Math 2.0

Calculus of variations and optimal control; optimization Variational inequalities Theorem

Lions–Stampacchia theorem

Builds on Hilbert spaceCoercive bilinear formConvex setClosed setContinuous dual space

Statement

Let HH be a real Hilbert space and let K⊆HK \subseteq H be a nonempty closed convex set. Let a ⁣:H×H→ℝa \colon H \times H \to \R be a bounded coercive bilinear form, not necessarily symmetric: there are constants M,α>0M, \alpha > 0 with ∣a(u,v)∣≤M∥u∥∥v∥\abs{a(u, v)} \le M \norm{u} \norm{v} and a(v,v)≥α∥v∥2a(v, v) \ge \alpha \norm{v}^2 for all u,v∈Hu, v \in H. Let ℓ\ell be an element of the continuous dual space H∗H^*. Then there is exactly one u∈Ku \in K such that a(u,v−u)≥ℓ(v−u)for all v∈K.a(u, v - u) \ge \ell(v - u) \quad \text{for all } v \in K. If moreover aa is symmetric, then uu is the unique minimizer over KK of the function v↦12a(v,v)−ℓ(v)v \mapsto \tfrac12 a(v, v) - \ell(v).

Remarks

By the Riesz representation theorem there are a bounded linear operator AA on HH and a vector f∈Hf \in H with a(u,v)=⟨Au,v⟩a(u, v) = \ip{Au}{v} and ℓ(v)=⟨f,v⟩\ell(v) = \ip{f}{v}. The inequality then says that u=PK(u−ρ(Au−f))u = P_K\big(u - \rho (Au - f)\big) for any ρ>0\rho > 0, where PKP_K is the projection onto KK given by the Hilbert projection theorem. For 0<ρ<2α/M20 < \rho < 2\alpha / M^2 the map v↦PK(v−ρ(Av−f))v \mapsto P_K\big(v - \rho (Av - f)\big) is a contraction of KK, so the Banach fixed-point theorem gives existence and uniqueness. Uniqueness also follows directly: if u1,u2u_1, u_2 are two solutions, adding the two inequalities gives a(u1−u2,u1−u2)≤0a(u_1 - u_2, u_1 - u_2) \le 0, hence u1=u2u_1 = u_2.

For K=HK = H the inequality becomes the equation a(u,w)=ℓ(w)a(u, w) = \ell(w) for all w∈Hw \in H, and the theorem reduces to the Lax–Milgram theorem. Example: the obstacle problem. Let Ω⊆ℝn\Omega \subseteq \R^n be bounded and open, H=H01(Ω)H = H^1_0(\Omega), a(u,v)=∫Ω∇u⋅∇v dxa(u, v) = \int_\Omega \nabla u \cdot \nabla v \, dx, and K={v∈H:v≥ψ a.e.}K = \set{v \in H : v \ge \psi \text{ a.e.}} for an obstacle ψ\psi such that KK is nonempty. The theorem gives a unique u∈Ku \in K that minimizes the Dirichlet energy among functions lying above ψ\psi. Coercivity cannot be dropped: for H=ℝH = \R, K=[0,∞)K = [0, \infty), a=0a = 0 and ℓ(v)=v\ell(v) = v, the inequality 0≥v−u0 \ge v - u for all v≥0v \ge 0 has no solution.

Going deeper

For a student

This is the basic existence theorem for variational inequalities and the constrained version of the Lax–Milgram theorem. In the symmetric case it is a statement about minimizing a strictly convex quadratic function over a closed convex set. The nonsymmetric case needs the fixed-point argument, since no energy is available. It applies to obstacle problems, to contact problems in elasticity such as the Signorini problem, and, after a change of unknown, to some free boundary problems.

Reading path

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  1. Closed set concept
  2. Coercive bilinear form concept
  3. Continuous dual space concept
  4. Convex set concept
  5. Hilbert space concept
  6. Lions–Stampacchia theorem statement

Where this leads

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Further reading

  1. Web https://en.wikipedia.org/wiki/Variational_inequality
About this page
TagH80M01T0H8
URIm2://H80M01T0H8
Kindstatement, theorem
WritingW0 stub
MSC49J40, 47J20, 35J86
StatusThis copy of the site has no build data. Run m2 status H80M01T0H8.
AboutVariational inequality
UsesHilbert space, Coercive bilinear form, Convex set, Closed set, Continuous dual space

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