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Domain decomposition methods

In mathematics, numerical analysis, and numerical partial differential equations, domain decomposition methods solve a boundary value problem by splitting it into smaller boundary value problems on subdomains and iterating to coordinate the solution between adjacent subdomains. A coarse problem with one or few unknowns per subdomain is used to further coordinate the solution between the subdomains globally. The problems on the subdomains are independent, which makes domain decomposition methods suitable for parallel computing. Domain decomposition methods are typically used as preconditioners for Krylov space iterative methods, such as the conjugate gradient method, GMRES, and LOBPCG.

Example 1: 1D Linear BVP
\begin{cases} u''(x) = u(x), \\ u(0) = 0, \\ u(1) = 1. \end{cases} The exact solution is: u(x)=\frac{e^x-e^{-x}}{e^{1}-e^{-1}} Subdivide the domain into two subdomains, one from \left[0,\tfrac{1}{2}\right] and another from \left[\tfrac{1}{2},1\right]. In the left subdomain define the interpolating function v_1(x) and in the right define v_2 (x) . At the interface between these two subdomains the following interface conditions shall be imposed: \begin{align} v_1{\left(\frac{1}{2}\right)} &= v_2{\left(\frac{1}{2}\right)} \\ v_1'{\left(\frac{1}{2}\right)} &= v_2'{\left(\frac{1}{2}\right)} \end{align} Let the interpolating functions be defined as: \begin{align} v_1(x) &= \sum_{n=0}^{N} u_{n} T_n (y_1(x)) \\ v_2(x) &= \sum_{n=0}^{N} u_{n+N} T_n (y_2(x)) \\ y_1(x) &= 4x-1 \\ y_2(x) &= 4x-3 \end{align} Where T_n (y) is the nth cardinal function of the Chebyshev polynomials of the first kind with input argument y. If N=4 then the following approximation is obtained by this scheme: \begin{align} u_1 &= 0.06236, & u_2 &= 0.21495, \\ u_3 &= 0.37428, & u_4 &= 0.44341, \\ u_5 &= 0.51492, & u_6 &= 0.69972, \\ u_7 &= 0.90645. \end{align} This was obtained with the following MATLAB code. clear all N = 4; a1 = 0; b1 = 1/2; [T D1 D2 E1 E2 x xsub] = cheb(N,a1,b1); % the diff matrices on [0,1/2] are the same %as those on [1/2 1]. I = eye(N+1); H = D2-I; H1 = 1 zeros(1,N)]; H(2:end-1,:); [zeros(1,N) 1; H1 = [H1 [zeros(N,N+1); -[1 zeros(1,N)]; H2 = [D1(1,:); H(2:end-1,:); [zeros(1,N) 1; H2 = -D1(N+1,:); zeros(N,N+1)] H2]; K = [H1; H2]; F = [zeros(2*N+1,1); 1]; u = K\F; xx = -cos(pi*(0:N)'/N); x1 = 1/4*(xx+1); x2 = 1/4*(xx+3); x = [x1; x2]; uex = (exp(x)-exp(-x))./(exp(1)-exp(-1)); ==See also==
Related Books
• Barry Smith, Petter Bjørstad, and William Gropp: Domain Decomposition: Parallel Multilevel Methods for Elliptic Partial Differential Equations, Cambridge Univ. Press, ISBN 0-521-49589-X (1996). == External links ==
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