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| In [[mathematics]], in the area of [[numerical analysis]], '''Galerkin methods''' are a class of methods for converting a continuous operator problem (such as a [[differential equation]]) to a discrete problem. In principle, it is the equivalent of applying the method of [[variation of parameters]] to a function space, by converting the equation to a [[weak formulation]]. Typically one then applies some constraints on the function space to characterize the space with a finite set of basis functions. The approach is usually credited to the Russian mathematician [[Boris Galerkin]] but the method was discovered by the Swiss mathematician Walther Ritz,<ref>"Le destin douloureux de Walther Ritz (1878-1909)", (Jean-Claude Pont, editor), Cahiers de Vallesia, 24, (2012), ISBN 978-2-9700636-5-0</ref> to whom Galerkin refers. Often when referring to a Galerkin method, one also gives the name along with typical approximation methods used, such as [[Bubnov-Galerkin method]] (after [[Ivan Bubnov]]), [[Petrov–Galerkin method]] (after Georgii I. Petrov<ref name=Mikhlin>S. G. Mikhlin, "Variational methods in Mathematical Physics", Pergamon Press, 1964</ref><ref name="Birthday">"Georgii Ivanovich Petrov (on his 100th birthday)", Fluid Dynamics, May 2012, Volume 47, Issue 3, pp 289-291, DOI 10.1134/S0015462812030015</ref>) or [[Ritz–Galerkin method]]<ref name=ErnGuermond>A. Ern, J.L. Guermond, ''Theory and practice of finite elements'', Springer, 2004, ISBN 0-387-20574-8</ref> (after [[Walther Ritz]]).
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| Examples of calculating the global stiffness matrix in the [[finite element method]],<ref name=BrennerScott>S. Brenner, R. L. Scott, ''The Mathematical Theory of Finite Element Methods'', 2nd edition, Springer, 2005, ISBN 0-387-95451-1</ref><ref name=Ciarlet>P. G. Ciarlet, ''The Finite Element Method for Elliptic Problems'', North-Holland, 1978, ISBN 0-444-85028-7</ref>
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| * [[Boundary element method]] for solving integral equations
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| * [[Krylov subspace method]]s.<ref name=Saad>[[Yousef Saad|Y. Saad]], ''Iterative Methods for Sparse Linear Systems'', 2nd edition, SIAM, 2003, ISBN 0-89871-534-2</ref>
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| ==Introduction with an abstract problem==
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| ===A problem in weak formulation===
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| Let us introduce Galerkin's method with an abstract problem posed as a [[weak formulation]] on a [[Hilbert space]], <math>V</math>, namely,
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| : find <math>u\in V</math> such that for all <math>v\in V, a(u,v) = f(v)</math>.
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| Here, <math>a(\cdot,\cdot)</math> is a [[bilinear form]] (the exact requirements on <math>a(\cdot,\cdot)</math> will be specified later) and <math>f</math> is a bounded linear functional on <math>V</math>.
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| ===Galerkin Dimension Reduction===
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| Choose a subspace <math>V_n \subset V</math> of dimension ''n'' and solve the projected problem:
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| : Find <math>u_n\in V_n</math> such that for all <math>v_n\in V_n, a(u_n,v_n) = f(v_n)</math>.
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| We call this the '''Galerkin equation'''. Notice that the equation has remained unchanged and only the spaces have changed.
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| Reducing the problem to a finite dimensional vector subspace allows us to numerically compute <math> u_n </math> as a finite linear combination of the basis vectors in <math> V_n </math>.
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| ===Galerkin orthogonality===
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| The key property of the Galerkin approach is that the error is orthogonal to the chosen subspaces. Since <math>V_n \subset V</math>, we can use <math>v_n</math> as a test vector in the original equation. Subtracting the two, we get the Galerkin orthogonality relation for the error, <math>\epsilon_n = u-u_n</math> which is the error between the solution of the original problem, <math>u</math>, and the solution of the Galerkin equation, <math>u_n</math>
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| :<math> a(\epsilon_n, v_n) = a(u,v_n) - a(u_n, v_n) = f(v_n) - f(v_n) = 0.</math>
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| ===Matrix form===
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| Since the aim of Galerkin's method is the production of a [[system of linear equations|linear system of equations]], we build its matrix form, which can be used to compute the solution by a computer program.
