lead
RANDU is an obsolete method for generating random numbers used primarily in the 1960s and 1970s.
View the Source Crank-Nicolson method (Wikipedia)
Includes: Crank-Nicolson method, Lead sectionQuote, Includes: Crank-Nicolson method, Lead section
the Crank-Nicolson method is a finite difference method used for numerically solving the heat equation and similar partial differential equations.
View the Source Dormand-Prince method (Wikipedia)
Includes: Dormand-Prince method, Lead
is an embedded method for solving ordinary differential equations (ODE).
Includes: John R. Dormand, Lead
Dormand and Prince chose the coefficients of their method to minimize the error of the fifth-order solution.
Includes: P. J. Prince, Lead
Dormand and Prince chose the coefficients of their method to minimize the error of the fifth-order solution.
View the SourceArnoldi iteration (source article)
Includes: Arnoldi iteration, LeadQuote, Includes: Arnoldi iteration, Lead
In numerical linear algebra, the Arnoldi iteration is an eigenvalue algorithm and an important example of an iterative method.
View the Source Walter Edwin Arnoldi (source article)
Includes: Walter Edwin Arnoldi, LeadQuote, Includes: Walter Edwin Arnoldi, Lead
an eigenvalue algorithm used in numerical linear algebra
View the Source Monte Carlo method (source article)
Includes: Monte Carlo method, LeadQuote, Includes: Monte Carlo method, Lead
are a broad class of computational algorithms based on repeated random sampling
View the Source Stanislaw Ulam (MacTutor biography)
Includes: Stanisław Ulam, Biography, Los AlamosQuote, Includes: Stanisław Ulam, Biography, Los Alamos
He also devised the Monte-Carlo method widely used in solving mathematical problems using statistical sampling.
View the Source About GNU Octave (project page)
Includes: GNU Octave, About, opening paragraphQuote, Includes: GNU Octave, About, opening paragraph
primarily intended for numerical computations
View the Source Carl Runge (MacTutor)
Includes: Carl Runge, SummaryQuote, Includes: Carl Runge, Summary
Carl Runge worked on a procedure for the numerical solution of algebraic equations
View the Source Welch's method (Wikipedia)
Includes: Welch's method, Lead section [in-field]Quote, Includes: Welch's method, Lead section [in-field]
It is used in physics, engineering, and applied mathematics for estimating the power of a signal at different frequencies.
View the Source Steffensen's method (Wikipedia)
Includes: Steffensen's method, Lead sectionQuote, Includes: Steffensen's method, Lead section
an iterative method named after Johan Frederik Steffensen for numerical root-finding
View the Source Householder's method (Wikipedia)
Includes: Householder's method, Lead [in-field]Quote, Includes: Householder's method, Lead [in-field]
In mathematics, and more specifically in numerical analysis, Householder's methods are a class of root-finding algorithms
View the Source Iterative proportional fitting (Wikipedia)
Includes: Iterative proportional fitting, LeadQuote, Includes: Iterative proportional fitting, Lead
is the operation of finding the fitted matrix
View the Source Upwind scheme (Wikipedia)
Includes: Upwind scheme, LeadQuote, Includes: Upwind scheme, Lead
In computational physics, the term advection scheme refers to a class of numerical discretization methods for solving hyperbolic partial differential equations.
View the Source Beeman's algorithm (Wikipedia)
Includes: Beeman's algorithm, Lead paragraph [in-field]Quote, Includes: Beeman's algorithm, Lead paragraph [in-field]
It was designed to allow high numbers of particles in simulations of molecular dynamics
View the Source Durand-Kerner method (Wikipedia)
Includes: Durand-Kerner method, Lead paragraph [in-field]Quote, Includes: Durand-Kerner method, Lead paragraph [in-field]
In numerical analysis, the Weierstrass method or Durand-Kerner method
View the Source Laguerre's method (Wikipedia)
Includes: Laguerre's method, Lead paragraph [in-field]Quote, Includes: Laguerre's method, Lead paragraph [in-field]
In numerical analysis, Laguerre's method
View the Source Biconjugate gradient stabilized method (Wikipedia)
Includes: Biconjugate gradient stabilized method, Lead paragraph [in-field]Quote, Includes: Biconjugate gradient stabilized method, Lead paragraph [in-field]
In numerical linear algebra, the biconjugate gradient stabilized method
View the Source Cash-Karp method (Wikipedia)
Includes: Cash-Karp method, Lead paragraph [in-field]Quote, Includes: Cash-Karp method, Lead paragraph [in-field]
In numerical analysis, the Cash-Karp method
View the Source NA Digest, Volume 20, Issue 25: Jeff Cash announcement
Includes: Jeff R. Cash, NA Digest post, Jeff CashQuote, Includes: Jeff R. Cash, NA Digest post, Jeff Cash
Jeff's research has been mainly focused on the solution of difference and differential equations, with an emphasis on mathematical software.
