Math 2.0

Numerical analysis Definition

Galerkin method

Builds on Hilbert spaceBilinear formContinuous dual spaceLax–Milgram theoremCoercive bilinear form

Definition

Let HH be a real Hilbert space, and let B ⁣:H×H→ℝB \colon H \times H \to \R be a bounded bilinear form. Let ff be a bounded linear functional on HH, an element of the continuous dual space. Consider the problem of finding u∈Hu \in H with B(u,v)=f(v)B(u, v) = f(v) for all v∈Hv \in H. Let VNV_N be a finite-dimensional subspace of HH. The Galerkin method replaces this problem by the following one: find uN∈VNu_N \in V_N such that B(uN,v)=f(v)for all v∈VN.B(u_N, v) = f(v) \quad \text{for all } v \in V_N. The element uNu_N is the Galerkin approximation of uu in VNV_N.

Remarks

If φ1,…,φN\varphi_1, \ldots, \varphi_N is a basis of VNV_N and uN=∑jcjφju_N = \sum_j c_j \varphi_j, the problem is the linear system ∑j=1NB(φj,φi) cj=f(φi)\sum_{j=1}^{N} B(\varphi_j, \varphi_i) \, c_j = f(\varphi_i) for i=1,…,Ni = 1, \ldots, N. If BB is coercive with constant α\alpha and bounded with constant MM, the Lax–Milgram theorem applied on VNV_N gives a unique uNu_N. Subtracting the two problems gives Galerkin orthogonality: B(u−uN,v)=0B(u - u_N, v) = 0 for all v∈VNv \in V_N. From it follows Céa's lemma: ∥u−uN∥≤Mαinf⁡v∈VN∥u−v∥\norm{u - u_N} \le \frac{M}{\alpha} \inf_{v \in V_N} \norm{u - v}.

Example: for −u′′=1-u'' = 1 on (0,1)(0, 1) with u(0)=u(1)=0u(0) = u(1) = 0, take H=H01(0,1)H = H^1_0(0, 1), B(u,v)=∫01u′v′ dxB(u, v) = \int_0^1 u' v' \, dx, f(v)=∫01v dxf(v) = \int_0^1 v \, dx and V1V_1 spanned by φ(x)=x(1−x)\varphi(x) = x(1 - x). Then B(φ,φ)=∫01(1−2x)2 dx=1/3B(\varphi, \varphi) = \int_0^1 (1 - 2x)^2 \, dx = 1/3 and f(φ)=1/6f(\varphi) = 1/6, so u1=12x(1−x)u_1 = \frac{1}{2} x(1 - x). This is the exact solution, as Céa's lemma predicts, since the exact solution lies in V1V_1.

Non-example: choosing uN∈VNu_N \in V_N so that B(uN,w)=f(w)B(u_N, w) = f(w) for all ww in a different subspace WN≠VNW_N \ne V_N is not the Galerkin method in the sense above. It is called a Petrov–Galerkin method, and its analysis needs an inf-sup condition instead of coercivity.

Reading path

To understand this page from the ground up, read these 96 pages in order. The foundations come first.

  1. Bilinear form concept
  2. Closed set concept
  3. Coercive bilinear form concept
  4. Compact operator concept
  5. Continuous dual space concept
  6. Convex set concept
  7. Element definition
  8. Extended real number line object
  9. Hilbert space concept
  10. Hölder continuity concept
  11. Inequality of arithmetic and geometric means statement
  12. Linear form concept
  13. Lp space concept
  14. Orthogonal complement concept
  15. Proposition concept
  16. Real numbers object
  17. Set bounded above definition
  18. Sobolev space concept
  19. Uniform metric on bounded functions example
  20. Vector space definition
  21. Weak derivative concept
  22. Weak solution concept
  23. Set definition
  24. Young's inequality for products statement
  25. Sobolev embedding theorem statement
  26. Conjunction definition
  27. Disjunction definition
  28. Implication definition
  29. Predicate definition
  30. Supremum definition
  31. Inner product definition
  32. Linear map definition
  33. Linear subspace definition
  34. Norm definition
  35. Empty set object
  36. Family of sets definition
  37. Ordered pair definition
  38. Hölder's inequality statement
  39. Intersection definition
  40. Union definition
  41. Existential quantifier definition
  42. Universal quantifier definition
  43. Inner product space definition
  44. Orthogonal vectors definition
  45. Endomorphism definition
  46. Linear form definition
  47. Sum of subspaces definition
  48. Cartesian product definition
  49. Union of a family of sets definition
  50. Subset definition
  51. Uniqueness quantifier definition
  52. Norm induced by an inner product definition
  53. Orthogonal complement definition
  54. Riesz representation theorem in finite dimensions statement
  55. Sobolev inequality statement
  56. Direct sum of subspaces definition
  57. Binary relation definition
  58. Topological space definition
  59. Parallelogram law statement
  60. A space is the direct sum of a subspace and its orthogonal complement statement
  61. Projection definition
  62. Sequential compactness definition
  63. Function definition
  64. Subspace topology definition
  65. Orthogonal projection definition
  66. Preimage of a set definition
  67. Restriction of a function definition
  68. Orthogonal projection is the closest point statement
  69. Metric space definition
  70. Subspace metric definition
  71. Convergence of a sequence in a metric space definition
  72. Open ball definition
  73. Hilbert projection theorem statement
  74. Diameter of a set definition
  75. Metric topology definition
  76. Epsilon characterisation of Cauchy sequences statement
  77. Totally bounded set definition
  78. Riesz representation theorem statement
  79. Open set definition
  80. Complete metric space definition
  81. Open cover definition
  82. Open sets characterised by neighbourhoods statement
  83. Open sets of a metric space statement
  84. Compact space definition
  85. Continuity at a point of a topological space definition
  86. Compact set definition
  87. Lebesgue number lemma statement
  88. Epsilon-delta continuity in metric spaces statement
  89. Compactness and sequential compactness agree in metric spaces statement
  90. Equicontinuity definition
  91. Compact iff complete and totally bounded statement
  92. Arzelà–Ascoli theorem statement
  93. Rellich–Kondrachov theorem statement
  94. Poincaré inequality statement
  95. Lax–Milgram theorem statement
  96. Galerkin method definition

Further reading

  1. Web https://en.wikipedia.org/wiki/Galerkin_method
About this page
TagMR4D29XAPB
URIm2://MR4D29XAPB
Kinddefinition
WritingW0 stub
MSC65N30, 35A15
DefinesGalerkin method
UsesHilbert space, Bilinear form, Continuous dual space, Lax–Milgram theorem, Coercive bilinear form
Changed2 November 2026

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