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Strict convexity gives uniqueness of a minimiser
Statement
Let be a convex subset of a real vector space and let be proper and strictly convex (Convex and strictly convex functionals on a convex subset of a real vector space, Proper, coercive and weakly lower semicontinuous extended-real functionals). If both minimise on , then .
Facts & Assumptions
Given: A convex subset of a real vector space and a proper, strictly convex extended-real functional (Convex and strictly convex functionals on a convex subset of a real vector space, Proper, coercive and weakly lower semicontinuous extended-real functionals); points that both minimise on , in the sense that .
Strict convexity: for with and one has ; convexity gives (Convex and strictly convex functionals on a convex subset of a real vector space).
The infimum is a lower bound: for every (Greatest lower bound (infimum)).
Proof
Set-up. Let both minimise and suppose for contradiction that . Properness gives , so is finite.
Strict convexity at the midpoint. The midpoint lies in the convex set , and strict convexity with applies because and : hence .
Contradiction. Step 2.1 gives , while [F2] gives since . This is impossible, so ; two distinct minimisers cannot exist.
Remarks
Properness is necessary. Without it the statement is false: on the functional is convex and vacuously strictly convex, and and are two distinct points at which equals . Properness, equivalently the existence of a finite competitor, is what excludes this degenerate case, and it holds in the finite-valued integral-functional applications (Proper, coercive and weakly lower semicontinuous extended-real functionals).
Depends on
Used by
- Non-strict convexity allows many minimisers Counterexample
- Euler-Lagrange is necessary but not sufficient without convexity Remark
- Stationarity is sufficient for a global minimum of a convex differentiable functional Theorem
- The direct method for convex integral functionals Theorem
- The Dirichlet principle for the Poisson equation Theorem
Dependency tree · two levels
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Sources
- Gerald Teschl, Partial Differential Equations: From Classical to Modern (2026 author manuscript; complete 392-page archived text) (standard reference, not scraped)
- Riccardo Cristoferi, Calculus of Variations: Lecture Notes, Carnegie Mellon University 2016 (complete 133-page notes) (standard reference, not scraped)