View the Source Graeffe's method (Wikipedia)
Includes: Graeffe's method, Lead sectionQuote, Includes: Graeffe's method, Lead section
Graeffe's method or Dandelin-Lobachesky-Graeffe method is an algorithm for finding all of the roots of a polynomial.
View the Source Aitken's delta-squared process (Wikipedia)
Includes: Aitken's delta-squared process, Lead sectionQuote, Includes: Aitken's delta-squared process, Lead section
Aitken's delta-squared process or Aitken extrapolation is a series acceleration method used for accelerating the rate of convergence of a sequence.
View the Source Aberth method (Wikipedia)
Includes: Aberth method, Lead sectionQuote, Includes: Aberth method, Lead section
is a root-finding algorithm developed in 1967 for simultaneous approximation of all the roots of a univariate polynomial.
View the Source SIMPLE algorithm (Wikipedia)
Includes: SIMPLE algorithm, Lead sectionQuote, Includes: SIMPLE algorithm, Lead section
the SIMPLE algorithm is a widely used numerical procedure to solve the Navier-Stokes equations.
View the Source Wikipedia: LU decomposition
Includes: LU Decomposition Algorithm, Lead sentenceQuote, Includes: LU Decomposition Algorithm, Lead sentence
lower-upper (LU) decomposition or factorization factors a matrix as the product of a lower triangular matrix and an upper triangular matrix (see matrix multiplication and matrix decomposition).
View the Source Wikipedia: Runge-Kutta methods
Includes: Runge-Kutta Method Algorithm, Lead sectionQuote, Includes: Runge-Kutta Method Algorithm, Lead section
In numerical analysis, the Runge-Kutta methods (English: RUUNG-ə-KUUT-tah) are a family of explicit and implicit iterative methods, which include the Euler method, used in discretization for the approximate solutions of differential equations.
View the Source Wikipedia: Nelder-Mead method
Includes: Nelder-Mead Method Algorithm, Lead sentenceQuote, Includes: Nelder-Mead Method Algorithm, Lead sentence
Nelder-Mead method (also downhill simplex method, amoeba method, or polytope method) is a numerical method used to find a local minimum or maximum of an objective function in a multidimensional space.
View the Source QR algorithm (Wikipedia)
Includes: QR Algorithm, Lead sentenceQuote, Includes: QR Algorithm, Lead sentence
QR algorithm or QR iteration is an eigenvalue algorithm: that is, a procedure to calculate the eigenvalues and eigenvectors of a matrix.
View the Source Conjugate gradient method (Wikipedia)
Includes: Conjugate Gradient Method, Lead sentenceQuote, Includes: Conjugate Gradient Method, Lead sentence
conjugate gradient method is an algorithm for the numerical solution of particular systems of linear equations, namely those whose matrix is positive-semidefinite.
View the Source Jacobi Eigenvalue Algorithm (Wikipedia)
Includes: Jacobi Eigenvalue Algorithm, Lead sentenceQuote, Includes: Jacobi Eigenvalue Algorithm, Lead sentence
Jacobi eigenvalue algorithm is an iterative method for the calculation of the eigenvalues and eigenvectors of a real symmetric matrix (a process known as diagonalization).
View the Source Gauss-Seidel method (Wikipedia)
Includes: Gauss-Seidel Method, Lead sentenceQuote, Includes: Gauss-Seidel Method, Lead sentence
Gauss-Seidel method, also known as the Liebmann method or the method of successive displacement, is an iterative method used to solve a system of linear equations.
View the Source Brent's method (Wikipedia)
Includes: Brent's Method, Lead sentenceQuote, Includes: Brent's Method, Lead sentence
Brent's method is a hybrid root-finding algorithm combining the bisection method, the secant method and inverse quadratic interpolation.
View the Source Simpson's Rule (Wikipedia)
Includes: Simpson's Rule, Lead sentenceQuote, Includes: Simpson's Rule, Lead sentence
Simpson's rules are several approximations for definite integrals, named after Thomas Simpson (1710-1761).
View the Source Remez algorithm (Wikipedia)
Includes: Remez Algorithm, Lead sentenceQuote, Includes: Remez Algorithm, Lead sentence
Remez algorithm or Remez exchange algorithm, published by Evgeny Yakovlevich Remez in 1934, is an iterative algorithm used to find simple approximations to functions, specifically, approximations by functions in a Chebyshev space that are the best in the unifo
View the Source Bareiss algorithm (Wikipedia)
Includes: Bareiss Algorithm, Lead sentenceQuote, Includes: Bareiss Algorithm, Lead sentence
Bareiss algorithm, named after Erwin Bareiss, is an algorithm to calculate the determinant or the echelon form of a matrix with integer entries using only integer arithmetic; any divisions that are performed are guaranteed to be exact (there is no remainder).