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| Let <math>e_1, e_2,\ldots,e_n</math> be a [[basis (linear algebra)|basis]] for <math>V_n</math>. Then, it is sufficient to use these in turn for testing the Galerkin equation, i.e.: find <math>u_n \in V_n</math> such that
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| :<math>a(u_n, e_i) = f(e_i) \quad i=1,\ldots,n.</math>
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| We expand <math>u_n</math> with respect to this basis, <math>u_n = \sum_{j=1}^n u_je_j</math> and insert it into the equation above, to obtain
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| :<math>a\left(\sum_{j=1}^n u_je_j, e_i\right) = \sum_{j=1}^n u_j a(e_j, e_i) = f(e_i) \quad i=1,\ldots,n.</math>
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| This previous equation is actually a linear system of equations <math>Au=f</math>, where
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| :<math>A_{ij} = a(e_j, e_i), \quad f_i = f(e_i).</math>
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| ====Symmetry of the matrix====
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| Due to the definition of the matrix entries, the matrix of the Galerkin equation is [[symmetric matrix|symmetric]] if and only if the bilinear form <math>a(\cdot,\cdot)</math> is symmetric.
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| ==Analysis of Galerkin methods==
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| Here, we will restrict ourselves to symmetric [[bilinear form]]s, that is
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| :<math>a(u,v) = a(v,u).</math>
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| While this is not really a restriction of Galerkin methods, the application of the standard theory becomes much simpler. Furthermore, a [[Petrov–Galerkin method]] may be required in the nonsymmetric case.
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| The analysis of these methods proceeds in two steps. First, we will show that the Galerkin equation is a [[well-posed problem]] in the sense of [[Hadamard]] and therefore admits a unique solution. In the second step, we study the quality of approximation of the Galerkin solution <math>u_n</math>.
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| The analysis will mostly rest on two properties of the [[bilinear form]], namely
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| * Boundedness: for all <math>u,v\in V</math> holds
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| *:<math>a(u,v) \le C \|u\|\, \|v\|</math> for some constant <math>C>0</math>
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| * Ellipticity: for all <math>u\in V</math> holds
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| *:<math>a(u,u) \ge c \|u\|^2</math> for some constant <math>c>0.</math>
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| By the Lax-Milgram theorem (see [[weak formulation]]), these two conditions imply well-posedness of the original problem in weak formulation. All norms in the following sections will be norms for which the above inequalities hold (these norms are often called an energy norm).
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| ===Well-posedness of the Galerkin equation===
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| Since <math>V_n \subset V</math>, boundedness and ellipticity of the bilinear form apply to <math>V_n</math>. Therefore, the well-posedness of the Galerkin problem is actually inherited from the well-posedness of the original problem.
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| ===Quasi-best approximation (Céa's lemma)===
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| {{main|Céa's lemma}}
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| The error <math>u-u_n</math> between the original and the Galerkin solution admits the estimate
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| :<math>\|u-u_n\| \le \frac{C}{c} \inf_{v_n\in V_n} \|u-v_n\|.</math>
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| This means, that up to the constant <math>C/c</math>, the Galerkin solution <math>u_n</math>
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| is as close to the original solution <math>u</math> as any other vector in <math>V_n</math>. In particular, it will be sufficient to study approximation by spaces <math>V_n</math>, completely forgetting about the equation being solved.
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| ====Proof====
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| Since the proof is very simple and the basic principle behind all Galerkin methods, we include it here:
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| by ellipticity and boundedness of the bilinear form (inequalities) and Galerkin orthogonality (equals sign in the middle), we have for arbitrary <math>v_n\in V_n</math>:
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| :<math>c\|u-u_n\|^2 \le a(u-u_n, u-u_n) = a(u-u_n, u-v_n) \le C \|u-u_n\| \, \|u-v_n\|.</math>
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| Dividing by <math>c \|u-u_n\|</math> and taking the infimum over all possible <math>v_n</math> yields the lemma.
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| ==References==
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| <!--
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| <ref name=ErnGuermond> A. Ern, J.L. Guermond, ''Theory and practice of finite elements'', Springer, 2004, ISBN 0-387-20574-8 </ref>
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| <ref name=BrennerScott> S. Brenner, R. L. Scott, ''The Mathematical Theory of Finite Element Methods'', 2nd edition, Springer, 2005, ISBN 0-387-95451-1 </ref>
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| <ref name=Ciarlet> P. G. Ciarlet, ''The Finite Element Method for Elliptic Problems'', North-Holland, 1978, ISBN 0-444-85028-7 </ref>
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| <ref name=Saad> Y. Saad, ''Iterative Methods for Sparse Linear Systems'', 2nd edition, SIAM, 2003, ISBN 0-89871-534-2 </ref>
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| -->
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| <references />
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| ==External links==
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| * {{springer|title=Galerkin method|id=p/g043040}}
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| * [http://math.fullerton.edu/mathews/n2003/GalerkinMod.html Galerkin's Method]
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| * [http://mathworld.wolfram.com/GalerkinMethod.html Galerkin Method from MathWorld]
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| {{Mathematics-footer}}
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| {{DEFAULTSORT:Galerkin Method}}
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| [[Category:Numerical analysis]]
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| [[Category:Numerical differential equations]]
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| [[Category:Articles containing proofs]]
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