Math 2.0

Calculus of variations and optimal control; optimization Definition

Morrey quasiconvexity

Builds on Sobolev spaceConvex function on R^nRank-one convexity

Definition

Let m,n≥1m, n \ge 1 and let f ⁣:ℝm×n→ℝf \colon \R^{m \times n} \to \R be continuous. The function ff is quasiconvex (in the sense of Morrey) if f(ξ)≤1∣D∣∫Df(ξ+∇φ(x)) dxf(\xi) \le \frac{1}{\abs{D}} \int_D f\big(\xi + \nabla \varphi(x)\big) \, dx for every bounded open set D⊆ℝnD \subseteq \R^n, every ξ∈ℝm×n\xi \in \R^{m \times n} and every φ∈W01,∞(D;ℝm)\varphi \in W^{1,\infty}_0(D; \R^m). Here W01,∞(D;ℝm)W^{1,\infty}_0(D; \R^m) is the Sobolev space of Lipschitz maps that vanish on ∂D\partial D. The number ∣D∣\abs{D} is the Lebesgue measure of DD.

Remarks

If the inequality holds for one bounded open set DD with ∣∂D∣=0\abs{\partial D} = 0, it holds for all of them; often DD is the unit cube.

Example: every convex ff is quasiconvex. Since φ=0\varphi = 0 on ∂D\partial D, the average of ∇φ\nabla \varphi over DD is 00, and Jensen's inequality gives the inequality.

Non-example: f(ξ)=−∣ξ∣2f(\xi) = -\abs{\xi}^2 is not quasiconvex. For φ≠0\varphi \ne 0, the cross term 2∫Dξ:∇φ dx2 \int_D \xi : \nabla \varphi \, dx vanishes, so the average of f(ξ+∇φ)f(\xi + \nabla \varphi) is −∣ξ∣2−1∣D∣∫D∣∇φ∣2 dx<f(ξ)-\abs{\xi}^2 - \frac{1}{\abs{D}} \int_D \abs{\nabla \varphi}^2 \, dx < f(\xi).

Every quasiconvex function is rank-one convex. For m=1m = 1 or n=1n = 1, quasiconvexity is ordinary convexity. For m≥3m \ge 3 and n≥2n \ge 2, Šverák gave a rank-one convex function that is not quasiconvex; the case m=2m = 2 is open.

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  1. Euclidean space object
  2. Function concept
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  4. Sobolev space concept
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  6. Convex function on R^n concept
  7. Morrey quasiconvexity definition

Further reading

  1. Web https://en.wikipedia.org/wiki/Quasiconvexity_(calculus_of_variations)
About this page
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MSC49J45, 26B25
DefinesMorrey quasiconvexity
UsesSobolev space, Convex function on R^n, Rank-one convexity

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