View the Source Ellipsoid method (Wikipedia)
Includes: Ellipsoid Method, Lead sentenceQuote, Includes: Ellipsoid Method, Lead sentence
ellipsoid method is an iterative method for minimizing convex functions over convex sets.
View the Source Wikipedia: Newton-Raphson Method
Wikimedia FoundationIncludes: Newton-Raphson Method, LeadQuote, Includes: Newton-Raphson Method, Lead
In numerical analysis, the Newton-Raphson method, also known simply as Newton's method, named after Isaac Newton and Joseph Raphson, is a root-finding algorithm which produces successively better approximations to the roots (or zeroes) of a real-valued function.
View the Source Secant method (Wikipedia)
Includes: Secant Method Algorithm, LeadQuote, Includes: Secant Method Algorithm, Lead
In numerical analysis, the secant method is a root-finding algorithm that uses a succession of roots of secant lines to better approximate a root of a function f.
View the Source Broyden-Fletcher-Goldfarb-Shanno algorithm (Wikipedia)
Includes: BFGS Algorithm, LeadQuote, Includes: BFGS Algorithm, Lead
In numerical optimization, the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is an iterative method for solving unconstrained nonlinear optimization problems.
View the Source Broyden's method (Wikipedia)
Includes: Broyden's Method Algorithm, LeadQuote, Includes: Broyden's Method Algorithm, Lead
In numerical analysis, Broyden's method is a quasi-Newton method for finding roots in k variables.
View the Source Monte Carlo integration (Wikipedia)
Includes: Monte Carlo integration, LeadQuote, Includes: Monte Carlo integration, Lead
In mathematics, Monte Carlo integration is a technique for numerical integration using random numbers.
View the Source Euler method (Wikipedia)
Includes: Euler method, LeadQuote, Includes: Euler method, Lead
In mathematics and computational science, the Euler method (also called the forward Euler method) is a first-order numerical procedure for solving ordinary differential equations (ODEs) with a given initial value.
View the Source Jacobi method (Wikipedia)
Includes: Jacobi method, LeadQuote, Includes: Jacobi method, Lead
In numerical linear algebra, the Jacobi method (a.k.a. the Jacobi iteration method) is an iterative algorithm for determining the solutions of a strictly diagonally dominant system of linear equations.
View the Source Halley's method (Wikipedia)
Includes: Halley's method, LeadQuote, Includes: Halley's method, Lead
In numerical analysis, Halley's method is a root-finding algorithm used for functions of one real variable with a continuous second derivative.
View the Source Fixed-point iteration (Wikipedia)
Includes: Fixed-point iteration, LeadQuote, Includes: Fixed-point iteration, Lead
In numerical analysis, fixed-point iteration is a method of computing fixed points of a function.
View the Source Cuthill-McKee algorithm (Wikipedia)
Includes: Cuthill-McKee algorithm, LeadQuote, Includes: Cuthill-McKee algorithm, Lead
In numerical linear algebra, the Cuthill-McKee algorithm (CM), named after Elizabeth Cuthill and James McKee, is an algorithm to permute a sparse matrix that has a symmetric sparsity pattern into a band matrix form with a small bandwidth.
View the Source FTCS scheme (Wikipedia)
Includes: FTCS scheme, LeadQuote, Includes: FTCS scheme, Lead
In numerical analysis, the FTCS (forward time-centered space) method is a finite difference method used for numerically solving the heat equation and similar parabolic partial differential equations.
View the Source Backward Euler method (Wikipedia)
Includes: Backward Euler method, LeadQuote, Includes: Backward Euler method, Lead
In numerical analysis and scientific computing, the backward Euler method (or implicit Euler method) is one of the most basic numerical methods for the solution of ordinary differential equations.
View the Source Multigrid method (Wikipedia)
Includes: Multigrid method, LeadQuote, Includes: Multigrid method, Lead
In numerical analysis, a multigrid method (MG method) is an algorithm for solving differential equations using a hierarchy of discretizations.
View the Source Gauss-Legendre quadrature (Wikipedia)
Includes: Gauss-Legendre quadrature, LeadQuote, Includes: Gauss-Legendre quadrature, Lead
In numerical analysis, Gauss-Legendre quadrature is a form of Gaussian quadrature for approximating the definite integral of a function.
View the Source Runge-Kutta-Fehlberg method (Wikipedia)
Includes: Runge-Kutta-Fehlberg method, LeadQuote, Includes: Runge-Kutta-Fehlberg method, Lead
In mathematics, the Runge-Kutta-Fehlberg method (or Fehlberg method) is an algorithm in numerical analysis for the numerical solution of ordinary differential equations.
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